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Intrinsic capacity decline and its associations in community-dwelling older adults in Kedah, Malaysia
*Corresponding author: Maria Justine, Department of Physiotherapy, Faculty of Health Sciences, Universiti Teknologi MARA, Selangor, Malaysia. maria205@uitm.edu.my
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Received: ,
Accepted: ,
How to cite this article: Noordin N, Wah YC, Justine M. Intrinsic capacity decline and its determinants among community-dwelling older adults in Kedah, Malaysia. Int J Health Sci (Qassim). 2026;20:74-84. doi: 10.25259/IJHS_276_2025
Abstract
Objectives:
Intrinsic capacity (IC) is the composite of physical and mental capacities, reflecting the overall functional ability in older adults. Evidence on IC decline in Malaysia remains limited; therefore, this study examined the prevalence of decline across six IC domains and identified key sociodemographic and clinical associations.
Methods:
This cross-sectional study recruited 329 older adults from three Pusat Aktiviti Warga Emas centers in Kedah, Malaysia. Their IC was assessed using the World Health Organization-Integrated Care for Older People Step 1 screening tool across six domains (Mini-Mental State Examination, Short Physical Performance Battery, Mini Nutritional Assessment–Short Form, Geriatric Depression Scale–15, visual acuity self-report, and whisper test self-report). Data were analyzed using multivariable logistic regression adjusted for weight, body mass index, and gender, and expressed as adjusted odds ratios (aOR) with 95% confidence intervals (CI).
Results:
IC decline was most common in vision (69.6%) and cognition (52.6%), followed by locomotion (40.1%), vitality (30.4%), hearing (23.1%), and psychological function (17.9%). Overall, 77.2% had impairment in at least one domain. Significant associations were observed between walking-aid use and decline in locomotion (aOR = 7.75), vitality (aOR = 1.99), and hearing (aOR = 3.55). Non-Malay ethnicity was associated with higher odds of psychological decline (aOR = 4.09) but lower odds of vitality decline (aOR = 0.28). Multimorbidity was associated with increased odds of vitality and psychological decline, while higher education was associated with lower odds of cognitive impairment (aOR = 0.35).
Conclusion:
IC decline was highly prevalent, particularly in vision and cognition. These findings suggest the need for early, community-based, multidisciplinary strategies to preserve function and promote healthy aging.
Keywords
Community-dwelling older adults
Healthy aging
Intrinsic capacity
Malaysia
INTRODUCTION
The World Health Organization (WHO) conceptualizes intrinsic capacity (IC) as the composite of physical and mental capacities that an individual can draw on to maintain functional ability and healthy aging.[1] In the WHO healthy aging framework, IC refers to an individual’s composite of physical and mental capacities, while functional ability reflects the interaction between IC and environmental factors, and disability represents a downstream outcome when functional limitations are not adequately compensated. Accordingly, indicators such as walking-aid use, hearing-aid use, and pacemaker implantation are better interpreted as markers of existing functional limitation or healthcare utilization, rather than direct associations with IC decline. IC spans cognitive, locomotor, psychological, vitality, and sensory domains, highlighting the physiological and psychological reserves that sustain independence. Declines in these domains predispose older adults to frailty, disability, and dependency.[2-4] The WHO Integrated Care for Older People (WHO-ICOPE) framework recommends screening six IC domains: Cognitive, locomotor, vitality, vision, hearing, and psychological to identify older adults at risk and to guide suitable targeted interventions for them.[4]
Studying IC is essential because it provides a function-centered, preventive lens on aging, enabling detection of early multidomain decline before disability develops. Unlike disease-based measures, IC integrates physical and mental reserves, supporting population surveillance, risk stratification, and timely intervention. This approach underpins the WHO-ICOPE framework by guiding person-centered, multidomain strategies to preserve independence and quality of life in older adults.
Globally, IC decline is increasingly recognized as a major public health issue, although prevalence estimates vary substantially across countries and study designs, ranging between 19% and 89%.[5-7] A multi-country study spanning eight nations demonstrated that IC decline is strongly associated with both dependence and mortality.[8] In a large community-based survey in China, 39.9% of older adults were found to have experienced IC decline, with locomotor and cognitive deficits being the most prominent.[9] Lower education, being unmarried, and low income were identified as significant correlates.[10] Other research emphasizes the role of sensory and psychological decline as important factors associated with falls and disability, while stepwise models consistently identify cognitive, psychological, and locomotor impairments as primary contributors to functional deterioration.[11] In addition, other studies also reported risk factors of IC decline include advancing age, female gender, multimorbidity, and lower educational attainment.[6,8]
IC decline shows substantial regional variation, reflecting differences in demographic aging, socioeconomic context, and healthcare access. Evidence from East Asia highlights prominent cognitive and locomotor impairments, whereas European studies more frequently report locomotor and vitality decline associated with frailty and healthcare utilization. Importantly, IC research from these regions has directly informed preventive strategies, including multicomponent exercise programs, nutritional optimization, sensory screening, and cognitive training to slow functional decline.[3,8] Longitudinal findings further support early, community-based interventions implemented before disability onset. Together, these insights support the WHOICOPE framework, demonstrating how IC surveillance translates into scalable, person-centered preventive care pathways tailored to population needs.[4]
In Malaysia, population aging is accelerating, with older adults expected to account for 15% of the population by 2030.[12] The northern region shows particularly rapid demographic shifts; for instance, Kedah recorded 13.3% of its population as older adults in 2024, reflecting its status as one of the country’s most aged states.[13] Recent Malaysian evidence showed that 93.8% of older adults had impairment in at least one IC domain.[14] There is a lack of evidence from the northern region of Malaysia, particularly in Kedah, considering its escalating aging population. This limitation may hinder the ability to design targeted ICOPE-based interventions for the community-dwellers. The identification of some modifiable factors, such as the anthropometrics and clinical measures, remains limited. For instance, obesity that can be identified through the measurement of anthropometry is common among Malaysian older adults and is known to contribute to sarcopenia, metabolic disease, and mobility impairment.[15] In addition, falls, which represent another major geriatric syndrome, function both as a consequence of IC decline and as a risk factor that further accelerates deterioration.
Kedah, with one of the highest proportions of older adults in Malaysia, still lacks population-based data on IC decline. To address this gap, the present study builds on a multicenter community survey in Kedah. Specifically, it aims to estimate the prevalence of decline across six IC domains among community-dwelling older adults and to explore factors, such as sociodemographic, anthropometric, and clinical variables, that may contribute to multidomain IC decline. We hypothesized that the use of walking aids, sensory impairments, and a history of falls would be associated with higher odds of IC decline, whereas younger age, gender, and education level may be associated with lower odds of IC decline in specific domains.
MATERIALS & METHODS
Study design and participants
We conducted a community-based cross-sectional study among older adults attending wellness programs at three community centers known as Pusat Aktiviti Warga Emas (PAWE) in Kedah, Malaysia, between February and September 2025. Eligible participants were community-dwelling older adults aged ≥60 years who attended PAWE centers, were able to communicate, and provided written informed consent. The participants were excluded if they presented with severe cognitive impairment, acute medical illness, or physical limitations that precluded completion of anthropometric or functional assessments.
Participants were selected using a convenience sampling approach from older adults attending routine programs at the PAWE centers. These centers serve as community hubs for health screening, physical and mental wellness activities for older adults within their respective districts, providing an accessible sampling frame for community-dwelling populations.
Data collection
Before data collection, all trained assessors underwent standardized training conducted by the principal investigator. The training covered study objectives, ethical conduct, informed consent procedures, standardized administration of questionnaires, collection of anthropometric data, and WHO-ICOPE Step 1 screening protocols for IC assessments including all six domains (Mini-Mental State Examination [MMSE], Short Physical Performance Battery [SPPB], Mini Nutritional Assessment–Short Form [MNA-SF], Geriatric Depression Scale–15 [GDS-15], and self-reported sensory). Practical demonstrations and supervised practice sessions were conducted to ensure consistency and inter-observer reliability before field deployment.
Trained assessors conducted ice-breaking and briefing sessions with participants before collecting sociodemographic data (age, gender, ethnicity, education, marital status, and income) and clinical information (number of chronic diseases, medication use, walking aid, hearing aid, pacemaker, and falls in the past year) through structured interviews. Apart from that, height, weight, body mass index (BMI), waist-to-height ratio (WHtR), muscle mass, and skeletal muscle index (SMI) were measured physically by our trained assessors. Assistive device use (walking aid and hearing aid) and pacemaker implantation were recorded as clinical indicators of existing functional limitation and healthcare engagement, and their association with IC was analyzed for the impairment rather than assumed causal determinants.
Multimorbidity was defined as the presence of ≥2 chronic conditions,[16,17] polypharmacy as the concurrent use of ≥5 medications,[18] and low income was classified according to the national poverty threshold (Department of Statistics Malaysia).[19]
Several measures were implemented to minimize reporting and data-collection bias. Standardized and validated instruments were used across all IC domains, and data were collected using uniform protocols by trained assessors. Interviews were conducted in the participants’ preferred language to reduce misunderstanding, and objective measures were prioritized where possible. To limit interviewer bias, assessors followed structured scripts, and data completeness was checked during each visit. Anthropometric and functional assessments were performed using calibrated equipment and standardized procedures.
IC assessment
IC was assessed using the WHO ICOPE Step 1 screening tool.[4] Decline was defined as: cognition (MMSE <24), locomotion (SPPB <9), vitality (MNA-SF <12), vision (visual acuity <6/12 or self-reported impairment), hearing (failed whisper test or self-reported impairment), and psychological status (GDS-15 ≥5). Each domain was coded as impaired (1) or unimpaired (0). Multidomain decline was defined as ≥2 impairments,[6] while IC decline was defined as ≥1 impairment.[17]
Anthropometry and body composition
The participant’s height (cm) and body weight (kg) were measured using standardized protocols, while the BMI was calculated as kilograms divided by square meters height (kg/m2). The waist circumference was measured at the midpoint between the rib and iliac crest with measuring tape in centimeters, with central obesity defined as ≥90 cm in men and ≥80 cm in women.[20] WHtR was calculated as waist circumference (cm) divided by height (cm), with values >0.5 was considered high risk of cardiometabolic disease.[21] SMI was derived from the bioelectrical impedance analysis and defined as low if <7.0 kg/m2 (men) or <5.7 kg/m2 (women).[22]
Statistical analysis
Descriptive statistics summarized participant characteristics and IC prevalence. Logistic regression analyses were performed to examine associations between sociodemographic, clinical, and anthropometric factors and both multidomain and domain-specific IC decline. Independent variables examined included age, sex, ethnicity, education, marital status, multimorbidity, comorbidities, medication use, walking aid, hearing aid, pacemaker, BMI, waist circumference, WHtR, and SMI.
Covariates were chosen based on established literature and their biological relevance. Age and gender were included in all multivariable models as core demographic confounders, while BMI was included to account for the influence of overall adiposity on functional and metabolic outcomes. Additional variables demonstrating statistical significance (P < 0.10) or clinical relevance in unadjusted analyses were entered into multivariable logistic regression models to identify independent factors associated with IC decline.
Adjusted odds ratios (aORs) for age, gender, and BMI with 95% confidence intervals (CIs) were reported, with significance set at P < 0.05. Analyses were conducted using IBM Statistical Package for the Social Sciences Statistics (Version 29.0).
Given the cross-sectional design, all effect estimates represent associations only, and causal relationships between explanatory variables and IC decline cannot be inferred.
This study was conducted and reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement for cross-sectional studies. A completed STROBE checklist indicating where each reporting item is addressed in the manuscript is provided as Supplementary File 1.
Ethical considerations
Ethical approval for this study was granted by the Universiti Teknologi MARA (UiTM) Research Ethics Committee (REC/09/2024 (PG/MR/437)). Written informed consent was obtained from all participants after they were provided with clear information on the study objectives, procedures, potential risks, and benefits. Recruitment and consent were facilitated by trained research assistants, who allowed participants sufficient time to ask questions and decide on their participation.
This study followed the principles of the Declaration of Helsinki. All participants gave written informed consent before taking part. Their confidentiality was carefully protected by removing personal identifiers, storing data securely, and limiting access to the research team only. Participants were also reminded that they could withdraw at any time without affecting their access to care or services.
RESULTS
Characteristics of participants and prevalence of IC
Decline across domains
Table 1 shows the characteristics of the study participants and the prevalence of IC decline across domains. A total of 329 community-dwelling older adults were included, with a mean age of 67.4 ± 6.1 years. The sample comprised slightly more females (52.0%) than males (48.0%). Most participants were married (90.6%) and had at least secondary education (65.3%), but the majority came from low- to middle-income households (median monthly income RM 1500, IQR: 1200– 3000).
| Characteristics | Total (n=329) |
|---|---|
| Age, years, mean±SD | 67.4±6.1 |
| Sex, n(%) | |
| Male | 158 (48.0) |
| Female | 171 (52.0) |
| Marital status, n(%) | |
| Married | 298 (90.6) |
| Widowed/Divorced/Single | 31 (9.4) |
| Education level, n(%) | |
| None | 10 (3.0) |
| Primary | 46 (14.0) |
| Secondary | 215 (65.3) |
| Tertiary | 58 (17.6) |
| Household income, RM/month, median (IQR) | |
| <RM1999.00 | 1500.00 (1200.00–1500.00) |
| RM2000.00–RM3999.00 | 2000.00 (2000.00–2200.00) |
| >RM4000.00 | 4000.00 (4000.00–4372.50) |
| Number of chronic diseases, mean±SD | 1.2±1.1 |
| Morbidity group, n(%) | |
| No disease | 120 (36.5) |
| 1–2 disease | 168 (51.1) |
| >2 diseases | 41 (12.5) |
| Number of medications, mean±SD | 0.9±0.5 |
| Medication group, n(%) | |
| None | 59 (17.9) |
| Non-polypharmacy (1–4) | 243 (73.9) |
| Polypharmacy (≥5) | 27 (8.2) |
| Falls in past 12 months, n(%) | |
| No | 201 (61.1) |
| Once | 80 (24.3) |
| More than once | 48 (14.6) |
| Height, cm, mean±SD | 157.1±0.1 |
| Weight, kg, mean±SD | 66.6±12.4 |
| BMI, kg/m2, mean±SD | 26.9±4.3 |
| BMI group, n (%) | |
| Underweight <18.5 | 8 (2.4) |
| Normal 18.5–22.9 | 56 (17.0) |
| Overweight 23.0–27.4 | 130 (39.5) |
| Obese ≥27.5 | 135 (41.0) |
| Waist circumference, cm, mean±SD | 94.4±11.3 |
| Waist circumference category, n(%) | |
| Normal (Men <90, Women <80) | 37 (11.2) |
| High risk (Men ≥90, Women ≥80) | 292 (88.8) |
| Waist-to-height ratio, mean±SD | 0.59±0.07 |
| Waist-to-height category, n(%) | |
| Normal (<0.50) | 22 (6.7) |
| Central obesity (0.50–0.59) | 149 (45.3) |
| Severe central obesity (≥0.60) | 158 (48.0) |
| Muscle mass, kg, mean±SD | 22.8±5.4 |
| Muscle mass category, n(%) | |
| Normal (≥20 kg men, ≥15 kg women) | 301 (91.5) |
| Low muscle mass | 28 (8.5) |
| Skeletal muscle index, kg/m2, mean±SD | 9.2±1.9 |
| SMI category, n(%) | |
| Normal (≥7.0 men, ≥5.4 women) | 315 (95.7) |
| Low (<7.0 men, <5.4 women) | 14 (4.3) |
| Intrinsic capacity domains impaired, n(%) | |
| Locomotion (SPPB <9) | 132 (40.1) |
| Vitality (MNA-SF <12) | 100 (30.4) |
| Cognition (MMSE <24) | 173 (52.6) |
| Psychological (GDS-15 ≥5) | 59 (17.9) |
| Vision (VA worse than 6/12) | 229 (69.6) |
| Hearing (failed whisper test) | 76 (23.1) |
| IC domain-count score, mean±SD | 2.3±1.2 |
| Any IC decline category | |
| <1 domain | 75 (22.8) |
| ≥1 domain | 254 (77.2) |
Values are presented as mean (SD), median (IQR), or n (%), as appropriate. BMI: Body mass index, IQR: Interquartile range, IC: Intrinsic capacity, MMSE: Mini-mental state examination, SPPB: Short physical performance battery, GDS-15: Geriatric Depression Scale–15; MNA-SF=Mini Nutritional Assessment–Short Form; VA=Visual Acuity
Clinical characteristics revealed a substantial burden of multimorbidity, with over half (51.1%) reporting one to two chronic diseases and 12.5% more than two. Falls were common, with 24.3% experiencing at least one fall in the past year. Polypharmacy was less frequent, affecting 8.2% of participants.
Anthropometric measures showed a high prevalence of overweight and obesity, with a mean BMI of 26.9 ± 4.3 kg/m2; nearly 81% of participants were overweight or obese in combination. Central obesity was particularly striking, present in 88.8% by waist circumference and confirmed by WHtR, where 93.3% were classified as centrally obese, including nearly half 48.0% with severe central obesity. Muscle health was relatively preserved, with only 4.3% showing low SMI.
Regarding IC, impairments were widespread: vision (69.6%) and cognition (52.6%) were the most affected domains, followed by locomotion (40.1%), vitality (30.4%), hearing (23.1%), and psychological function (17.9%). Overall, 77.2% of participants demonstrated a decline in at least one IC domain.
Unadjusted logistic regression analysis of factors associated with IC decline
Unadjusted logistic regression analyses were performed to examine unadjusted associations between sociodemographic and clinical characteristics and IC decline across domains, identifying several significant associates before multivariable adjustment [Table 2].
| Mobility | Vitality | Cognitive | |||||||
|---|---|---|---|---|---|---|---|---|---|
| OR | P-value | 95% CI | OR | P-value | 95% CI | OR | P-value | 95% CI | |
| Age (Ref: 60-69) | |||||||||
| 70–79 | 13.58 | 0.001 | 2.960–62.37 | 1.18 | 0.772 | 0.382–3.654 | 3.601 | 0.054 | 0.978–13.259 |
| 80–89 | 5.73 | 0.050 | 1.002–22.33 | 1.59 | 0.440 | 0.487–5.239 | 3.153 | 0.093 | 0.826–12.044 |
| Ethnic (Ref: Malay) | |||||||||
| Others | 1.41 | 0.405 | 0.625–3.206 | 3.226 | 0.220 | 1.409–7.385 | 1.386 | 0.441 | 0.604–3.182 |
| Gender (R: Male) | |||||||||
| Female | 1.61 | 0.035 | 1.034–2.522 | 1.337 | 0.229 | 0.833–2.146 | 0.614 | 0.029 | 0.397–0.951 |
| Education (Ref: Primary) | |||||||||
| Secondary | 0.095 | 0.005 | 0.018–0.497 | 3.732 | 0.228 | 0.438–31.779 | 0.527 | 0.387 | 0.124–2.244 |
| Tertiary | 0.245 | 0.001 | 0.107–0.559 | 0.707 | 0.410 | 0.310–1.612 | 0.866 | 0.719 | 0.396–1.894 |
| None | 0.643 | 0.175 | 0.339–1.218 | 0.957 | 0.892 | 0.507–1.807 | 1.242 | 0.465 | 0.694–2.224 |
| Smoking (R: No) | |||||||||
| Yes | 0.661 | 0.217 | 0.343–1.276 | 0.497 | 0.075 | 0.235–1.199 | 1.715 | 0.098 | 0.905–3.250 |
| Marital status (R; Married) | |||||||||
| Widow, Divorced, and Single | 3.95 | 0.001 | 1.749–8.931 | 1.161 | 0.714 | 0.523–2.580 | 1.908 | 0.110 | 0.864–4.215 |
| Income (R: <1999) | |||||||||
| 2000–3999 | 1.25 | 0.607 | 0.535–2.919 | 1.138 | 0.777 | 0.464–2.793 | 0.936 | 0.879 | 0.403–2.178 |
| >4000 | 1.37 | 0.488 | 0.557–3.412 | 1.204 | 0.705 | 0.461–3.144 | 0.804 | 0.634 | 0.327–1.977 |
| Comorbid (R: None) | |||||||||
| 1–2 | 2.40 | 0.018 | 1.161–4.998 | 2.456 | 0.018 | 1.166–5.173 | 0.859 | 0.675 | 0.422–1.748 |
| >2 | 1.09 | 0.787 | 0.555–2.176 | 1.698 | 0.137 | 0.845–3.411 | 1.001 | 0.997 | 0.506–1.982 |
| Walking aids (R: None) | |||||||||
| Yes | 8.45 | 0.001 | 4.166–17.157 | 1.839 | 0.046 | 1.012–3.341 | 0.775 | 0.388 | 0.434–1.384 |
| Hearing aids (R: none) | |||||||||
| Yes | 2.89 | 0.041 | 1.043–8.029 | 2.126 | 0.133 | 0.795–5.680 | 1.015 | 0.976 | 0.382–2.700 |
| Pacemaker (R: None) | |||||||||
| Yes | 3.11 | 0.068 | 0.918–10.557 | 2.372 | 0.143 | 0.746–7.545 | 2.799 | 0.128 | 0.744–10.530 |
| Medication (R: None) | |||||||||
| <5 | 1.453 | 0.425 | 0.580–3.642 | 0.447 | 0.132 | 0.157–1.275 | 0.898 | 0.816 | 0.361–2.233 |
| 5 above | 1.422 | 0.387 | 0.640–3.157 | 0.692 | 0.447 | 0.268–1.787 | 0.807 | 0.598 | 0.364–1.789 |
| BMI (Ref: Normal) | |||||||||
| UW | 0.37 | 0.19 | 0.086–1.639 | 0.583 | 0.476 | 0.132–2.568 | 1.642 | 0.509 | 0.377–7.146 |
| OW | 0.89 | 0.74 | 0.476–1.697 | 0.739 | 0.383 | 0.374-1.459 | 0.394 | 0.007 | 0.202–0.771 |
| OB | 0.94 | 0.80 | 0.574–1.539 | 0.684 | 0.160 | 0.403–1.161 | 1.048 | 0.859 | 0.647–1.696 |
| WC (Normal) | |||||||||
| Abnormal | 1.02 | 0.95 | 0.508–2.047 | 2.140 | 0.032 | 1.068–4.288 | 1.555 | 0.218 | 0.770–3.141 |
| SMI (Ref: Normal) | |||||||||
| Abnormal | 0.321 | 0.068 | 0.095–1.089 | 0.134 | 0.003 | 0.036–0.507 | 0.785 | 0.685 | 0.244–2.527 |
| Psychological | Hearing | Vision | |||||||
| OR | P-value | 95% CI | OR | P-value | 95% CI | OR | P-value | 95% CI | |
| Age (Ref: 60-69) | |||||||||
| 70–79 | 1.766 | 0.356 | 0.528–0.591 | 9.000 | 0.001 | 2.853–8.389 | 1.127 | 0.844 | 0.342–3.720 |
| 80–89 | 2.257 | 0.217 | 0.621–8.211 | 3.780 | 0.027 | 1.166–12.26 | 1.023 | 0.972 | 0.295–3.545 |
| Ethnic (Ref: Malay) | |||||||||
| Others | 3.469 | 0.004 | 1.473–8.171 | 2.889 | 0.013 | 1.252–6.665 | 0.760 | 0.527 | 0.324–1.782 |
| Gender (R: Male) | |||||||||
| Female | 1.214 | 0.502 | 0.689–2.140 | 0.902 | 0.694 | 0.540–1.507 | 1.680 | 0.032 | 1.046–2.699 |
| Education (Ref: Primary) | |||||||||
| Secondary | 0.377 | 0.289 | 0.062–2.284 | 0.184 | 0.020 | 0.767–1.371 | 0.755 | 0.705 | 0.176–3.234 |
| Tertiary | 0.526 | 0.301 | 0.155–1.780 | 0.520 | 0.186 | 0.198–1.371 | 0.554 | 0.180 | 0.233–1.313 |
| None | 0.356 | 0.038 | 0.135–0.944 | 0.606 | 0.207 | 0.278–1.320 | 0.763 | 0.386 | 0.415–1.404 |
| Smoking (R: No) | |||||||||
| Yes | 0.774 | 0.588 | 0.328–1.825 | 0.760 | 0.489 | 0.350–1.652 | 0.736 | 0.354 | 0.385–1.407 |
| Marital status (R; Married) | |||||||||
| Widow, Divorced, and Single | 0.907 | 0.850 | 0.332–2.477 | 1.235 | 0.627 | 0.526–2.899 | 1.021 | 0.961 | 0.450–2.315 |
| Income (R: <1999) | |||||||||
| 2000–3999 | 0.162 | 0.079 | 0.021–1.235 | 0.982 | 0.973 | 0.348–2.776 | 1.020 | 0.967 | 0.403–2.580 |
| >4000 | 0.264 | 0.211 | 0.033–2.128 | 0.668 | 0.668 | 0.226–1.976 | 1.175 | 0.747 | 0.440–3.138 |
| Comorbid (R: None) | |||||||||
| 1–2 | 3.018 | 0.016 | 1.228–7.417 | 4.604 | 0.001 | 2.039–10.394 | 0.685 | 0.323 | 0.324–1.450 |
| >2 | 1.393 | 0.407 | 0.636–3.054 | 2.059 | 0.047 | 1.011–4.194 | 0.756 | 0.443 | 0.369–1.545 |
| Walking aids (R: None) | |||||||||
| Yes | 1.534 | 0.230 | 0.763–3.084 | 3.644 | 0.001 | 1.976–6.718 | 1.695 | 0.133 | 0.852–3.374 |
| Hearing aids (R: none) | |||||||||
| Yes | 1.991 | 0.213 | 0.674–5.884 | 5.325 | 0.001 | 1.952–14.523 | 0.366 | 0.045 | 0.137–0.978 |
| Pacemaker (R: None) | |||||||||
| Yes | 3.479 | 0.039 | 1.064–11.371 | 2.475 | 0.132 | 0.762–8.035 | 0.869 | 0.822 | 0.255–2.954 |
| Medication (R: None) | |||||||||
| <5 | 1.125 | 0.826 | 0.394–3.212 | 0.235 | 0.068 | 0.050–1.111 | 3.712 | 0.019 | 1.238–11.129 |
| 5 above | 1.888 | 0.179 | 0.747–4.775 | 0.249 | 0.064 | 0.057–1.085 | 1.710 | 0.298 | 0.622–4.697 |
| BMI (Ref: Normal) | |||||||||
| UW | 0.324 | 0.142 | 0.072–1.458 | 0.227 | 0.046 | 0.053–0.971 | 1.714 | 0.476 | 0.389–7.547 |
| OW | 0.584 | 0.164 | 0.274–1.246 | 0.521 | 0.075 | 0.255–1.067 | 1.353 | 0.383 | 0.686–2.672 |
| OB | 1.071 | 0.839 | 0.553–2.072 | 0.758 | 0.361 | 0.417–1.375 | 1.462 | 0.160 | 0.861–2.482 |
| WC (Normal) | |||||||||
| Abnormal | 1.837 | 0.130 | 0.835–4.038 | 1.710 | 0.156 | 0.814–3.591 | 1.036 | 0.926 | 0.491–2.819 |
| SMI (Ref: Normal) | |||||||||
| Abnormal | 0.420 | 0.168 | 0.122–1.443 | 0.283 | 0.033 | 0.089–0.906 | 1.151 | 0.822 | 0.338–3.914 |
Bold values should be indicated as footnotes, as “Significant at P<0.05”. OR: Odds ratio, CI: Confidence interval, Ref: Reference category, BMI: Body mass index, UW: Underweight, OW: Overweight, OB: Obese, WC: Waist circumference, SMI: Skeletal muscle index
Age showed a strong association with IC decline. Participants aged 70–79 had markedly higher odds of mobility decline (OR = 13.58, P = 0.001) and hearing impairment (OR = 9.00, P = 0.001) compared with those aged 60–69. Ethnicity influenced outcomes, with non-Malay groups showing greater risks of psychological (OR = 3.47, P = 0.004) and hearing decline (OR = 2.89, P = 0.013).
Gender differences highlight that women were more likely to experience mobility (OR = 1.61, P = 0.035) and vision decline (OR = 1.68, P = 0.032), but less likely to have cognitive decline (OR = 0.61, P = 0.029). Education was strongly protective; secondary (OR = 0.095, P = 0.005) and tertiary education (OR = 0.245, P = 0.001) substantially reduced the odds of mobility decline.
Widowed, divorced, and single category participants had nearly four-fold higher odds of mobility decline (OR = 3.95, P = 0.001). Comorbidities raised risks across domains, including hearing (OR = 4.60, P = 0.001) and psychological decline (OR = 3.01, P = 0.016).
Assistive device use showed strong associations with IC decline, with walking aid use markedly increasing the odds of locomotion (OR = 8.45, P = 0.001) and hearing impairment (OR = 3.64, P = 0.001), while hearing aid use being associated with hearing impairment (OR = 5.33, P = 0.001). These associations likely reflect underlying functional limitations rather than causal effects on IC.
Body composition also contributed with abnormal waist circumference that raised vitality decline risk (OR = 2.14, P = 0.032), whereas higher skeletal muscle was associated with lower odds off vitality (OR = 0.134, P = 0.003) and hearing decline (OR = 0.283, P = 0.033).
Multivariable-adjusted (age, gender, and BMI) logistic regression analysis of factors associated with IC decline
Variables that showed significant or clinically relevant associations in the unadjusted analyses were further entered into multivariate logistic regression models to adjust for potential confounders and to identify the independent association of IC decline [Tables 3 and 4]. Across domains, device use remains the most consistently associated factor of IC decline. For mobility, walking aid use demonstrated the strongest effect, with users nearly 8 times more likely to experience decline (aOR 7.75, 95% CI: 3.72–16.15, P = 0.001). Interestingly, comorbidities were inversely associated, as individuals with one to two conditions (aOR 0.46, 95% CI: 0.27–0.79, P = 0.005) or more than two (aOR 0.39, 95% CI: 0.18–0.86, P = 0.019) showed reduced odds of decline, and lack of formal education was also associated with a protective effect (aOR 0.35, 95% CI: 0.15–0.82, P = 0.015).
| Predictor | Mobility: aOR (95% CI) | Mobility:P-value | Vitality: aOR (95% CI) | Vitality:P-value | Cognition: aOR (95% CI) | Cognition:P-value |
|---|---|---|---|---|---|---|
| Walking aid use | 7.75 (3.72–16.15) | 0.001 | 1.99 (1.07–3.69) | 0.030 | 0.82 (0.45–1.51) | NS |
| Comorbidities (1–2 conditions) | 0.46 (0.27–0.79) | 0.005 | 2.28 (1.06–4.89) | 0.035 | 1.07 (0.50–2.25) | NS |
| Comorbidities (>2 conditions) | 0.39 (0.18–0.86) | 0.019 | 1.55 (0.76–3.15) | NS | 1.12 (0.55–2.27) | NS |
| No formal education | 0.35 (0.15–0.82) | 0.015 | 0.16 (0.02–1.50) | NS | 1.31 (0.72–2.40) | NS |
| Non-Malay ethnicity | 0.82 (0.31–2.17) | NS | 0.28 (0.11–0.67) | 0.005 | 1.20 (0.48–2.90) | NS |
| Abnormal SMI | 0.33 (0.09–1.26) | NS | 0.15 (0.04–0.59) | 0.007 | 0.70 (0.20–2.50) | NS |
Models were adjusted for age, gender, and body mass index (BMI). Only key associates demonstrating independent associations with each intrinsic capacity domain are presented. NS indicate non-significant, variables that were not independently associated with the respective domain after adjustment. No independent associations were identified for the cognition domain in the fully adjusted model. BMI: Body mass index, aOR: Adjusted odds ratios, CI: Confidence interval, SMI: Skeletal muscle index
| Predictor | Psychological: aOR (95% CI) | Psychological:P-value | Hearing: aOR (95% CI) | Hearing:P-value | Vision: aOR (95% CI) | Vision:P-value |
|---|---|---|---|---|---|---|
| Non-Malay ethnicity | 4.09 (1.60–10.42) | 0.003 | 1.99 (0.78–5.05) | NS | 0.76 (0.30–1.89) | NS |
| Comorbidities (≥1 condition) | 3.10 (1.23–7.84) | 0.017 | 0.40 (0.20–0.80) | 0.009 | 0.57 (0.25–1.25) | NS |
| Pacemaker use | 3.52 (1.03–12.02) | 0.044 | 1.70 (0.48–6.05) | NS | 0.93 (0.26–3.30) | NS |
| No formal education | 0.36 (0.13–0.96) | 0.040 | 0.70 (0.31–1.56) | NS | 0.75 (0.40–1.39) | NS |
| Walking aid use | 1.70 (0.80–3.50) | NS | 3.55 (1.85–6.80) | 0.001 | 1.60 (0.80–3.22) | NS |
| Hearing aid use | 1.70 (0.52–5.50) | NS | 4.33 (1.46–12.82) | 0.008 | 0.35 (0.12–0.99) | 0.048 |
| Comorbidities (1–2 conditions) | 3.10 (1.22–7.80) | 0.017 | 0.41 (0.22–0.76) | 0.009 | 0.57 (0.26–1.25) | NS |
| Comorbidities (>2 conditions) | 1.31 (0.60–2.93) | NS | 0.16 (0.05–0.55) | 0.001 | 0.70 (0.33–1.50) | NS |
| Medication use (<5 drugs) | 1.20 (0.42–3.50) | NS | 0.21 (0.04–1.05) | NS | 0.45 (0.25–0.88) | 0.008 |
| Medication use (≥5 drugs) | 2.00 (0.78–5.13) | NS | 0.26 (0.06–1.19) | NS | 0.25 (0.08–0.76) | 0.014 |
Models were adjusted for age, gender, and body mass index (BMI). Only key associates demonstrating independent associations with each intrinsic capacity domain are presented. NS indicate non-significant, variables that were not independently associated with the respective domain after multivariable adjustment. BMI: Body mass index, aOR: Adjusted odds ratios, CI: Confidence interval
Vitality decline was linked to walking aid use (aOR 1.99, 95% CI: 1.07–3.69, P = 0.030) and comorbidities (aOR 2.28, 95% CI: 1.06–4.89, P = 0.035), whereas non-Malay ethnicity (aOR 0.28, 95% CI: 0.11–0.67, P = 0.005) and abnormal SMI (aOR 0.15, 95% CI: 0.04–0.59, P = 0.007) were protective. No independent associations were observed for cognitive decline after multivariable adjustment.
Psychological decline was strongly associated with non-Malay ethnicity (aOR 4.09, 95% CI: 1.60–10.42, P = 0.003), comorbidities (aOR 3.10, 95% CI: 1.23–7.84, P = 0.017), and pacemaker use (aOR 3.52, 95% CI: 1.03–12.02, P = 0.044), while lack of formal education showed protective effects (aOR 0.36, 95% CI: 0.13–0.96, P = 0.040).
For hearing, significant risks were observed with walking aid (aOR 3.55, 95% CI: 1.85–6.80, P = 0.001), hearing aid (aOR 4.33, 95% CI: 1.46–12.82, P = 0.008), and pacemaker use (aOR 3.52, 95% CI: 1.03–12.02, P = 0.044), whereas comorbidities were protective (one to two conditions: aOR 0.41, P = 0.009; more than two: aOR 0.16, P = 0.001). In the adjusted models, assistive device use and pacemaker implantation remained strongly associated with IC impairment, supporting their interpretation as markers of accumulated morbidity and functional limitation rather than independent associations.
Vision outcomes highlighted the protective influence of medication use (fewer than five drugs: aOR 0.45, 95% CI: 0.25–0.88, P = 0.008; ≥5 drugs: aOR 0.25, 95% CI: 0.08–0.76, P = 0.014) and hearing aid use (aOR 0.35, 95% CI: 0.12–0.99, P = 0.048).
DISCUSSION
This study contributes to the growing body of evidence on IC by demonstrating a high burden of multidomain decline among community-dwelling older adults in a rapidly aging Malaysian state. Rather than repeating prevalence estimates, the present findings are best interpreted in relation to international research that has established IC as a sensitive marker of early functional vulnerability preceding frailty and disability. The predominance of vision impairment and evidence of cognitive decline risk observed in this study are consistent with reports from China and other Southeast Asian countries,[23,24] where uncorrected sensory deficits and cognitive decline remain common due to delayed screening and limited access to preventive services.[9,22]
The recruitment of participants from PAWE community centers has important implications for interpretation and generalizability. PAWE centers represent structured wellness environments that attract older adults who are more socially connected, health-aware, and functionally mobile. As a result, the prevalence of IC decline observed in this study may underestimate the true burden among less-engaged or more vulnerable older adults, while certain associations, particularly those related to healthcare engagement and assistive device use, may be amplified in this setting. Accordingly, the findings should be generalized primarily to older adults living in similar community-based, wellness-oriented settings, rather than to the entire older population, including those who are homebound, institutionalized, or socially isolated.
The strong association between walking-aid use and declines in locomotion, vitality, and hearing mirrors findings from European and Japanese cohorts, where reliance on assistive devices reflects underlying functional limitation and progression toward frailty rather than acting as an independent causal factor.[25,26] This consistency across regions reinforces the interpretation of device use as a marker of accumulated functional loss, supporting the WHO conceptual distinction between IC and disability. Similarly, the association between multimorbidity and declines in vitality and psychological domains is consistent with longitudinal evidence linking clustered chronic conditions with greater energy loss and psychological burden.[8]
Importantly, assistive device use and pacemaker implantation typically occur after the onset of functional impairment, and therefore, their associations with IC decline likely reflect reverse causation and underlying disease severity, consistent with the WHO distinction between IC, functional impairment, and disability.
Notably, several findings highlight context-specific patterns that differ from those of Western populations. The protective associations observed for education and selected indicators of healthcare engagement may reflect differences in health literacy, healthcare engagement, and access to ongoing care among older adults with regular health system contact.[27] Comparable patterns have been reported in Korea and Taiwan, where frequent interaction with primary care reduced sensory and mobility decline despite a high burden of chronic disease.[28,29] These findings suggest that the relationship between multimorbidity and IC decline is not uniform and may be modified by access to healthcare services and continuity of care.[30]
From a global perspective, the present results have relevance beyond Malaysia. Regions with similar sociodemographic profiles, including other middle-income Southeast Asian countries and rapidly aging rural populations elsewhere, face comparable challenges of sensory impairment, multimorbidity, and delayed preventive care. The consistency of key associations across diverse settings supports the transferability of WHO-ICOPE-aligned strategies, particularly those emphasizing early screening, mobility preservation, nutritional optimization, and mental health support delivered at the community level.
Importantly, this study reinforces the value of IC as a practical framework for population-level prevention, rather than a diagnostic endpoint. By detecting early signs of functional vulnerability before disability becomes apparent, IC-based surveillance helps health systems focus on scalable, person-centered interventions.[31] In settings such as Kedah, embedding multidisciplinary ICOPE pathways within existing community hubs, including PAWE centers and primary care clinics, offers a feasible approach to preserving independence and delaying disability. Similar models may be adapted in other regions facing parallel demographic and health system constraints.[32]
Strengths and Limitations
This study has several strengths, particularly in its comprehensive assessment of IC across all six WHO-ICOPE domains within a Malaysian population. It is one of the first to assess IC comprehensively across all six WHO-ICOPE domains in a Malaysian population, using validated tools and standardized administration by trained assessors monitored by principle investigator with physiotherapy background. The relatively large sample size and inclusion of participants from multiple PAWE centers strengthen the reliability of the findings and provide valuable insights into the health status of older adults in rural and semi-urban communities.
Several limitations should also be acknowledged. The study excluded participants from urban areas, which may limit the generalizability of the results to the wider Malaysian aging population. The cross-sectional design prevents causal interpretations of the associations identified. Reliance on self-reported data, such as falls and medical history, introduces the potential for recall bias. Finally, while validated screening instruments were employed, the absence of clinical diagnostic confirmation may have resulted in under- or over-estimation of impairments in certain domains. This recruitment approach introduces potential selection bias, as older adults who attended PAWE centers are likely to be more socially engaged and functionally independent than non-attendees. Because participants were recruited from PAWE community centers, which provide structured wellness, social, and health-promotion activities, the study population may differ systematically from the broader older adult population in terms of health status, health-seeking behavior, and social support.
CONCLUSION
This study highlights a substantial burden of multidomain IC decline among community-dwelling older adults, reinforcing IC as a sensitive marker of early functional vulnerability rather than clear disability. The observed associations, particularly those related to multimorbidity and markers of functional limitation, are consistent with international evidence and support the conceptual distinction between IC, functional impairment, and disability proposed by the WHO. Importantly, the findings demonstrate the relevance of IC-based surveillance for guiding preventive, person-centered strategies in populations with similar sociodemographic profiles, including rapidly aging middle-income settings. Embedding WHO-ICOPE-aligned screening and early interventions within community and primary care platforms may offer a scalable approach to preserving functional ability and delaying disability across diverse regions.
These findings are most applicable to community-active older adults in settings similar to PAWE centers and should not be extrapolated to more frail or socially isolated populations without caution. Given the cross-sectional design, these findings should be interpreted as associative rather than causal, and the implications for intervention should be viewed as informative for future research and planning, rather than definitive evidence of effectiveness. Overall, the findings reinforce IC as an early functional vulnerability construct, with assistive devices representing markers of existing functional limitation rather than causal influences on IC decline.
Reporting guidelines
The reporting of this cross-sectional study complies with the STROBE guidelines. The completed STROBE checklist is available as Supplementary File 1.
Acknowledgment:
We would like to thank all the community center facilitators of the 3 PAWE institutions where the data collection took place for the permission given and facilitating the process.
Authors’ contributions:
NN: Data collection, wrote the original manuscript draft, and data management. YCW: Data analysis reviewed and edited the manuscript. MJ: Principal investigator, data analysis, and reviewed and edited the manuscript.
Ethical approval:
The research/study approved by the Institutional Review Board at Universiti Tecknologi MARA, number (REC/09/2024 (PG/MR/437)), dated September 03, 2024.
Declaration of patient consent:
Written informed consent was obtained from the patient for publication of this original article and accompanying images. Efforts have been made to protect the patient’s identity.
Conflicts of interest:
There are no conflicts of interest.
Availability of data and material:
The datasets supporting this study’s findings will be available on request from the corresponding author.
Use of Artificial Intelligence (AI)-Assisted Technology for manuscript preparation:
Artificial intelligence (AI) tools were used solely to assist with language editing. No AI tools were used for data extraction, statistical analysis, result interpretation, or the generation of original scientific content. All analyses were conducted by the authors, who take full responsibility for the integrity and accuracy of the manuscript.
Financial support and sponsorship: Nil
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