Intrinsic capacity differs from functional ability in predicting 10-year mortality and biological features in healthy aging: results from the I-Lan longitudinal aging study

Results

Demographic characteristics of participants stratified by IC and FA status

The demographic characteristics of the participants (mean age 63.9 ± 9.3 years, 47.5% men) are shown in Supplementary Table 1. Compared to the high IC group (n = 1190), those with low IC (n = 649) were older (70.0 ± 8.8 vs. 60.6 ± 7.7 years old), mainly women (63.0% vs. 46.8%), had fewer years of education (2.5 ± 3.4 vs. 8.2 ± 4.5 years), were less likely to consume alcohol (23.0% vs. 38.5%), and had a higher disease burden (CCI 1.6 ± 1.4 vs. 0.7 ± 1.1). Compared to the high FA group (n = 1769), those with low FA (n = 70) were older (76.0 ± 9.9 vs. 63.5 ± 8.9 years old), had fewer years of education (2.9 ± 4.1 vs. 6.4 ± 4.9 years), were less likely to consume alcohol (15.7% vs. 33.7%) and had a higher disease burden (CCI 2.3 ± 1.6 vs. 1.0 ± 1.2). Comparisons of subcategories of IC were shown in Supplementary Table 2. The distributions of IC and FA were left-skewed (Supplementary Figure 1). Overall, IC declined progressively from 86.0 ± 5.1 to 80.5 ± 5.1 points, and FA declined from 99.9 ± 1.3 to 99.3 ± 4.1 points in a mean follow-up period of 6.5 ± 0.8 years.

Survival analysis for IC and FA status

There were 238 deaths in a mean follow-up period of 8.5 ± 1.5 years. Kaplan–Meier analysis showed that low FA (Figure 1A, log-rank test, p < 0.001) and low IC (Figure 1B, log-rank test, p < 0.001) were significantly associated with mortality. A one-point (percent) increase in IC score decreased the odds of mortality by 5% (HR 0.95, 95% CI 0.93–0.97, p < 0.001), and those with low IC had a greater risk of mortality (HR 1.94, 95% CI 1.39–2.70, p < 0.001). The associations between FA and mortality were attenuated after adjusting for relevant confounders (Table 1).

Figure 1. Kaplan–Meier survival plots for (A) functional ability and (B) intrinsic capacity.

Table 1. Relationship between Intrinsic capacity, functional ability and mortality.

	Model Ia	p	Model IIb	p
	HR (95%CI)		HR (95%CI)
Intrinsic capacityc	0.94 (0.92–0.96)	<0.001	0.95 (0.93–0.97)	<0.001
Functional abilityc	0.97 (0.94–1.00)	0.025	0.97 (0.94–1.00)	0.089
Low Intrinsic capacityd	2.19 (1.58–3.04)	<0.001	1.94 (1.39–2.70)	<0.001
Low Functional abilityd	1.53 (1.00–2.33)	0.049	1.29 (0.84–1.97)	0.248
Components of intrinsic capacityc
Locomotion	0.97 (0.96–0.98)	<0.001	0.97 (0.96–0.98)	<0.001
Cognition	0.99 (0.98–1.00)	0.010	0.99 (0.98–1.00)	0.018
Psychology	0.99 (0.97–1.00)	0.022	0.99 (0.98–1.00)	0.139
Vitality	0.97 (0.95–0.98)	<0.001	0.98 (0.96–0.99)	0.006
Sensory	0.98 (0.95–1.00)	0.047	0.98 (0.96–1.01)	0.182
aCox proportional hazards model adjusted for age, gender, and education years. bCox proportional hazards model adjusted for age, gender, education years, smoke, drink and charlson comorbidity index. cnumerical variables. dcategorical variables.

Biomarkers associated with low IC

The results of adjusted logistic regression analysis for the associations between biomarkers and low IC are shown in Figure 2. Participants with higher levels of fasting glucose had higher odds of having low IC (OR 1.40, 95% CI 1.09–1.81, p = 0.010), but those with higher levels of cholesterol (OR 0.60, 95% CI 0.47–0.79, p < 0.001) and LDL-C (OR 0.72, 95% CI 0.55–0.94, p = 0.015) were less likely to have low IC. Those in the lowest tertile of DHEA-S had higher odds for low IC (OR 3.33, 95% CI 1.32–8.41, p = 0.011). Of the inflammatory biomarkers, higher levels of hsCRP (OR 1.45, 95% CI 1.05–2.00, p = 0.023) and neutrophil-to-lymphocyte ratio (NLR, highest tertile OR 1.77, 95% CI 1.29–2.43, p < 0.001) were significantly associated with low IC (Figure 2).

Figure 2. Logistic regression to explore biomarkers associated with low intrinsic capacity at baseline.

Biomarkers associated with longitudinal preservation or deterioration of IC

Adjusted logistic regressions showed that predictors for rapid deterioration of IC were lower levels of dehydroepiandrosterone sulfate (DHEA-S, middle tertile OR 1.84, 95% CI 1.15–2.95, p = 0.012; lowest tertile OR 2.25, 95% CI 1.34–3.77, p = 0.002) and vitamin D deficiency (OR 1.82, 95% CI 1.02–3.27, p = 0.044) (Figure 3). Inverse probability weighting regressions were used to reduce potential selection bias from excluded participants, and findings were similar (OR 1.41, 95% CI 1.09–1.83, p = 0.008 for lowest tertile of DHEA-S; OR 1.06, 95% CI 1.01–1.12, p = 0.030 for vitamin D deficiency). Supplementary Figure 2 shows adjusted logistic regression to explore potential biomarkers for maintained or improved IC. All biomarkers showed insignificant associations.

Figure 3. Logistic regression to explore biomarkers associated with rapidly deteriorated intrinsic capacity at a 7-year follow-up period.

Materials and Methods

Participants and study design

Data from the first and third waves of the I-Lan Longitudinal Aging Study (ILAS) were collected for the baseline cross-sectional (wave 1) and longitudinal cohort analyses (wave 1 and 3). ILAS was a prospective cohort study focused on interactions between sarcopenia, frailty, and cognitive functioning throughout the aging process. The details of the study design, participant recruitment, and data collection of ILAS have been reported previously [33]. Briefly, ILAS recruited community-dwelling adults aged ≥50 years without severe disability, dementia or communication difficulties, limited life expectancy due to major illness or being institutionalized. The first part of this study was a survival analysis of a 10-year follow-up, and the second part was a 7-year longitudinal study to capture biological features based on the status of IC changes (maintained, improved and rapidly deteriorated). In the first part of the study, data from 1,839 participants from the ILAS wave 1 survey in 2011 were used to evaluate the 10-year mortality risk of IC and FA (Figure 4A). In the second part of the study, 1019 participants who recruited in ILAS wave 1 and completed the ILAS wave 3 survey since 2018 (216 participants died before wave 3 survey and 604 participants declined to participate in wave 3 survey) were enrolled (Figure 4B). Compared to those enrolled in the second part of this study, those excluded were older (67.5 ± 10.0 vs. 61.1 ± 7.5 years, p < 0.001), less educated (4.5 ± 4.5 vs. 7.6 ± 4.8 years, p < 0.001), higher disease burden of Charlson comorbidity index (1.4 ± 1.4 vs. 0.7 ± 1.1, p < 0.001), but similar sex proportions.

Figure 4. Study flowcharts of (A) survival analysis and (B) longitudinal study for biological features of intrinsic capacity. Abbreviations: IC: denotes intrinsic capacity; FA: denotes functional ability.

This study was designed and conducted in accordance with the principles of the 1964 Declaration of Helsinki and later amendments. The institutional review board of National Yang Ming University (YM103008) and Taipei Veterans General Hospital (2018-05-003B) approved the study protocol, and written informed consent was obtained from each individual before inclusion. The observational design and reporting format followed the STROBE guidelines [34].

Intrinsic capacity (IC)

The five IC elements, i.e., cognition, locomotion, vitality, psychology, and sensory, were selected based on the principle proposed by WHO ICOPE [5].

Cognition was evaluated by the Chinese version of the Mini-Mental State Examination (MMSE), with scores ranging from 0 to 30, and a higher score on the MMSE indicated better cognition [35]. Locomotion was assessed by a timed 6-meter gait speed at the usual pace in meters/second based on a consensus recommended by the Asian Working Group for Sarcopenia (AWGS) [36]. Vitality was assessed by the Mini Nutritional Assessment (MNA), with scores ranging from 0 to 30, and a higher score indicated better nutrition [37]. Psychology was measured with the Center for Epidemiologic Studies—Depression scale (CESD) with scores ranging from 0 to 60, and a higher score denoted a greater level of depressive symptoms [38]. Psychological scores were obtained by multiplying the original CESD scores by −1 in this study. The reason why we would like to adopt this approach is mainly because IC was constructed based on positive capacity for physical and mental reserves. However, we used CESD to measure mental reserve, but a higher CESD score indicates the higher level of depression. We thus rescale our CESD by multiplying the original CESD by −1. Sensory impairment was assessed through a self-reported score comprising visual and hearing impairments based on a previous study [12]. A sensory score was built from two questions of vision and hearing: score from 0 (independent), −1 (need supervision), −2 (need help), and −3 (dependent), yielding a total score ranging from −6 to 0. We further used the percent of maximum possible method - calculated by [100 × (observed − minimum)/(maximum − minimum)]- to rescale all individual variables with a ranging from 0 (minimum possible) to 100 (maximum possible) [39] to make the composite values of IC comparable longitudinally [40]. Psychological scores were obtained by 100 minus the rescaled CESD scores. For each study participant, we calculated their IC scores as the mean of the sum of subscores obtained in each of five elements.

Functional ability (FA)

Functional ability (FA) was measured by SMAF through the percent of maximum possible method to rescale the original score with the range from 0 to 100. SMAF is a 29-item four-level measurement scale based on WHO’s classification of impairments, disabilities, and handicap with consideration of available resources and environmental factors to compensate for functional impairment [41]. The SMAF assessed functional ability in 5 areas: activities of daily living (ADL) [7 items], mobility [6 items], communication [3 items], mental functions [5 items] and instrumental activities of daily living (IADL) [8 items]. For each item, the disability was scored on a 4-level scale: 0 (independent), −0.5 (with difficulty), −1 (needs supervision), −2 (needs help), −3 (dependent). Resources available to compensate for the disability were also evaluated, and a handicap score was deducted. The stability of the resources was also assessed. A disability score (on −87) can be calculated, together with subscores for each dimension. Given the involvement of environmental factors, the SMAF evaluated a person’s FA rather than their IC alone [42].

Acquisition of mortality

All participants in ILAS received a phone call by research nurses every 3 months to check their health conditions and survival status. These survival data were calculated from the index interview day until the last phone contact before 31 March 2022.

Other variables

Potential confounding variables were identified from previous literature, which included age, sex, education years, smoking and alcohol consumption in the past six months (yes versus no). The burden of disease was assessed by Charlson’s comorbidity index (CCI) [43]. Venous blood samples were collected from all ILAS participants after a 10-hour overnight fast. Biomarkers related to cardiometabolic health, hormones and biochemistry were tested for all participants, including fasting glucose, total cholesterol, triglycerides, LDL, insulin level, and homeostasis model assessment-insulin resistance (HOMA-IR)-insulin resistance. Inflammatory biomarkers (NLR, platelet-to-lymphocyte ratio, homocysteine, and hsCRP), age-related hormones (growth hormone, IGF-1, DHEA-S, testosterone, sex hormone binding globulin (SHBG), intact parathyroid hormone, and micronutrients (vitamin B12, folic acid and vitamin D, measured by 25-OH vitamin D) were also tested for all participants. Details of the machine, limit of detection, and intra- and inter-assay coefficients of variation for serum biomarkers are shown in the appendix (Supplementary Table 3). The free androgen index (FAI) was calculated from testosterone and SHBG [44].

Statistical analysis

Numerical variables were expressed as the mean ± standard deviation, and categorical variables were expressed as numbers with percentages. Comparisons of baseline characteristics between different IC or FA groups were performed by Student’s t test for continuous variables and chi-square tests or Fisher’s exact test for categorical variables. In the first part of this study, IC (≥82.7 vs. <82.7) and FA (≥98.9 vs. <98.9) at baseline were assigned to high IC/FA or low IC/FA groups according to the abovementioned cutoff values. Receiver operating curve (ROC) analysis and Youden’s index maxima were used to determine the optimal cutoff values that achieved optimal discrimination (Supplementary Table 4). Subcategories of IC as mobility (≥39.8 vs. <39.8), cognition (≥86.7 vs. <86.7), psychological (≥96.7 vs. <96.7), vitality (≥88.3 vs. <88.3), and sensory (≥83.3 vs. <83.3) were categorized into high and low for comparisons of baseline characteristics. Multivariable logistic regression was used to assess the associations between identified biomarkers and low IC. Cox proportional hazard regression was used to evaluate the association between IC, FA, and mortality. Schoenfeld residuals were used to test proportionality assumptions in Cox proportional hazard models. Kaplan–Meier survival plots and log-rank tests were applied to investigate the association between IC, FA, and mortality. In the second part of this study, multivariable logistic regressions were used to identify biomarkers associated with maintained or improved IC or rapidly deteriorated IC. The rapidly deteriorated IC group was defined as those with a decline in IC score >10% (equal to the 1 standard deviation (SD) lower than the group mean of decline in IC score) between wave 1 and 3 survey.

Biomarkers were dichotomized based on definitions used in previous literature: HOMA-IR (≥2 vs. <2) [45], high cholesterol (≥200 or taking lipid lower drugs vs. <200 mg/dL) [46], high triglycerides (≥150 or taking lipid lower drugs vs. <150 mg/dL) [46], high LDL-C (≥130 or taking lipid lower drugs vs. <130 mg/dL) [46], high fasting blood glucose (≥100 or taking oral anti-diabetic drugs vs. <100 mg/dL) [46], hyperhomocysteinemia (>15 vs. ≤15 μmol/L), and hsCRP (≥0.3 vs. <0.3 mg/dL) [47]. All other biomarkers, including the FAI, were tertilized [44]. Vitamin D insufficiency and deficiency were defined by 25-OH vitamin D <20 and <10 ng/mL, respectively [29].

A p value from two-sided tests <0.05 and 95% CIs not spanning the null hypothesis values were considered to be statistically significant. All analyses were performed using the SAS statistical package version 9.4 (SAS Institute, Inc., Cary, NC, USA).

Abbreviations

WHO: World Health Organization; IC: Intrinsic Capacity; FA: Functional Ability; ICOPE: Integrated Care for Older People; DHEA-S: dehydroepiandrosterone sulfate; IGF-1: insulin-like growth Factor 1; hsCRP: high-sensitivity C-reactive protein; ILAS: I-Lan Longitudinal Aging Study; MMSE: Mini-Mental State Examination; AWGS: Asian Working Group for Sarcopenia; MNA: Mini Nutritional Assessment; CESD: Epidemiologic Studies—Depression scale; SMAF: Functional Autonomy Measurement System; ADL: activities of daily living; IADL: instrumental activities of daily living; CCI: Charlson’s comorbidity index; LDL: low-density lipoprotein cholesterol; HOMA-IR : homeostasis model assessment-insulin resistance -insulin resistance; NLR: neutrophil-to-lymphocyte ratio; FAI: free androgen index; ROC: Receiver operating curve.

Author Contributions

Conceptualization, W-J.L., L-N.P., M-H.L., C-H. L., and L-K.C.; Methodology, W-J.L.; Validation, L-N.P., M-H.L., C-H. L., and L-K.C.; Formal analysis, W-J.L.; Investigation, W-J.L.; Resources, L-K. C.; Data curation, W-J.L.; Writing – original draft preparation, W-J.L.; Writing –review and editing, W-J.L., L-N.P., M-H.L., C-H. L.,F-Y.H., and L-K.C.; Visualization, W-J.L.; Supervision, L-K.C.; Project administration, W-J.L.

Acknowledgments

We express our gratitude for the support from the Center for Geriatrics and Gerontology of Taipei Veterans General Hospital and Department of Family Medicine of Taipei Veterans General Hospital Yuanshan Branch.

Conflicts of Interest

The authors declare no conflicts of interest related to this study.

Ethical Statement and Consent

This study was designed and conducted in accordance with the principles of the 1964 Declaration of Helsinki and later amendments. The institutional review board of National Yang Ming University (YM103008) and Taipei Veterans General Hospital (2018-05-003B) approved the study protocol, and written informed consent was obtained from each individual before inclusion. The observational design and reporting format followed the STROBE guidelines [34].

Funding

The whole study was funded by the National Science and Technology Council (NSTC-108-2634-F-010-001, NSTC 111-2314-B-A49-048-MY2, NSTC 111-2321-B-A49-006, and NSTC 111-2321-B-A49-008), National Health Research Institute (NHRI-11A1-CG-CO-01-2225-1), and Taipei Veterans General Hospital (110VACS-001).

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