Intrinsic capacity and stroke risk in a multiple cohort study

Domain: chemistry
Published: 2026-03-11
Editorial outcome: major_revision

Abstract
Intrinsic capacity is a concept established by the World Health Organization (WHO). The concept aims to represent
the total of a person's physical and mental abilities, measured across five domains: cognition, psychological, sensory,
vitality, and locomotor that were identified as crucial for healthy aging. The aim being to shift focus from disease to
function to predict health, disability, and frailty. In this large-scale cohort study, we aim to investigate the association
between intrinsic capacity and incident stroke. The study includes 184,219 participants aged 40 years or older. Intrinsic
capacity is assessed across five domains according to the WHO Integrated Care for Older People framework. We use Cox
proportional hazards regression models to examine this association and perform stratified and sensitivity analyses to
evaluate domain-specific contributions and robustness. Here we show that both overall intrinsic capacity and each of its
five domains are significantly associated with stroke incidence, with the strongest association observed among adults
aged 80 years or older. These findings highlight intrinsic capacity as a promising, multidimensional target for primary
stroke prevention in an aging population.

Introduction
Over the past three decades, substantial progress has been made in stroke prevention and management, supported by
advancements in medical science and public health systems.1 From 1990 to 2019, the global stroke mortality rate
decreased by 36.4%.2 Nevertheless, recent epidemiological data indicate that stroke remains a leading contributor to
global morbidity and mortality.3 By 2021, the global prevalence of stroke reached 93.8 million, with a 70% increase in
incident cases. Stroke-related deaths and disability-adjusted life years (DALYs) rose by 44% and 32%, respectively.
Currently, the global economic burden of stroke exceeds USD 890 billion annually, and in the absence of effective
mitigation strategies, it is projected to double by 2050.4 Thus, addressing the modifiable risk factors for stroke has
become a critical priority in global public health.

Well-recognised risk factors for stroke include hypertension, diabetes, tobacco use, physical inactivity, and
environmental exposure. The Global Burden of Disease data from 1990 to 2021 highlighted notable shifts in the
distribution of these risk factors. For example, salt intake and tobacco use decreased by 4.6% and 12.8%, respectively.5
However, there have been marked increases in the prevalence of high body mass index (BMI), elevated fasting plasma
glucose levels, increased blood pressure, and exposure to extreme ambient temperatures. Of particular concern, stroke-
related DALYs attributable to heat exposure among individuals aged 65 years and older increased by 72.4% between
2017 and 2021 compared to 2000–2004.6 Despite the overall decline in stroke mortality, population aging has led to a
nearly 200% increase in stroke incidence among adults aged 80 years and older, substantially contributing to the global
stroke burden.7 Age and gender are commonly regarded as non-modifiable risk factors; however, the increasing age-
related stroke burden poses substantial and growing challenges for global health systems.

The rapid demographic shift toward an aging global population has altered the epidemiology of non-communicable
diseases, thereby necessitating novel approaches for risk assessment and health promotion.8 To address this issue, the
World Health Organization (WHO) introduced the concept of intrinsic capacity in 2015, a cornerstone of its subsequent
"Decade of Healthy Ageing (2021-2030)" global strategy.9 While often related, intrinsic capacity, as defined by WHO,
differs from functional decline by focusing on the individual's inherent physical and mental capacities rather than solely
their ability to perform daily activities. This framework emphasises maintaining and enhancing the physical and mental
capacities that support healthy aging, thereby enabling older adults to live independently and preserve their functional
abilities. This evolution necessitates a paradigm shift from managing single diseases toward delivering comprehensive,
people-centered primary and long-term care services, with a central focus on preserving intrinsic capacity. Empirical
evidence supports the utility of the five-domain model of intrinsic capacity as a valid construct for assessing functional
health in older adults.10,11 The decline in intrinsic capacity has been associated with an increased risk of frailty, falls,
cardiovascular events, and all-cause mortality. However, there remains a paucity of research examining the relationship
between intrinsic capacity and clinically relevant outcomes such as stroke. Strengthening the evidentiary foundation in
this area is essential for informing public health interventions, supporting clinical decision-making, and guiding policy
development to delay the onset of age-related conditions.12,13

This study is the first to use a large population cohort to identify the association between the development trajectory
of intrinsic capacity and the incidence of stroke. The complexity of assessing the correlation between intrinsic capacity
development and clinical outcomes has led to a widespread concern that has not been well addressed, particularly amid a
growing stroke burden due to population aging. Our findings are expected to support population-based stroke prevention,
provide effective interventions to address the rising burden of stroke associated with population aging, and ultimately
contribute to reducing burden on healthcare systems.

Results
All eligible participants included in the study are shown in Figure 1. During the 1,293,239 person-years of follow-up,
15,125 incident strokes were identified. The proportion of incident strokes was 48.4% in men and 51.6% in women.

The baseline characteristics of the participants in the four cohorts are summarised in Table 1. The overall mean age
was 61.4 ± 10.3 (mean [± SD]) years. Among these cohorts, SHARE participants had the highest mean age (63.4 ± 10.2
years), whereas CHARLS participants were the youngest on average (55.0 ± 9.4 years). Individuals who experienced
incident stroke had a mean age of 70.3 ± 11.4 years. After adjusting for all covariates, participants in the ELSA cohort
exhibited the highest intrinsic capacity scores (mean 35.1 ± 5.20), whereas those in the CHARLS cohort had the lowest
scores (mean 30.6 ± 5.24) (Supplementary Figure 3).

Table 2 presents the HRs for the association between intrinsic capacity and incident stroke among participants from
all four cohorts. Participants who developed incident stroke were more likely to be men, older, unmarried, low-income,
current smokers, non-drinkers, physically inactive, and to report poor self-rated health, hypertension or diabetes.
Compared with individuals in the lowest quartile, those in the second, third, and highest quartiles demonstrated
progressively lower risks of stroke, with HRs of 0.75 (95% CI 0.72–0.79), 0.70 (95% CI 0.67–0.74), and 0.64 (95% CI
0.61–0.68), respectively. A significant negative linear association was observed between intrinsic capacity levels and
stroke risk (P < 0.001). The gender-specific results are summarized in Table 3.

HRs for the five domains of intrinsic capacity associated with incident stroke are shown in Table 4. All five domains
(cognitive, locomotor, vitality, sensory, and psychological capacity) were significantly associated with the risk of stroke.
As the scores in these subdomains increased, the risk of stroke correspondingly decreased. The linear trend test
demonstrated strong statistical significance (P < 0.001).

The results of the sensitivity analyses are presented in Table 5, Table 6 and Figure 2. Table 5 shows that across the
four cohorts, higher levels of intrinsic capacity were consistently associated with a lower risk of stroke, with a
statistically significant linear trend. Age-stratified analyses further revealed that the association between intrinsic capacity
and incident stroke was stronger among individuals aged ≥80 years, with HRs of 0.67 (95% CI 0.58–0.78), 0.57 (95% CI
0.47–0.70), and 0.50 (95% CI 0.35–0.66), compared to HRs of 0.77 (95% CI 0.74–0.81), 0.73 (95% CI 0.69–0.76), and
0.67 (95% CI 0.63–0.71) among those aged <80 years (Table 6).

Figure 2 illustrates the associations between changes in intrinsic capacity and stroke risk. Compared with
participants who maintained moderate intrinsic capacity at baseline, midpoint, and endpoint, those with persistently low
intrinsic capacity had an increased risk of stroke (HR 2.11, 95% CI 1.95–2.19), whereas those with consistently high
intrinsic capacity had a reduced risk (HR 0.81, 95% CI 0.71–0.93). Notably, participants whose intrinsic capacity
declined from a moderate level at baseline to a lower level at the midpoint experienced a higher risk of stroke than those
who maintained moderate intrinsic capacity (HR 1.57, 95% CI 1.44–1.72). Furthermore, participants with low intrinsic
capacity at baseline who showed progressive improvement by the endpoint had a substantially reduced risk compared
with those with persistently low intrinsic capacity (HR 0.36, 95% CI 0.25–0.53). Conversely, participants with high
intrinsic capacity at baseline who experienced a progressive decline by the endpoint had an increased risk compared with
those who consistently maintained high capacity (HR 1.65, 95% CI 1.37–2.08).

Methods
Ethics approval and consent to participate
This study employed publicly available aggregated data without individual-level identifiers. Ethical approval was
not required as the utilized data were already anonymized and in the public domain. The study was conducted in
accordance with the Declaration of Helsinki.

Study design and participants
This large-scale cohort study pooled data from four longitudinal studies: the Health and Retirement Study (HRS);40
the English Longitudinal Study of Aging (ELSA);41 the Survey of Health, Aging, and Retirement in Europe (SHARE);42
and the China Health and Retirement Longitudinal Study (CHARLS).43 The HRS utilised a multistage probability design
based on the US population. The SHARE covered 29 countries using probability sampling. The ELSA is an annual cross-
sectional survey designed for the English population. The CHARLS employed a multistage probability design across
China. Data coverage spanned 1992–2020 for HRS, 2002–2019 for ELSA, and 2004–2020 for SHARE (with the
exception of 2008). Data collection follows a biennial schedule. CHARLS contributed data from the 2011, 2013, 2015,
and 2018 waves. Response rates varied by study design: HRS (85–90%, steady-state design), CHARLS (85%, at
baseline), ELSA (82% in Wave 2, post-technological update), and SHARE (61% in Wave 1, due to multinational
complexity). This study utilizes data from four large-scale, nationally representative cohort studies, each of which
provides a sample size sufficient to ensure adequate statistical power. In total, 234,340 participants, including their
spouses, were surveyed biennially between 1992 and 2020. Supplementary Tables 1 and 2 summarize the baseline
characteristics of participants. This study utilized publicly available data; therefore, no pre-specified exclusion criteria
were applied.

Intrinsic capacity measures
Intrinsic capacity was measured in accordance with the WHO guidelines and assessed across five domains:
cognitive, locomotor, vitality, sensory, and psychological capacity.44 Intrinsic capacity scores were derived for all the
participants based on five domains, with total scores ranging from 0 to 51 and higher scores indicating greater intrinsic
capacity.

Cognitive capacity was evaluated dimensions using two subscales: memory and orientation. The word recall test,
comprising 20 items, assessed immediate and delayed memory, whereas the orientation test included four items related to
time orientation. The scores ranged from 0 to 24, with higher scores indicating better cognitive function. Locomotor
capacity was assessed using the Instrumental Activities of Daily Living (IADL) scale and the chair stand test. Participants
who reported no difficulty in tasks such as using a phone, managing money, shopping, preparing meals, and taking
medications were assigned 5 points; otherwise, 0 points were assigned. In the chair stand test, participants who were able
to rise from a chair without using their arms scored 1 point, whereas those requiring assistance scored 0. Vitality, a
physiological component of intrinsic capacity, reflects an individual’s energy balance and metabolic status. In the
Integrated Care for Older People (ICOPE) screening framework, nutritional assessment is applied to evaluate vitality.
BMI is a widely accepted, simple, and practical measure of nutritional and metabolic status in community-based primary
healthcare.45 Vitality was evaluated using BMI based on the WHO criteria. BMI categories were scored as follows: 18.5–
24.9 kg/m² = 3 points; 25.0–34.9 kg/m² = 2 points; <18.5 kg/m² = 1 point; and >35.0 kg/m² = 0 points. Participants from
CHARLS were categorized according to Asian-specific criteria, with BMI scored as follows: 18.5–22.9 kg/m² = 3 points;
23.0–29.9 kg/m² = 2 points; <18.5 kg/m² = 1 point; >30.0 kg/m² = 0 points. Sensory capacity was assessed using self-
reported eyesight and hearing rated on a five-point scale from poor (1 point) to excellent (5 points). Although grip
strength is commonly employed as a proxy indicator of vitality, it was not included in this study due to the lack of
corresponding measurements in the earlier cohorts. Eyesight scores were calculated as the average of the distance and
near-vision ratings. The highest score for sensory capacity is 10 points. Psychological capacity was measured using the
Center for Epidemiologic Studies Depression Scale (CES-D), which comprised eight items assessing the participants’
feelings over the previous week. The total score was calculated after reversing the relevant items, with values ranging
from 0 to 8. The detailed measurement methods for intrinsic capacity are provided in Supplementary Table 3.

Covariates
Covariates were assessed during each observation period from 1992 to 2020. Participants self-reported their
demographic characteristics, including gender, marital status, educational level, and individual income. Age was
calculated from the reported date of birth. Smoking status was assessed by asking participants whether they currently
smoked; those who reported ever smoking were further asked about the age and year at which they started and stopped
smoking. Alcohol use was assessed by asking, “During the past year, did you drink any alcoholic beverages, such as
beer, wine, or liquor?” Respondents who reported drinking provided additional information on beverage types, frequency
of consumption, and subjective experiences related to drinking. Physical activity was evaluated according to type,
intensity, and frequency. General health status was self-reported on a five-point scale ranging from very good to very
bad. Participants also reported their medical history. However, data on specific medication classes, detailed dietary
habits, nuanced social network characteristics, and direct measures of cognitive reserve were not available in this study.

Outcomes
At baseline, 2,850 participants with a prior physician-confirmed diagnosis of stroke were excluded from the
outcome assessment. The remaining eligible participants were continuously monitored for their health status and survival
throughout the follow-up period. Stroke was diagnosed by physicians based on clinical assessment; however, detailed
classification into ischemic or hemorrhagic subtypes was not consistently available across all cohorts, representing a
limitation in our outcome ascertainment.

Statistical analysis
A total of 184,219 participants aged ≥40 years, were included in the analysis. The cohort comprised 81,754 (44.4%)
men and 102,465 (55.6%) women, with a mean baseline age of 61.4 years. Gender-based differences were carefully
considered in this study. Participants’ gender was self-reported, and analyses were stratified accordingly. Baseline
characteristics across the different cohorts are summarised as frequencies and percentages. Person-years of follow-up
were calculated from the baseline to either a physician-confirmed stroke diagnosis or the end of the observation period.
Sensitivity analyses suggested that the data were likely missing not at random (MNAR); therefore, we employed
complete case analysis to address the missing data. We restricted our analysis to complete cases by excluding
observations with missing data.

Cox proportional hazards (CPH) regression models were used to examine the association between intrinsic capacity
levels and incident stroke. Intrinsic capacity scores were categorized into quartiles (Q1–Q4), with the lowest quartile
(Q1) serving as the reference group, and three dummy variables were created to represent different exposure levels. The
proportional hazard assumption was tested using Schoenfeld residuals and graphical diagnostics (Supplementary Figure 1
and 2). Person-years exposed to relevant risk factors were calculated, and hazard ratios (HRs) with 95% confidence
intervals (CIs) were estimated to quantify stroke risk relative to intrinsic capacity levels. Stratified CPH models further
assessed the association between each domain of intrinsic capacity and stroke incidence. All models were adjusted for
potential confounders, including age, gender, marital status, individual income, educational level, smoking status, alcohol
use, physical activity, hypertension, diabetes, and self-reported health status.

We performed formal interaction tests to assess effect modification by age, gender, and cohort. The tests revealed
significant interactions (P for interaction < 0.001), indicating that the association between intrinsic capacity and stroke
differed by age groups, gender, and cohorts.

Sensitivity analyses were conducted to evaluate the robustness of the association between intrinsic capacity and
incident stroke. First, analysis of covariance (ANCOVA) was used to compare the intrinsic capacity levels across the four
cohorts. Within each cohort, CPH models were used to evaluate the association between intrinsic capacity and the risk of
stroke. Second, we performed an age-stratified analysis by CPH models for individuals aged <80 years and those aged
≥80 years to assess the association between intrinsic capacity and stroke across different age groups. Third, intrinsic
capacity was assessed at baseline, midpoint, and endpoint, and classified into high, medium, or low categories at each
time point. Based on intrinsic capacity levels at baseline, midpoint, and endpoint, three control groups were established
to examine the association between intrinsic capacity trajectories and incident stroke. Fourth, to verify the robustness of
the hypothesized association between intrinsic capacity and stroke, a directed acyclic graph (DAG) was developed
(Supplementary Figure 4). Additionally, intrinsic capacity scores were included in the model as a continuous variable
(Supplementary Table 4).

All statistical tests were two-sided, and P-values < 0.05 were deemed statistically significant. Data analyses were
performed using SAS (version 9.4; SAS Institute Inc., Cary, NC, USA) and R (version: 4.1.2). Schematic diagrams and
mechanistic models were developed using Adobe Photoshop 2023 to visually summarize key findings.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This study, using data derived from four cohorts, investigated the association between intrinsic capacity (IC) and the risk of incident stroke. The IC concept provides a novel and positive approach to improving the care of community-dwelling older adults by addressing optimal functioning across its five domains. Although the operationalization of IC based on well-known indicators of physical and mental functioning is justified, the finding of this study did not provide a lot of new insights into this field. Also, there is a noticeable disconnect between the findings of this study and its integration into daily practice.\nIn addition to the above comment, there are a few methodology concerns from me:\n1. It is unclear to me how authors synthesize scores from five domains. The synthetic algorithm is required in the manuscript.\n2. The author is expected to provide detailed measurement scales and measurement methods of five domains in the appendix.\n3. The author is expected to include descriptions of the design of all four included cohorts both in the main manuscript in brief and in the appendix in detail.\n4. The score of CI largely depends on individuals’ frailty status; thereafter, it is really hard to eliminate the possibility of reversing causation between CI and stroke. The author did not include any method that could potentially eliminate the issue of reverse causality.\n5. The author compared the different risks among different quartiles, but did not report the baseline characteristics of different quartiles. The potential extreme imbalance among different quartiles cannot be fully eliminated by the adjustment of regression model.\n6. The author did not report how the different results from four cohorts have been synthesized. Also, the detailed results of each individual cohort need to be reported separately in the appendix.\n7. I failed to find any description on how missing values of covariates to be processed in the whole manuscript.\n8. In the flow-chart, the author said all individuals with missing data for IC measurement were excluded from this study. In this case, the author needs to compare the baseline characteristics of the entire cohort and eligible participants and provide comprehensive discussion on potential selection bias.", "reviewer_2": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_3": "This study examines the association between intrinsic capacity and incident stroke using pooled date from four large-scale longitudinal cohorts. The question is clearly relevant given population ageing.\nKey strengths;\n- Large, multinational cohorts - very large sample size\n- Consistent results across cohorts and subanalyses\n- Strong statistical signal with dose-response relationship\n- Figures and tables clear\nConcerns;\n1. Given prior work on frailty and multi morbidity, the finding that global functional status predicts stroke risk is not surprising or entirely novel. The authors should explicitly discuss what additional predictive value IC adds beyond existing constructs such as frailty, multi morbidity etc.\n2. At least one study has already reported associations of IC with CVD outcomes, specifically including stroke (PMID: 37434422). This hasn't been cited. Please discuss what the incremental contribution of this study is and reference this paper.\n3. Please explain why IC ws measured differently in the CHARLS cohort with Asian-specific BMI cutoffs\n4. Why use quartiles modelling instead of continuous modelling?\n4. The hazard ratios are very large for an observational association. Consider whether there could be an element of reverse causality here (subclinical cerebrovascular or small vessel disease may lower IC domains such as cognition and locomotor) before an overt stroke. Also avoid causal phrasing of intrinsic capacity as a TARGET for prevention rather than a MARKER for stroke risk.\nI recommend major revision.", "reviewer_4": "Key Results:\nThis large-scale, multi-cohort study demonstrated a significant and consistent inverse association between intrinsic capacity —assessed across the five WHO-defined domains—and incident stroke risk in adults aged 40 years and older. Notably, individuals with higher and stable intrinsic capacity levels exhibited lower stroke incidence, with the strongest associations observed among those aged 80 years and above. Each intrinsic capacity domain (cognitive, locomotor, vitality, sensory, and psychological) independently contributed to stroke risk reduction, underscoring intrinsic capacity as a promising target for primary stroke prevention in aging populations.\nValidity:\nThe study’s conclusions are well-supported by its longitudinal design, large sample size, robust analyses across diverse international cohorts, and sensitivity testing, all of which enhance the validity of the findings. However, certain limitations warrant consideration: the absence of a standardized global assessment tool for intrinsic capacity, lack of formal inter-rater reliability testing, and reliance on clinical stroke diagnoses without imaging confirmation may introduce measurement variability and diagnostic uncertainty. While these factors do not invalidate the overall findings, they suggest caution when generalizing the results.\nSignificance:\nThese findings hold important implications for stroke prevention and healthy aging. The study reinforces the World Health Organization’s framework for integrated care of older adults and aligns with emerging paradigms in stroke prevention by identifying intrinsic capacity as a modifiable and measurable construct linked to stroke incidence.\nData and Methodology:\nOverall, the study is well-designed; however, the description of covariate data collection lacks critical details that would improve clarity and completeness. It remains unclear whether standardized assessment protocols were uniformly applied across the four cohorts or if significant methodological differences existed.\nAnalytical Approach:\nGiven the variability in intrinsic capacity scores across cohorts and the absence of statistical adjustments for study site or cohort, the results may be confounded by cohort-specific differences. Additionally, the authors did not explicitly account for repeated intrinsic capacity measurements in their Cox regression analyses, potentially compromising the validity of estimated associations by ignoring within-subject correlations over time. These limitations should be acknowledged and addressed in future analysis.\nSuggested Improvements:\n1. Covariate Data Collection: The authors should provide detailed descriptions of covariate data collection methods, specifying whether data were obtained via self-report, interviews, medical records, or physical examinations. For variables such as physical activity, alcohol use, and smoking status, clarifying the specific questions or scales used, along with procedures for handling missing data and validating self-reported measures, would enhance rigor and transparency.\n2. Statistical Analysis: The analytical approach should be revised to incorporate models that account for repeated measurements and within-subject correlations (e.g., mixed-effects Cox models), thereby improving the validity of association estimates.\n3. Figure 2: The figure lacks clarity, particularly in the absence of legends. The positioning of the five domains centrally—despite being measured first—is confusing, and it is unclear whether the odds ratios represent associations between changes in overall intrinsic capacity or changes in each domain with stroke risk. Clarification or redesign is recommended.\n4. Table 3 – Alcohol Use: The finding that alcohol consumption appears protective is puzzling. Confidence intervals are unusually narrow, and reverse causation is plausible, as individuals with health issues may cease drinking, making non-drinking a potential marker of underlying illness. Unmeasured confounders related to both drinking status and stroke risk may also explain this association. Checking for collinearity among covariates is advisable to ensure model validity. Given these concerns, conclusions regarding alcohol use should be drawn cautiously.\n5. Baseline Characteristics and Cohort Effects: The authors should test and report differences in baseline characteristics across cohorts with corresponding p-values (in addition to descriptive statistics in Table 1). Adjusting cohort or study site in Cox models is essential to account for heterogeneity and reduce confounding (except for Table 5).\nClarity and Context:\nThe manuscript’s section order deviates from conventional scientific formats, with the results presented last, which may hinder readability. The rationale for selecting 80 years as the cutoff for stratified age analyses is not explained. Furthermore, reference #27 is cited incorrectly; the cited study uses age 60, not 80, as the relevant threshold for increased sensory impairments and stroke risk.\nReferences:\nThe manuscript appropriately cites relevant literature. However, the following reference lacks the year of publication and should be corrected:\nBeard JR, Officer AM, Cassels AK. The World Report on Aging and Health. Gerontologist 56, S163–S166.\nMy Expertise:\nNo aspects of the manuscript, data, or analyses fall outside my scope of expertise or were beyond my ability to assess."}, "author_response": "Responds to the reviewer’s comments (Reviewer 1):\nDear Reviewers:\nThank you for your comments concerning our manuscript entitled “Intrinsic capacity and stroke: a multiple cohort study\". Those comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance to our researches. We have studied comments carefully and have made correction which we hope meet with approval. The main corrections in the paper and the responds to the reviewer’s comments are as flowin g:\nCOMMENT:\nThis study, using data derived from four cohorts, investigated the association between intrinsic capacity (IC) and the risk of incident stroke. The IC concept provides a novel and positive approach to improving the care of community-dwelling older adults by addressing optimal functioning across its five domains. Although the operationalization of IC based on well-known indicators of physical and mental functioning is justified, the finding of this study did not provide a lot of new insights into this field. Also, there is a noticeable disconnect between the findings of this study and its integration into daily practice.\nRESPONSE:\nThank you for the reviewers' suggestions. As we mentioned in the background, many scholars believe that there is currently a lack of research on the association between intrinsic capacity and clinical outcomes, which also provided us with an opportunity to conduct this study. To our knowledge, this is the first large-scale cohort study to explore the association between intrinsic capacity and the incidence of stroke. One of its major strengths lies in the well-documented increasing trend of stroke incidence among older adults, particularly those aged 80 and above. These specific populations face high risks when it comes to clinical medical treatment. Reducing the incidence of stroke by early enhancement and improvement of intrinsic capacity is of great importance for alleviating clinical crises and developing community interventions. Therefore, this present study holds practical significance from both clinical and community intervention perspectives.\nRegarding daily practice, which is also a present research hotspot, the World Health Organization has already established the Integrated Care for Older People: Guidelines on Community-Level Interventions to Manage Declines in Intrinsic Capacity (Integrated care for older people: Guidelines on community-level interventions to manage declines in intrinsic capacity. Geneva: WHO; 2017 (http://apps.who.int/iris/handle/10665/258981)).\nIn accordance with the reviewers’ comments, we have strengthened this discussion in the revised manuscript.\n(See P 9, line 242-245)\nCOMMENT1:\nIn addition to the above comment, there are a few methodology concerns from me:\n1. It is unclear to me how authors synthesize scores from five domains. The synthetic algorithm is required in the manuscript.\nRESPONSE1:\nWe apologize for the lack of clarity in this description. Following the reviewer's suggestion, we have moved the explanation of how the intrinsic capacity total score is derived—by summing the five domain scores—from the Statistical Analysis section to the Intrinsic Capacity Measures section. We have provided a clearer description of this section. (See P9-10, Line 257-282)\nCOMMENT2:\n2. The author is expected to provide detailed measurement scales and measurement methods of five domains in the appendix.\nRESPONSE2:\nFollowing the reviewers' recommendations, we have added comprehensive details on the measurement scales and methods for all five domains to the appendix. (See Supplementary Table S1)\nCOMMENT3:\n3. The author is expected to include descriptions of the design of all four included cohorts both in the main manuscript in brief and in the appendix in detail.\nRESPONSE3:\nThank you for the reviewers’ suggestions. The detailed descriptions and cohort profiles of the four studies have been made publicly available. Following the reviewers’ comments, we have included the relevant references.\nCOMMENT4:\n4. The score of CI largely depends on individuals’ frailty status; thereafter, it is really hard to eliminate the possibility of reversing causation between CI and stroke. The author did not include any method that could potentially eliminate the issue of reverse causality.\nRESPONSE4:\nThank you for your suggestion. The cohort study design is a widely used research methodology in population studies for validating causal relationships, as it provides strong statistical power. In the present study, we employed a cohort design and excluded individuals with a prior diagnosis of stroke at baseline, thereby minimizing the risk of reverse causality. Moreover, we analyzed the association between changes in intrinsic capacity trajectories and the incidence of stroke, which further supports the causal relationship between intrinsic capacity levels and stroke occurrence.\nWith regard to intrinsic capacity and frailty, current research perspectives generally consider intrinsic capacity as an indicator of an individual’s functional reserve, whereas frailty represents a vulnerable clinical state associated with high risk. Intrinsic capacity is dynamic and highly modifiable, while frailty is less reversible. From a temporal perspective, intrinsic capacity serves as the precursor and foundation, whereas frailty typically manifests as its outcome and expression.\nCOMMENT5:\n5. The author compared the different risks among different quartiles, but did not report the baseline characteristics of different quartiles. The potential extreme imbalance among different quartiles cannot be fully eliminated by the adjustment of regression model.\nRESPONSE5:\nThank you for the reviewers' suggestions. As mentioned, it is challenging to eliminate all confounding factors through model adjustments. In such cases, a common strategy is to conduct stratified analyses. Age is often considered the most important confounding factor, and we performed stratified analyses for age, gender, study cohort, and each dimension of intrinsic capacity to better control important potential confounders. In accordance with the reviewers’ recommendation, we have added a table of baseline population characteristics based on intrinsic capacity quartiles as supplementary material. (See Supplementary Table S2)\nCOMMENT6:\n6. The author did not report how the different results from four cohorts have been synthesized. Also, the detailed results of each individual cohort need to be reported separately in the appendix.\nRESPONSE6:\nWe apologize for the lack of clarity in our previous description. Following the reviewer’s suggestions, we have revised this section to improve clarity. Table 2 presents the hazard ratios for the association between intrinsic capacity and incident stroke among participants from all four cohorts. In addition, Table 5 reports the association results between intrinsic capacity and stroke within each cohort. We have added further description to make this part of the results clearer. (See P3, Line 87-89; P4, Line 100-102)\nCOMMENT7:\n7. I failed to find any description on how missing values of covariates to be processed in the whole manuscript.\nRESPONSE7:\nThank you for the reviewer’s suggestion. We have indicated the missing covariates in Figure 1. In accordance with the reviewer’s suggestion, we have added a corresponding description into the text. (See P11, Line 308-310)\nCOMMENT8:\n8. In the flow-chart, the author said all individuals with missing data for IC measurement were excluded from this study. In this case, the author needs to compare the baseline characteristics of the entire cohort and eligible participants and provide comprehensive discussion on potential selection bias.\nRESPONSE8:\nBased on the reviewers’ suggestions, we have provided a detailed description of the baseline characteristics for both the entire cohort and the eligible participants in the supplementary table. Additionally, potential exclusion biases are discussed in the limitations section. (See Supplementary Table S3; P8, Line 222-234)\nWe tried our best to revise our manuscript and made some changes in the manuscript. We appreciate for your warm work earnestly, and hope that the correction will meet with approval.\nOnce again, thank you very much for your comments and suggestions.\nResponds to the reviewer’s comments (Reviewer 2):\nDear Reviewers:\nThank you for your comments concerning our manuscript entitled “Intrinsic capacity and stroke: a multiple cohort study\". Those comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance to our researches. We have studied comments carefully and have made correction which we hope meet with approval. The main corrections in the paper and the responds to the reviewer’s comments are as flowin g:\nCOMMENT1:\nOverall Assessment\nThis study provides robust evidence for a significant association between intrinsic capacity (IC) and incident stroke, particularly highlighting the importance of IC trajectories and age-specific effects. The findings are highly relevant to healthy aging and stroke prevention strategies. Although, Following Comments needs be addressed.\nMajor Comments:\n1. Methodology: Intrinsic Capacity Operationalization and Harmonization\nComment: The authors states that \"Intrinsic capacity was measured in accordance with the WHO guidelines\" (Page 8, Paragraph 2, Line 216). However, the operationalization of the 'Vitality' domain solely via BMI (Page 8, Paragraph 2, Line 227) warrants further justification or the exploration of alternative proxies. BMI, especially in older adults, may not fully capture sarcopenia or overall energy levels, which are critical aspects of vitality. Additionally, while the use of \"Asian-specific criteria\" for CHARLS participants is noted (Page 8, Paragraph 2, Line 229), the manuscript lacks sufficient detail on how the five IC domains were precisely standardized and harmonized across all four diverse cohorts (HRS, ELSA, SHARE, CHARLS), particularly for psychological capacity and cognition, where measurement tools might vary significantly.\nSuggestion:\nPage 8, Paragraph 2, Line 227 (Methods - Intrinsic Capacity Measures): Elaborate on the rationale for using BMI as the sole measure for vitality. If alternative proxies (e.g., grip strength, self-reported energy levels) were available in any cohort but not used, briefly explain why.\nPage 8, Paragraph 2, Lines 219-233 (Methods - Intrinsic Capacity Measures): Provide a supplementary table (e.g., Supplement Table S4) detailing the exact variables, specific questions, and scoring cutoffs used for each of the five intrinsic capacity domains within each of the four cohorts. This level of transparency is crucial for reproducibility and to assure readers of the comparability of IC measures across diverse populations.\nRESPONSE1:\nThank you for your suggestion. We have provided a detailed description of the intrinsic capacity to measure BMI. We also provide a supplementary table that details the exact variables used for the five domains of intrinsic capacity. (See P10, Line 273-282; Supplementary Table S1)\nCOMMENT2:\n2. Methodology: Stroke Ascertainment Details\nComment: The authors states that \"Stroke was diagnosed by physicians based on a clinical assessment\" (Page 9, Paragraph 2, Line 242). However, the absence of detailed stroke subtype classification (ischemic vs. hemorrhagic) and information on diagnostic validation procedures (e.g., neuroimaging confirmation rates) is a notable limitation.\nSuggestion:\nPage 9, Paragraph 2, Line 242 (Methods - Outcomes): Acknowledge the lack of detailed stroke subtype classification at this point in the methodology, rather than solely in the limitations section. For example, \"Stroke was diagnosed by physicians based on clinical assessment; however, detailed classification into ischemic or hemorrhagic subtypes was not consistently available across all cohorts, representing a limitation in our outcome ascertainment.\"\nPage 7, Paragraph 1, Lines 188-191 (Discussion - Limitations): Expand on how the lack of subtype classification might impact the interpretation of results, as risk factors and mechanisms can differ significantly between ischemic and hemorrhagic strokes.\nRESPONSE2_1:\nThank you for the reviewer’s suggestion. In response, we have added a more detailed statement to the revised manuscript. (See P11, Line 299-301)\nRESPONSE2_2:\nBased on the reviewer's suggestions, we have provided a detailed description for the suggestion (Page 7, Paragraph 1, Lines 188-191). (See P8, Line 218-220)\nCOMMENT3:\n3. Statistical Analysis: Missing Data Handling\nComment: While the authors mentions exclusions (Page 9, Paragraph 2, Line 240, and Figure 1 on Page 20), a clear and prominent description of how missing data for covariates or intrinsic capacity domains were handled is essential for methodological transparency. The current manuscript does not explicitly state the missing data handling strategy in the \"Statistical analysis\" section (Page 9, Paragraph 3, Lines 244-269).\nSuggestion:\nPage 9, Paragraph 3, Lines 244-269 (Methods - Statistical Analysis): Explicitly state the method used for handling missing data (e.g., \"Missing covariate data were handled using multiple imputation by chained equations (MICE) to minimize potential bias from complete-case analysis.\"). Clarify if participants with any missing IC domains were excluded or imputed.\nRESPONSE3:\nWe appreciate the reviewer’s insightful comment regarding the handling of missing data. In this study, we applied the listwise deletion method. Sensitivity analyses suggested that the data were likely missing not at random (MNAR), as older participants (particularly those aged 80 and above) had the highest proportion of missing values. As we know, older participants tended to have poorer intrinsic capacity, suggesting a systematic pattern of missingness. Under such circumstances, multiple imputation based on the missing-at-random assumption may introduce additional bias. In the absence of strong prior knowledge to explicitly model MNAR mechanisms, we considered complete case analysis to be a more transparent and conventional approach. To mitigate potential biases, we conducted stratified analyses. We have provided a more detailed description in the methods section and explicitly discussed this limitation in the manuscript. (See P11, Line 308-310; P8, Line 222-234)\nCOMMENT4:\n4. Discussion:\nComment: The interpretation of mechanisms, particularly for psychological and sensory capacities influencing stroke, currently leans towards surface-level biological explanations. Additionally, the comparison with prior work is limited to only one other study mentioned in the discussion (Page 7, Paragraph 1, Line 185).\nSuggestion:\nPage 6, Paragraph 4, Lines 176-178 (Discussion - Psychological Capacity): Expand on how psychological and sensory capacities might influence stroke through indirect pathways such as social isolation, depression (beyond direct biological links), reduced adherence to medical advice, or increased frailty.\nPage 7, Paragraph 1, Lines 185-186 (Discussion): Include a broader range of relevant literature, especially from fields like GeroScience, public health journals, or those exploring aging biomarkers, to provide a more comprehensive context for your findings and highlight where your study aligns with or diverges from existing evidence.\nRESPONSE4_1:\nFollowing the reviewers’ suggestions, we have incorporated the corresponding descriptions into the revised manuscript. (See P6, Line 173-177)\nRESPONSE4_2:\nThank you for the reviewer’s suggestion, we have now addressed it by providing a detailed description in the manuscript. (See P7-8, Line 205-213)\nCOMMENT5:\n5. Methodology / Discussion: Potential Residual Confounders\nComment: The manuscript provides a comprehensive list of adjusted covariates (Page 9, Paragraph 3, Lines 255-257). However, certain factors such as medication use (beyond hypertension/diabetes medications), specific dietary patterns, detailed social support networks, and measures of cognitive reserve were not included as covariates. These factors could potentially confound the observed associations.\nSuggestion:\nPage 9, Paragraph 3, Lines 255-257 (Methods - Covariates): Acknowledge that while extensive adjustments were made, certain potential confounders (e.g., specific medication classes, detailed dietary habits, nuanced social network characteristics, or direct measures of cognitive reserve) were not available or included in the analysis.\nRESPONSE5_1: Page 7, Paragraph 1, Lines 188-191 (Discussion - Limitations): Explicitly list these potential residual confounders in the limitations section and briefly discuss how their absence might influence the results.\nBased on the reviewer's suggestions, we have added a detailed description of these variables in the Methods section under the \"Covariates\" subsection. (See P10, Line 293-294)\nRESPONSE5_2:\nWe thank the reviewer for this suggestion. We have incorporated a detailed description on this point in the limitations section. (See P8, Line 227-230)\nCOMMENT6:\n6. Statistical Analysis: Directed Acyclic Graph (DAG)\n• Comment: A Directed Acyclic Graph (DAG) could be a valuable addition to visually represent the assumed causal relationships between intrinsic capacity, stroke, and the covariates, helping to identify potential confounders, mediators, or colliders.\n• Suggestion:\nPage 9, Paragraph 3, Lines 244-269 (Methods - Statistical Analysis): Consider including a brief statement about causal assumptions and referring to a DAG in a supplementary figure.\nSupplementary Material: Provide a DAG that illustrates your assumed causal structure. This is not strictly necessary for publication but is increasingly common in epidemiological studies to enhance transparency regarding causal assumptions and adjustment strategies.\nRESPONSE6:\nIn response to the reviewer’s suggestion, we have specified in the Methods section the use of directed acyclic graph (DAG) to assess the causal relationship between intrinsic capacity and stroke, and provided a supplementary figure accordingly. (See P12, Line 333-335; Supplement Figure S4)\nMINOR COMMENT1:\nMinor Comments\n1. Abstract and Results: Incidence Rate vs. Proportion\nComment: In the abstract, the statement \"The incidence rate was 48.4% in males and 51.6% in females\" (Page 1, Paragraph 1, Line 14) is imprecise. This refers to the proportion of incident strokes occurring in each sex, not an incidence rate (which is typically expressed per person-years or per 1,000 population).\nSuggestion:\nPage 1, Paragraph 1, Line 14 (Abstract): Revise to \"The proportion of incident strokes was 48.4% in males and 51.6% in females.\"\nPage 3, Paragraph 1, Line 73 (Results - First Paragraph): Apply the same correction.\nRESPONSE1: We apologize for this oversight and have corrected the manuscript accordingly.\nMINOR COMMENT2:\n2. Introduction: Framing and Novelty Statement\nComment: The introduction could more explicitly and earlier frame the study within global healthy aging frameworks and highlight its novelty.\nSuggestion:\nPage 2, Paragraph 3, Lines 53-56 (Introduction): Reference global frameworks like WHO’s “Decade of Healthy Ageing” earlier to frame the study’s relevance.\nPage 3, Paragraph 1, Lines 65-67 (Introduction): Include a short, explicit statement on the novelty of linking IC trajectories to stroke, as this is a key strength that is currently \"buried\" in the discussion.\nRESPONSE2_1: We have incorporated the corresponding descriptions as suggested by the reviewer. We have enhanced the clarity of this section by providing a more detailed description. (See P2, Line 55-58)\nRESPONSE2_2: We are grateful for the reviewer’s insightful comments. We have accordingly incorporated the relevant description into the revised version of the manuscript. (See P3, Line 69-72)\nMINOR COMMENT3:\n3. Terminology: Functional Decline vs. Intrinsic Capacity\nComment: For readers unfamiliar with WHO terminology, better distinction between \"functional decline\" and \"intrinsic capacity\" would be beneficial.\nSuggestion:\nPage 2, Paragraph 3, Lines 53-61 (Introduction): Briefly clarify the distinction, e.g., \"While often related, intrinsic capacity, as defined by WHO, differs from functional decline by focusing on the individual's inherent physical and mental capacities rather than solely their ability to perform daily activities.\"\nRESPONSE3: We thank the reviewer for the suggestion and have added a corresponding description in the manuscript. (See P2, Line 55-58)\nMINOR COMMENT4:\n4. Methodology: \"Dummy Variables\" for Intrinsic Capacity Quartiles\nComment: The manuscript mentions using \"three dummy variables representing different levels of exposure\" for intrinsic capacity quartiles (Page 1, Paragraph 1, Line 10 and Page 9, Paragraph 3, Line 253). While clear from the results, explicitly stating the reference group in the methods improves clarity.\nSuggestion:\nPage 9, Paragraph 3, Line 253 (Methods - Statistical Analysis): Clarify which quartile served as the reference group (e.g., \").\nRESPONSE4:\nFollowing the reviewers’ suggestions, we have clarified the reference group for the quartile analyses. (See P11, Line 313-314)\nMINOR COMMENT5:\n5. Results: Table 3 Clarification\nComment: The text states that \"The sex-specific results are summarized in Table 3\" (Page 3, Paragraph 3, Line 86). However, Table 3 (\"Hazard ratios for stroke incidence in relation to intrinsic capacity and associated risk factors by sex\") primarily shows HRs for intrinsic capacity and other covariates stratified by sex. The subsequent sentence in the text, \"Participants who developed incident stroke were more likely to be male, older, unmarried, low-income, current smokers, non-drinkers, physically inactive, and to report poor self-rated health, hypertension or diabetes\" (Page 3, Paragraph 3, Lines 86-88), describes descriptive baseline characteristics of stroke cases, which are typically found in Table 1 or a descriptive table of stroke vs. non-stroke groups. This creates a slight disconnect.\nSuggestion:\nPage 3, Paragraph 3, Lines 86-88 (Results): Rephrase the text to clearly indicate that Table 3 provides the sex-stratified hazard ratios for intrinsic capacity and other covariates. If the descriptive characteristics of stroke cases are important to highlight here, consider creating a separate supplementary table for these descriptive comparisons or ensure the text explicitly states these are descriptive findings, not HRs from Table 3.\nRESPONSE5:\nWe apologize for the lack of clarity in the previous description. We have revised the order of the descriptions to ensure consistency with the table. (See P3, Line 87-89)\nMINOR COMMENT6:\n6. Discussion: IC as a Modifiable Risk Factor\nComment: The discussion could be more proactive in suggesting specific interventions for IC.\nSuggestion:\nPage 7, Paragraph 1, Lines 202-204 (Discussion - Future Research): While you call for future research, briefly suggest specific types of interventions (e.g., targeted exercise programs, cognitive training, nutritional interventions, social engagement programs) and how IC could potentially be tracked in clinical practice or public health initiatives.\nRESPONSE6:\nThank you for the reviewer’s suggestion. We have revised this section accordingly. (See P9, Line 242-245)\nMINOR COMMENT7:\n7. Discussion: Limitations - Single Time Point IC Assessment\nComment: The limitations section should explicitly mention the limitation of using a single time point IC assessment for the majority of the analysis (except for those included in the trajectory models).\nSuggestion:\nPage 7, Paragraph 1, Lines 187-188 (Discussion - Limitations): Add a point stating, \"While our trajectory analysis provides dynamic insights, the primary analysis relies on baseline intrinsic capacity assessment, which may not fully capture changes in IC over the entire follow-up period for all participants.\"\nRESPONSE7:\nAccording to the reviewer’s suggestion, we have added the corresponding description. (See P8, Line 230-232)\nMINOR COMMENT8:\n8. Statistical Analysis: Sensitivity Analyses Description\nComment: While the manuscript performs excellent sensitivity analyses (Pages 9-10, Paragraph 3, Lines 260-269), the description could more explicitly state if \"effect modification\" by cohort, age, or baseline IC was formally tested using interaction terms, beyond simply presenting stratified results.\nSuggestion:\nPage 9, Paragraph 3, Lines 260-269 (Methods - Statistical Analysis): For each sensitivity analysis (e.g., by cohort, by age group), clarify if formal tests for interaction (effect modification) were conducted, and if so, briefly state the results (e.g., \"Formal interaction tests were performed to assess for effect modification by age, and a significant interaction was observed (P-value for interaction < 0.001), indicating that the association between IC and stroke indeed differed by age group.\").\nRESPONSE8:\nIn response to the reviewers’ suggestions, we have provided a more detailed description of the interaction test. (See P11, Line 322-324).\nWe tried our best to revise our manuscript and made some changes in the manuscript. We appreciate for your warm work earnestly, and hope that the correction will meet with approval.\nOnce again, thank you very much for your comments and suggestions.\nResponds to the reviewer’s comments (Reviewer 3):\nDear Reviewers:\nThank you for your comments concerning our manuscript entitled “Intrinsic capacity and stroke: a multiple cohort study\". Those comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance to our researches. We have studied comments carefully and have made correction which we hope meet with approval. The main corrections in the paper and the responds to the reviewer’s comments are as flow ing:\nGeneral Comments\nThis study examines the association between intrinsic capacity and incident stroke using pooled date from four large-scale longitudinal cohorts. The question is clearly relevant given population ageing.\nKey strengths;\n- Large, multinational cohorts - very large sample size\n- Consistent results across cohorts and subanalyses\n- Strong statistical signal with dose-response relationship\n- Figures and tables clear\nCOMMENT1:\n1. Given prior work on frailty and multi morbidity, the finding that global functional status predicts stroke risk is not surprising or entirely novel. The authors should explicitly discuss what additional predictive value IC adds beyond existing constructs such as frailty, multi morbidity etc.\nRESPONSE1:\nThank you for the reviewer’s suggestion. We have added the corresponding description to the Introduction and Discussion sections. (See P3, Line 69-72; P7-8, Line 205-213)\nIn addition, the World Health Organization has developed intrinsic capacity measurement tools, with the main aim of advancing person-centred assessment in community primary healthcare. Against the backdrop of global population ageing, the growing burden of stroke among older adults poses substantial challenges for clinical treatment and care and underscores the need for further research. Our study aims to contribute to this effort by offering readers a new perspective.\nCOMMENT2:\n2. At least one study has already reported associations of IC with CVD outcomes, specifically including stroke (PMID: 37434422). This hasn't been cited. Please discuss what the incremental contribution of this study is and reference this paper.\nRESPONSE2:\nThank you for the reviewer’s suggestion. We have incorporated this description into the Discussion section. (See P7, Line 196-202)\nCOMMENT3:\n3. Please explain why IC ws measured differently in the CHARLS cohort with Asian-specific BMI cutoffs\nRESPONSE3:\nBody-mass index (BMI) is generally lower in Chinese and other Asian populations than in European or US populations, yet the risk of adverse health outcomes at a given BMI is higher. On this basis, the World Health Organization has proposed lower BMI cutoff points for defining overweight and obesity in Asian populations.\nCOMMENT4:\n4. Why use quartiles modelling instead of continuous modelling?\nRESPONSE4:\nIn epidemiological studies, generating dummy variables from continuous measures is a widely used approach to assess disease risk. Transforming continuous variables into quartiles enables clearer assessment of dose–response relations, revealing the progressive increase in disease risk with greater exposure to risk factors.\nCOMMENT5:\n5. The hazard ratios are very large for an observational association. Consider whether there could be an element of reverse causality here (subclinical cerebrovascular or small vessel disease may lower IC domains such as cognition and locomotor) before an overt stroke. Also avoid causal phrasing of intrinsic capacity as a TARGET for prevention rather than a MARKER for stroke risk.\nRESPONSE5:\nThank you for the reviewer’s suggestion. As suggested by the reviewers, the research results on the causal relationship between cognitive impairment and stroke are diverse, and some studies have proposed potential pathological mechanisms linking the two. Using a large cohort design, we were able to validate this association. Cohort studies remain a classic method for assessing causality in population research. Cognitive impairment typically develops gradually, whereas preclinical stroke may manifest as cognitive decline or progress to clinical stroke within a short timeframe. The Cox model, which assumes a constant hazard over time, is well suited to this setting. Nevertheless, as highlighted by reviewers, some preclinical stroke cases may first present with cognitive impairment that eventually leads to stroke. Although we excluded patients with stroke at baseline, prior undiagnosed or subclinical events could not be ruled out. In line with reviewer feedback, this limitation has been explicitly acknowledged in the revised manuscript.\nWe tried our best to revise our manuscript and made some changes in the manuscript. We appreciate for your warm work earnestly, and hope that the correction will meet with approval.\nOnce again, thank you very much for your comments and suggestions."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The author has addressed the vast majority of my comments. Well done. I just want to raise a minor correction.\nIn the abstract and results section, the author said 'During the follow-up period, 15,125 individuals experienced stroke events. The proportion of incident strokes was 48.4% in men and 51.6% in women.' The author might want to revise this sentence like this: 'During the follow-up period, 15,125 individuals experienced stroke events (male: 48.4%; female: 51.6%)' to avoid potential misunderstanding.", "reviewer_3": "Thank you for your revisions\nRESPONSE1: The authors now acknowledge overlap between intrinsic capacity, frailty, and multimorbidity. However, they still do not cite any empirical evidence to demonstrate incremental predictive value of intrinsic capacity over these other constructs. The fact that they correlate is in alignment with this problem and does not prove its usefulness\nRESPONSE2/3: Appropriately addressed\nRESPONSE4: The rationale for quartile modelling is reasonable, though it would be reassuring to note whether similar associations were observed using continuous IC scores. Perhaps as a sensitivity analysis/in supplementaries\nRESPONSE5: Still significant causal language used in the Discussion. This should be revised", "reviewer_4": "Response Summary\nWhile all other reviewer comments have been thoroughly addressed, Figure 2 and its accompanying description require major revision. The figure must be redesigned with clear labeling, a descriptive legend, logical visual hierarchy, and consistent alignment between the text and quantitative data to meet the clarity and rigor standards expected for publication in Nature Communications\nOutstanding Issues – Figure 2\nA. Problems with Figure 2 Description\nThe provided description remains confusing and requires editing for clarity and consistency. The current text reads:\n“Figure 2 illustrates the association between changes in intrinsic capacity levels and the risk of stroke. Compared with participants who maintained moderate intrinsic capacity at baseline, midpoint, and endpoint, those with persistently low levels exhibited a higher risk of stroke (P < 0.001), whereas those with consistently high intrinsic capacity had a significantly lower risk (P < 0.001). Notably, participants whose intrinsic capacity declined from a moderate level at baseline to a lower level at the midpoint had a significantly higher risk of stroke, with HRs of 1.57 (95% CI: 1.44–1.72).”\nThe description should be revised for the following reasons:\n1. Missing reference group:\nThe sentence “Participants whose intrinsic capacity declined from a moderate level at baseline to a lower level at the midpoint had a significantly higher risk of stroke, with HRs of 1.57 (95% CI: 1.44–1.72)” does not specify its comparator group. It must explicitly state:\n“compared with those who maintained moderate intrinsic capacity throughout.”\n2. Inconsistent reporting of P values:\nReporting of P < 0.001 is inconsistent with the rest of the manuscript and the figure. These should be replaced by corresponding point estimates with 95% confidence intervals (CIs).\n3. Directional ambiguity:\nThe paragraph mixes qualitative phrases (e.g., “higher risk,” “lower risk”) with quantitative HRs without consistently clarifying the direction of effect relative to 1.0.\n4. A clearer, more logical sequence would present results by category — stable, declining, then improving trajectories — each compared to its appropriate reference group.\n________________________________________\nB. Problems with Figure 2 Design\nThe figure itself has several major scientific and visual deficiencies that must be corrected:\n1. Ambiguous symbols:\nThe human icons and arrows are not labeled or defined, leaving unclear whether they indicate “stable,” “declining,” or “improving” in intrinsic capacity.\n2. Lack of explanatory legend:\nThe figure does not include a proper legend or caption explaining what each trajectory represents, what Baseline → Endpoint means quantitatively, or how intrinsic capacity was measured.\n3. Unclear mapping between text and data:\nThe hazard ratios displayed on the right are not directly connected to the trajectory diagrams on the left. There are no labels (e.g., “Trajectory A,” “B,” “C”) linking HR values to their corresponding groups.\n4. Unclear visual hierarchy:\nThe central brain and sensory icons appear visually dominant but conceptually disconnected from the trajectories. Their relevance—whether to intrinsic capacity subdomains or to stroke mechanisms—remains undefined.\n________________________________________\nHere are suggested legends for figure: Figure 2. Hazard ratios (HRs) and 95% confidence intervals (CIs) for stroke risk according to longitudinal patterns of intrinsic capacity from baseline to endpoint.\nParticipants who maintained moderate intrinsic capacity across all time points served as the reference group. Compared with this reference, participants with persistently low intrinsic capacity had a higher risk of stroke (HR = 2.11; 95% CI 1.95–2.29), whereas those with consistently high intrinsic capacity had a lower risk (HR = 0.71; 95% CI 0.62–0.81). Participants whose intrinsic capacity declined from moderate to low also showed an increased risk of stroke (HR = 1.57; 95% CI 1.44–1.72).\nConversely, individuals with low intrinsic capacity at baseline who improved by the endpoint had a reduced risk relative to those who remained persistently low (HR = 0.36; 95% CI 0.25–0.53). Participants with high baseline intrinsic capacity who declined over time exhibited a higher risk compared with those who maintained high capacity (HR = 1.65; 95% CI 1.31–2.08).\nTrajectories are organized in a consistent order: stable, declining, and improving groups. Each trajectory is clearly labeled, and HRs correspond directly to the defined categories. The legend clarifies that “Baseline → Endpoint” reflects change in overall intrinsic capacity score over the follow-up period."}, "author_response": "Responds to the reviewer’s comments (Reviewer 1):\nDear Reviewers:\nThank you for your comments concerning our manuscript entitled “Intrinsic capacity and stroke: a multiple cohort study\". We have made correction which we hope meet with approval. The main corrections in the paper and the responds to the reviewer’s comments are as flowing:\nCOMMENT:\nThe author has addressed the vast majority of my comments. Well done. I just want to raise a minor correction.\nIn the abstract and results section, the author said 'During the follow-up period, 15,125 individuals experienced stroke events. The proportion of incident strokes was 48.4% in men and 51.6% in women.' The author might want to revise this sentence like this: 'During the follow-up period, 15,125 individuals experienced stroke events (male: 48.4%; female: 51.6%)' to avoid potential misunderstanding.\nRESPONSE: In accordance with the reviewers’ comments, we have made correction in the revised manuscript.\n(See P 1, line 14)\nOnce again, we would like to express our sincere gratitude to the reviewer for the valuable and kind suggestions.\nResponds to the reviewer’s comments (Reviewer 3):\nDear Reviewers:\nThank you for your comments concerning our manuscript entitled “Intrinsic capacity and stroke: a multiple cohort study\". Those comments are all valuable and very helpful for revising and improving our paper. We have made corrections based on the suggestions of the reviewers which we hope meet with approval. The main corrections in the paper and the responds to the reviewer’s comments are as flowing:\nCOMMENT1: The authors now acknowledge overlap between intrinsic capacity, frailty, and multimorbidity.\nHowever, they still do not cite any empirical evidence to demonstrate incremental predictive value of intrinsic\ncapacity over these other constructs. The fact that they correlate is in alignment with this problem and does not\nprove its usefulness.\nRESPONSE: We apologize for the lack of clarity in the previous revision. Based on the reviewers' suggestions, we\nhave enhanced our description by integrating empirical research evidence, thereby more effectively demonstrating\nthe incremental predictive value of intrinsic capacity. (See P8, Line 214-223)\nCOMMENT2/3: Appropriately addressed\nRESPONSE: Wethankthereviewerforthiscomment.\nCOMMENT4: The rationale for quartile modelling is reasonable, though it would be reassuring to note whether\nsimilar associations were observed using continuous IC scores. Perhaps as a sensitivity analysis/in supplementaries\nRESPONSE: Thank you for the reviewer’s suggestion. We have added continuous IC scores to the model, and the\nresults are presented in Supplementary Table 2.\nCOMMENT5: Still significant causal language used in the Discussion. This should be revised\nRESPONSE: In accordance with the reviewers’ suggestions, we have made the corresponding revisions.\nOnce again, thank you very much for your comments and suggestions.\nResponds to the reviewer’s comments (Reviewer 4):\nDear Reviewers:\nThank you for your comments concerning our manuscript entitled “Intrinsic capacity and stroke: a multiple\ncohort study\". Those comments are all valuable and very helpful for revising and improving our paper. We have\nmade corrections based on the suggestions of the reviewers which we hope meet with approval. The main\ncorrections in the paper and the responds to the reviewer’s comments are as flowing:\nCOMMENT Summary:\nWhile all other reviewer comments have been thoroughly addressed, Figure 2 and its accompanying description\nrequire major revision. The figure must be redesigned with clear labeling, a descriptive legend, logical visual\nhierarchy, and consistent alignment between the text and quantitative data to meet the clarity and rigor standards\nexpected for publication in Nature Communications\nOutstanding Issues – Figure 2\nRESPONSE: We are grateful for the reviewer’s constructive suggestions. Guided by these comments, we have\nmade comprehensive revisions to ensure the manuscript adheres to the high publishing standards required by\nNature Communications.\nCOMMENT:\nA. Problems with Figure 2 Description\nThe provided description remains confusing and requires editing for clarity and consistency. The current text reads:\n“Figure 2 illustrates the association between changes in intrinsic capacity levels and the risk of stroke. Compared\nwith participants who maintained moderate intrinsic capacity at baseline, midpoint, and endpoint, those with\npersistently low levels exhibited a higher risk of stroke (P < 0.001), whereas those with consistently high intrinsic\ncapacity had a significantly lower risk (P < 0.001). Notably, participants whose intrinsic capacity declined from a\nmoderate level at baseline to a lower level at the midpoint had a significantly higher risk of stroke, with HRs of\n1.57 (95% CI: 1.44–1.72).”\nThe description should be revised for the following reasons:\n1. Missing reference group:\nThe sentence “Participants whose intrinsic capacity declined from a moderate level at baseline to a lower level at\nthe midpoint had a significantly higher risk of stroke, with HRs of 1.57 (95% CI: 1.44–1.72)” does not specify its\ncomparator group. It must explicitly state:\n“compared with those who maintained moderate intrinsic capacity throughout.”\nRESPONSE: We appreciate the reviewer’s suggestions. In response, we have made the corresponding revisions.\n(See P4, Line 110-112)\nCOMMENT:\n2. Inconsistent reporting of P values:\nReporting of P < 0.001 is inconsistent with the rest of the manuscript and the figure. These should be replaced by\ncorresponding point estimates with 95% confidence intervals (CIs).\nRESPONSE: Based on the reviewers’ suggestions, we have made the corresponding revisions. (See P4, Line 109-\n110)\nCOMMENT:\n3. Directional ambiguity:\nThe paragraph mixes qualitative phrases (e.g., “higher risk,” “lower risk”) with quantitative HRs without\nconsistently clarifying the direction of effect relative to 1.0.\nRESPONSE: We appreciate the reviewer’s suggestion and have accordingly rewritten this paragraph to improve\nclarity and alignment with the study findings. (See P4, Line 107-110)\nCOMMENT:\n4. A clearer, more logical sequence would present results by category — stable, declining, then improving\ntrajectories — each compared to its appropriate reference group.\nRESPONSE: We apologize for the unclear description in the original manuscript. The complexity arose because\nchanges in the reference group, as well as changes in intrinsic capacity at both the intermediate and endpoint\nobservations, were considered in the analysis. Based on the reviewer’s suggestions, we have redrawn the figures to\nalign with the results section and have clarified the logical sequence in the description.\n________________________________________\nCOMMENT:\nB. Problems with Figure 2 Design\nThe figure itself has several major scientific and visual deficiencies that must be corrected:\n1. Ambiguous symbols:\nThe human icons and arrows are not labeled or defined, leaving unclear whether they indicate “stable,” “declining,”\nor “improving” in intrinsic capacity.\nRESPONSE: We appreciate the reviewer’s suggestion and have accordingly added labels to the human icon.\nCOMMENT:\n2. Lack of explanatory legend:\nThe figure does not include a proper legend or caption explaining what each trajectory represents, what Baseline →\nEndpoint means quantitatively, or how intrinsic capacity was measured.\nRESPONSE: We appreciate the reviewer’s suggestions and have accordingly made the relevant supplements and\nmodifications.\nCOMMENT:\n3. Unclear mapping between text and data:\nThe hazard ratios displayed on the right are not directly connected to the trajectory diagrams on the left. There are\nno labels (e.g., “Trajectory A,” “B,” “C”) linking HR values to their corresponding groups.\nRESPONSE: Thank you for the reviewer’s suggestions. We have revised the manuscript accordingly.\nCOMMENT:\n4. Unclear visual hierarchy:\nThe central brain and sensory icons appear visually dominant but conceptually disconnected from the trajectories.\nTheir relevance—whether to intrinsic capacity subdomains or to stroke mechanisms—remains undefined.\nRESPONSE: We appreciate the reviewer’s suggestions and have revised the figure to improve clarity. (See Figure\n2 new)\n________________________________________\nCOMMENT:\nHere are suggested legends for figure: Figure 2. Hazard ratios (HRs) and 95% confidence intervals (CIs) for stroke\nrisk according to longitudinal patterns of intrinsic capacity from baseline to endpoint.\nParticipants who maintained moderate intrinsic capacity across all time points served as the reference group.\nCompared with this reference, participants with persistently low intrinsic capacity had a higher risk of stroke (HR =\n2.11; 95% CI 1.95–2.29), whereas those with consistently high intrinsic capacity had a lower risk (HR = 0.71; 95%\nCI 0.62–0.81). Participants whose intrinsic capacity declined from moderate to low also showed an increased risk\nof stroke (HR = 1.57; 95% CI 1.44–1.72).\nConversely, individuals with low intrinsic capacity at baseline who improved by the endpoint had a reduced risk\nrelative to those who remained persistently low (HR = 0.36; 95% CI 0.25–0.53). Participants with high baseline\nintrinsic capacity who declined over time exhibited a higher risk compared with those who maintained high\ncapacity (HR = 1.65; 95% CI 1.31–2.08).\nTrajectories are organized in a consistent order: stable, declining, and improving groups. Each trajectory is clearly\nlabeled, and HRs correspond directly to the defined categories. The legend clarifies that “Baseline → Endpoint”\nreflects change in overall intrinsic capacity score over the follow-up period.\nRESPONSE: Thank you for the reviewer’s suggestions. We have made the corresponding modifications.\nWe have carefully revised the manuscript and implemented the key changes. We sincerely appreciate your\nthorough review and constructive comments, and we hope that the revisions meet with your approval.\nOnce again, thank you very much for your valuable suggestions."}, {"round": 3, "reviewer_comments": {"reviewer_3": "My comments have been adequately addressed. Well done\n(Remarks on code availability)\nNA", "reviewer_4": "I do not have any additional comments.\n(Remarks on code availability)\nI was able to review the provided code and found it to be generally well organized and readable. The structure and logic of the implementation are clear, and I was able to follow how the analyses described in the paper are intended to be performed. The repository includes sufficient documentation to understand the workflow and the intended use of the code."}, "author_response": ""}]

Decision letter