# Healthy aging: how does a multidimensional construct of functional ability predict objective and subjective outcomes?

Antoine Gbessemehlan, Cécile Proust-Lima, Luc Letenneur, Hélène Amieva,
Karine Pérès

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Antoine Gbessemehlan, Cécile Proust-Lima, Luc Letenneur, Hélène Amieva, Karine Pérès. Healthy aging: how does a multidimensional construct of functional ability predict objective and subjective outcomes?. BMC Geriatrics, 2025, 25 (1), pp.727. 10.1186/s12877-025-06328-3. hal-05294925

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# Healthy aging: how does a multidimensional construct of functional ability predict objective and subjective outcomes?

Antoine Gbessemehlan¹* ID, Cécile Proust-Lima¹, Luc Letenneur¹, Hélène Amieva¹ and Karine Pérès¹*

**Abstract**

**Background** Despite the comprehensive and holistic conceptual approach proposed by the WHO to measure Functional Ability (FA) in healthy aging, research exploring both intrinsic capacity (IC) and environments is rare. This study aimed to define a multidimensional FA construct based on the WHO framework and investigate its association with objective (mortality, IADL-disability) and subjective (poor life satisfaction, poor perceived health) outcomes.

**Methods** The sample included 587 older participants from the AMI (Aging Multidisciplinary Investigation) epidemiological cohort. In total eight subdomains of FA were defined using Structural Equation Models: five related to IC and three to the living environment (from 30 collected variables in total). Cox regression models were used to investigate the association between FA and incident adverse outcomes.

**Results** Participants were classified into four levels of FA (34% in very high, 16% in high, 22% in medium, and 28% in low). Compared to those with very high FA, participants with low FA had significantly higher risks of death (Hazard Ratio HR = 2.19; 95% Confidence Interval: 1.30–3.68), IADL-disability (HR = 3.13; 95% CI: 1.99–4.92) and were more likely to experience poor life satisfaction (HR = 1.87; 95% CI: 1.15–3.03) and poor perceived health (HR = 3.97; 95% CI: 1.85–8.53).

**Conclusion** Low FA levels are strongly associated with increased risks of both objective and subjective negative outcomes. These findings highlight the importance of simultaneously considering IC and environment to properly explore FA in healthy aging.

**Keywords** Healthy aging, Mortality, Disability, Life satisfaction, Subjective health

<footnote>*Correspondence:
Antoine Gbessemehlan
sgbessemehlan@yahoo.fr
Karine Pérès
karine.peres@u-bordeaux.fr
¹Univ. Bordeaux, INSERM UMR 1219, Bordeaux Population Health
Research Center, Bordeaux, France</footnote>
**Background**

With advancing age, most people experience a decline in physiological capacities, but with a great heterogeneity. While some older adults maintain good abilities in coping with daily living, others experience early losses, whilst others exhibit late but accelerated losses [1]. To better understand this heterogeneity, several studies explored over the past few decades how to define and assess the aging construct through a positive approach of aging. These works have led to the emergence of numerous concepts, such as successful aging, active aging, productive aging, healthy aging, etc [2–5]. Nevertheless, these entities lack consensus on their definition and how to measure them [2]. While the oldest concepts mainly relied on biomedical factors to operationalize the concept, more recent ones, such as healthy aging, tend to enrich the approach by including psychosocial factors or personal perspectives on their aging [2, 3, 5–7].

In 2015, the World Health Organization (WHO) provided a new definition and framework to assess healthy aging [8]. Healthy aging has been defined as the process of developing and maintaining Functional Ability (FA) that enables older people to continue to do what is valuable to them [8]. Thus, such a definition makes FA the key feature of healthy aging. It combines the Intrinsic Capacity (IC) of individuals, their living environments, and the way they interact. IC refers to all the mental and physical capacities that a person can draw on and includes their capacities to walk, think, see, hear, and remember [8]. Environments refer to the home, community, the built environment, relationships, attitudes, beliefs, health and social policies, and services that support them [8]. Nonetheless, the existing studies have largely investigated the construct of IC than the individuals’ environment and even less both simultaneously [9–14]. Findings from these studies have shown that altered IC was associated with an increased risk of adverse outcomes, such as disability, institutionalization or death [10, 11, 15, 16].

From a clinical and research perspective, the new WHO framework seems to be relevant to assess in a global and holistic way healthy aging in the older adults through their FA. Indeed, according to this framework, beyond IC, it is crucial to also consider individuals’ environment to properly assess healthy aging. Indeed, a good living environment may compensate to some extent the alteration of IC commonly observed in old age and thereby contributes to maintain a good level of FA [8]. However, to date, the multidimensional approach of FA as suggested by the WHO remains poorly explored in epidemiological studies [5, 17, 18]. Studies measuring the construct of FA are still limited [17–19], while it is critical to provide more evidence and better understand this construct. Furthermore, the degree of association between FA and various adverse outcomes are

poorly known. To promote such a comprehensive construct, longitudinal epidemiological studies using methodological and/or biostatistical approaches to measure and define FA are essential. To do so, we leveraged data from a French cohort to define FA according to a multidimensional approach by analyzing simultaneously IC and environmental factors. We aimed to examine the predictive value of FA measure by investigating the association between initial levels of FA and the risk of objective outcomes - mortality and disability - and subjective outcomes - based on individual perceptions, poor life satisfaction and perceived health.

**Materials and methods**

**Data and study population**

This study was conducted on the AMI (Aging Multidisciplinary Investigation) cohort, a French longitudinal study on health and aging in retired farmers living in rural area [20], developed with a multidisciplinary approach. The protocol has been described previously [20]. In 2007, participants were randomly recruited from the reimbursement database of the unique French Farmer Health Insurance System (Mutualité Sociale Agricole). Out of 2193 eligible individuals, 1002 retired farmers aged 65 years or older, with at least 20 years of agricultural activity and living in rural areas, agreed to participate and were included in the study. Data were collected during face-to-face interviews at the participants’ home by trained neuropsychologists and nurses, with the contribution of geriatricians for the diagnosis of neurocognitive disorders. These data included sociodemographic factors, lifestyle, data related to living environment and health conditions. Participants also underwent a battery of neuropsychological tests and completed a standardized self-administered questionnaire. The present study is a secondary analysis of data collected at baseline in 2007, which serves as the reference time point. No additional data collection was carried out specifically for this study. Follow-up assessments were conducted every 2–3 years using the same data collection procedures. This research and all methods were performed in accordance with the relevant guidelines and regulations embodied in the Declaration of Helsinki. The cohort was approved by the Ethics Review Board “Comité de Protection des Personnes Sud-Ouest Outre-Mer (Southwest and overseas individuals protection committee)” (IRB: 2006-A00595-46) and all participants gave written informed consent.

**Measures**

**Factors constitutive of the FA construct**

To capture the multidimensionality of FA, we considered the broadest possible range of variables collected at baseline. Only variables with no missing data were retained for analysis. As a result, only participants with complete
data for all selected variables were included, yielding an analytical sample of 587 participants out of the 1002 initially enrolled in the study. In total, 30 variables were retained, related to both IC (cognition, locomotion, psychology, vitality, sensory) and environments (social connection, material environment, care and support from professionals and family). In the analysis, each variable was coded such that a good situation/condition was indicated by a higher score. The measurement of each variable is detailed in eTable S1.

## Covariates

The following covariates were used to describe the sample: age; sex (male/female); marital status (partnered, non-partnered); education level (high, if the participant has obtained at least the Certificat d'Etude Primaire diploma - equivalent to 7 years of primary school, otherwise low), income (high, medium, and low).

## Outcomes

Four health endpoints were studied:

* Time to death: Vital status with the exact date of death was regularly updated over the eight years of follow-up.

* Time to incident disability. Disability was defined at each visit using the Lawton's scale [21] to assess the individual's capacity to: use the telephone, do the shopping, use transportation, handle medications, manage finances, prepare meals, do laundry and, housekeeping. Limitation in the execution of at least one of these eight activities was considered as disability in Instrumental Activities of Daily Living (IADL), otherwise participant was considered as without disability.

* Time to experience poor life satisfaction. Life satisfaction was defined at each visit using the following question: Are you overall satisfied with your current life? The response scale ranged from 1 (not at all) to 7 (very satisfied). Answers 1 to 4 defined poor life satisfaction and otherwise they defined good satisfaction. The time to first change from good to poor life satisfaction was considered.

* Time to experience bad perceived health. Perceived health was defined at each visit using the following question: Do you consider your health as being: Very good; Good; Medium; Poor; Very poor? The participants who responded "good", or "very good" were classified in good perceived health, otherwise they were classified in poor perceived health. The time to first change from good to poor perceived health was considered.

## Statistical analysis

### Development of the FA construct

FA construct was defined from the 30 variables using a 4-step procedure (Fig. 1). First, we defined 5 IC and 3 environment subdomains using a reflective approach. Based on previously published evidence on the items constituting the subdomains of the IC construct [9–12], we classified the selected factors into the most appropriate subdomains. For the environment subdomains, we gathered factors that might share a common construct. Subsequently, Confirmatory Factor Analyses (CFA) through Structural Equation Modeling (SEM) models were performed to confirm that the observed variables composing each latent subdomain (e.g., cognition, locomotion, social connections, etc.) provided a good characterization of it. Since some variables were ordinal, we used the Diagonally Weighted Least Square (DWLS) estimator as it makes no distributional assumptions on the observed variables [22, 23]. The fitted-quality of the SEM models was assessed based on the usual parameters: Comparative Fit Index; Tucker-Lewis Index; Value of the Root Mean Square Error of Approximation; and the Value of the Standardized Root Mean Square Residual [24].

In the third step, given our limited sample size to run a second-order factor model to create the global constructs of IC and environment, a latent score of each subdomain (first-order latent variable) was derived and transformed into a z-score. A higher score indicated a better subdomain level. In the absence of a valid alternative approach in the literature to create the IC and environment global constructs, they were defined as the mean score of its constituting subdomain z-scores. Then, we categorized these two construct scores into three groups (low, medium, high) based on the distribution tertiles cutoffs.

Finally, we combined the IC and environment categorized variables to create the FA variable (Fig. 1). We assumed that a high IC did not necessarily require a compensatory environment and therefore considered that a high IC corresponded to a high FA. As result, we sought to explore (as highlighted by the concept of FA) the potential compensation of an altered IC by the environment. For this purpose, FA was arbitrarily defined in four groups as follows: very high FA (high IC); high FA (medium/low IC, with high quality of environment); medium FA (medium/low IC, with medium environment); and low FA (medium/low IC, with low environment) (eTable S2).

Covariates and the subdomain scores were described and compared according to the FA levels using Chi-square or Fisher's tests for categorical variables and Kruskal-Wallis test for quantitative variables. In addition, to assess potential selection bias due to missing data, baseline characteristics of participants included in the
<figure><img src="image_3.png" /></figure>

Legend: reflective measurement - in black and formative measurement - in blue

<caption>**Fig. 1** Individual, one-factor model defining each subdomain</caption>
analysis were compared with those excluded using Chi-square test for categorical variables and Wilcoxon rank-sum test for continuous variable.

### Risk of adverse outcomes according to the initial level of FA

We investigated the association between the four-grades of FA construct and the occurrence of four adverse outcomes over the eight years of follow-up through Cox proportional hazards models, adjusted for age and sex. For each outcome, except death, prevalent cases were excluded. In a sensitivity analysis, associations were re-examined using the nine groups formed by crossing IC and environment tertile groups, resulting in a 3 × 3 matrix (eTable S2). Each group was labeled L1 to L9, with labels reflecting specific combinations (e.g., L1 = high IC and high environment; L9 = low IC and low environment). For each outcome, the Akaike Information Criterion (AIC) of the models (FA in four levels vs. FA with nine levels) were compared to check whether they were similar. Due to the low number of incident cases, this sensitivity analysis was not carried out for the “perceived health” outcome. Hazard Ratio (HR) values, 95% Confidence Intervals (CI) and p-values (a value < 0.05 was considered as significant) were reported. All analyses were performed using R (version 4.1.2) and the main packages used were Lavaan (version 0.6–11) and Survival (version 3.2–13) [25, 26].

## Results

### Sample description

Compared to the 415 participants excluded due to missing data, the 587 included participants were younger (median age: 74.5 vs. 77.4 years), reported less frequently poor perceived health (8.7% vs. 11.2%), and poor life satisfaction (18.2% vs. 28.2%). They were more frequently

<table><caption>**Table 1** Description and comparison of baseline characteristics of included and excluded participants</caption><thead><tr><th>Characteristics</th><th>Participants included (n=587)</th><th>Participants excluded (n=415)</th><th>p-value</th></tr></thead><tbody><tr><td>Age (in years, median [Q1 - Q3])</td><td>74.51 [70.10-79.34]</td><td>77.42 [72.01-83.17]</td><td>&lt;0.001</td></tr><tr><td>Older age (≥ 75 years), n (%)</td><td>276 (47.00)</td><td>262 (63.10)</td><td>&lt;0.001</td></tr><tr><td>Male sex, n (%)</td><td>367 (62.50)</td><td>259 (62.40)</td><td>0.971</td></tr><tr><td>Educational level (Higher level: &gt;CEP)</td><td>124 (21.10)</td><td>44 (10.70)</td><td>&lt;0.001</td></tr><tr><td>Marital status (Partnered), n (%)</td><td>433 (73.8)</td><td>242 (59.00)</td><td>&lt;0.001</td></tr><tr><td>Income levels</td><td></td><td></td><td>&lt;0.001</td></tr><tr><td>High, n (%)</td><td>146 (25.80)</td><td>53 (15.00)</td><td></td></tr><tr><td>Medium, n (%)</td><td>306 (54.10)</td><td>210 (59.30)</td><td></td></tr><tr><td>Low, n (%)</td><td>114 (20.10)</td><td>91 (25.70)</td><td></td></tr><tr><td>Poor perceived health, n (%)</td><td>51 (8.7)</td><td>43 (11.2)</td><td>0.199</td></tr><tr><td>Poor life satisfaction, n (%)</td><td>106 (18.2)</td><td>94 (28.2)</td><td>&lt;0.001</td></tr></tbody></table>

living with a partner (73.8% vs. 59.0%) and had higher income (25.8% vs. 15.0%) at baseline (Table 1).

### Construction of the FA measure

Overall, the 30 variables considered were significantly associated with the latent subdomain they measured (eTable S3 in the Supplement). The CFA confirmed that the observed variables composing each latent subdomain provided a good characterization of it and all models adequately fitted the data (eTable S4).

### Description and comparison of participants' characteristics according to FA levels

Table 2 reports the participants' characteristics and FA subdomains according to the four-grade FA construct, all based on baseline data. Participants with very high FA were more likely to be male, younger, living with a partner and to have a good perceived health and good life satisfaction compared to their counterparts. Regarding distributions of the subdomain scores, overall, the higher the latent subdomain scores, the better the FA levels (Table 2).

### Risks of adverse outcomes associated to the four-grade FA measure

Whatever the negative outcome considered, the persons with the lowest levels of FA had the highest risks (Table 3). Compared to participants with very high FA (taken as reference), those with low FA had a significantly higher risk of death (HR = 2.19 [95% CI: 1.30–3.68]). This risk was also higher among participants with medium and high levels, but it was not statistically significant. Groups with low, median, and high FA levels were two to three times more likely to exhibit IADL disability than individuals with a very high FA level. For subjective indicators, compared with the reference group, the risk of reporting a poor perceived health during the follow up was significantly higher in the low FA group (HR = 3.97 [95% CI: 1.85–8.53]), close to significance in the medium FA group (HR = 2.15, *p* = 0.063), but not different in the high FA group (*p* = 0.706). Finally, all the groups had an increased risk of loss of life satisfaction compared with the reference group, but the association was only significant in the low FA group (HR = 1.87 [95% CI: 1.15–3.03]); it was close to significance in the medium (HR = 1.55 [95% CI: 0.97–2.48]) and the high groups (HR = 1.48 [95% CI: 0.89–2.45]) (Table 3).

Sensitivity analyses (analyzing the 9-grade FA indicator) led to similar conclusions, and the AICs (main model vs. sensitivity model) were very close for each outcome. Indeed, compared to participants with both high levels of IC and environment, those with low levels of IC combined with a degraded environment had the significantly highest risk of experiencing the adverse outcomes
<table><caption>**Table 2** Description and comparison of participant's characteristics at baseline and functional ability (FA) subdomains according to global FA levels</caption><thead><tr><th rowspan="2">Variables</th><th colspan="4">FA levels</th><th rowspan="2">p value</th></tr><tr><th colspan="4">n (%)/mean (min; max)</th></tr><tr><th></th><th>Very High (n=200)</th><th>High (n=96)</th><th>Medium (n=127)</th><th>Low (n=164)</th><th></th></tr></thead><tbody><tr><td>Age (in years, median [Q1 - Q3])</td><td>71.89 [68.53-76.15]</td><td>73.13 [69.43-77.09]</td><td>74.12 [70.44-79.03]</td><td>79.32 [74.61-82.88]</td><td>&lt;0.001</td></tr><tr><td>Older age (≥ 75 years) n (%)</td><td>64 (32.00)</td><td>33 (34.40)</td><td>57 (44.90)</td><td>122 (74.40)</td><td>&lt;0.001</td></tr><tr><td>Sex (Male) n (%)</td><td>140 (70.00)</td><td>58 (60.40)</td><td>84 (66.10)</td><td>79 (48.20)</td><td>0.003</td></tr><tr><td>Educational level (Higher level: ≥ CEP) n (%)</td><td>75 (37.50)</td><td>16 (16.70)</td><td>21 (16.50)</td><td>12 (7.30)</td><td>&lt;0.001</td></tr><tr><td>Marital status (Partnered) n (%)</td><td>166 (83.00)</td><td>79 (82.30)</td><td>101 (79.50)</td><td>87 (53.00)</td><td>&lt;0.001</td></tr><tr><td><em>Income</em></td><td></td><td></td><td></td><td></td><td>&lt;0.001</td></tr><tr><td>High n (%)</td><td>79 (40.10)</td><td>23 (25.60)</td><td>32 (25.40)</td><td>12 (7.80)</td><td></td></tr><tr><td>Medium n (%)</td><td>90 (45.70)</td><td>48 (53.30)</td><td>65 (51.60)</td><td>103 (67.30)</td><td></td></tr><tr><td>Low n (%)</td><td>28 (14.20)</td><td>19 (21.10)</td><td>29 (23.00)</td><td>38 (24.80)</td><td></td></tr><tr><td>Poor perceived health n (%)</td><td>5 (2.50)</td><td>5 (5.20)</td><td>14 (11.00)</td><td>27 (16.60)</td><td>&lt;0.001</td></tr><tr><td>Poor life satisfaction n (%)</td><td>21 (10.50)</td><td>14 (14.70)</td><td>25 (19.80)</td><td>46 (28.60)</td><td>&lt;0.001</td></tr><tr><td><em>Functional capacities in daily living</em></td><td></td><td></td><td></td><td></td><td>&lt;0.001</td></tr><tr><td>Full capacities n (%)</td><td>137 (69.90)</td><td>53 (56.40)</td><td>37 (30.60)</td><td>16 (9.90)</td><td></td></tr><tr><td>Good capacities n (%)</td><td>56 (28.60)</td><td>41 (43.60)</td><td>77 (63.60)</td><td>84 (52.20)</td><td></td></tr><tr><td>Medium capacities n (%)</td><td>3 (1.50)</td><td>0 (0.00)</td><td>7 (5.80)</td><td>54 (33.50)</td><td></td></tr><tr><td>Poor capacities n (%)</td><td>0 (0.00)</td><td>0 (0.00)</td><td>0 (0.00)</td><td>7 (4.3)</td><td></td></tr><tr><td><em>Intrinsic capacity</em></td><td></td><td></td><td></td><td></td><td>&lt;0.001</td></tr><tr><td>High n (%)</td><td>200 (100.0)</td><td>0 (0.0)</td><td>0 (0.0)</td><td>0 (0.0)</td><td></td></tr><tr><td>Medium n (%)</td><td>0 (0.0)</td><td>71 (74.00)</td><td>78 (61.40)</td><td>43 (26.20)</td><td></td></tr><tr><td>Low n (%)</td><td>0 (0.0)</td><td>25 (26.00)</td><td>49 (38.60)</td><td>121 (73.80)</td><td></td></tr><tr><td><em>Environment</em></td><td></td><td></td><td></td><td></td><td>&lt;0.001</td></tr><tr><td>High n (%)</td><td>95 (47.50)</td><td>96 (100.00)</td><td>0 (0.0)</td><td>0 (0.00)</td><td></td></tr><tr><td>Medium n (%)</td><td>74 (37.00)</td><td>0 (0.00)</td><td>127 (100.00)</td><td>0 (0.00)</td><td></td></tr><tr><td>Low n (%)</td><td>31 (15.50)</td><td>0 (0.00)</td><td>0 (0.00)</td><td>164 (100.0)</td><td></td></tr><tr><td><em>FA subdomains</em></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Cognition<sup>§</sup></td><td>0.69 (-1.34; 1.68)</td><td>0.11 (-3.07; 1.41)</td><td>0.01 (-2.17; 1.70)</td><td>-0.38 (-4.09; 1.30)</td><td>&lt;0.001</td></tr><tr><td>Locomotion<sup>§</sup></td><td>0.60 (-1.03; 0.60)</td><td>0.60 (-1.75; 0.60)</td><td>0.60 (-2.45; 0.60)</td><td>-0.71 (-1.64; 0.60)</td><td>&lt;0.001</td></tr><tr><td>Pyschology<sup>§</sup></td><td>0.55 (-1.79; 0.66)</td><td>0.52 (-3.48; 0.66)</td><td>0.24 (-4.50; 0.66)</td><td>0.08 (-4.96; 0.38)</td><td>&lt;0.001</td></tr><tr><td>Vitality<sup>§</sup></td><td>0.58 (-1.59; 2.25)</td><td>-0.39 (-6.72; 1.30)</td><td>-0.34 (-2.70; 1.83)</td><td>-0.09 (-4.16; 2.13)</td><td>&lt;0.001</td></tr><tr><td>Sensory<sup>§</sup></td><td>1.24 (-1.56; 1.24)</td><td>-0.39 (-2.65; 1.24)</td><td>-0.57 (-1.99; 0.56)</td><td>-0.59 (-2.65; 1.24)</td><td>&lt;0.001</td></tr><tr><td>Social connection- Lifestyle<sup>§</sup></td><td>0.28 (-2.61; 2.37)</td><td>0.77 (-0.38; 2.08)</td><td>0.12 (-1.36; 2.08)</td><td>-0.77 (-2.86; 1.96)</td><td>&lt;0.001</td></tr><tr><td>Material<sup>§</sup></td><td>0.51 (-2.39; 0.51)</td><td>0.51 (-1.40; 0.51)</td><td>0.51 (-2.38; 0.51)</td><td>-1.40 (-3.00; 0.51)</td><td>&lt;0.001</td></tr><tr><td>Socio-medical support<sup>§</sup></td><td>0.37 (-1.92; 1.12)</td><td>0.12 (-0.48; 1.12)</td><td>0.08 (-2.34; 1.12)</td><td>-0.48 (-3.03; 1.12)</td><td>&lt;0.001</td></tr></tbody></table>

CEP(Certificat d'Etudes Primaires (French primary school diploma corresponding to around 7 years of schooling); §standardized score

examined. In addition, when the IC was good, degraded environments had no effect on objective outcomes, but only on the subjective one. (eFig S1)

Discussion

While aging in optimal conditions has progressively become a major societal issue to face the accelerated aging of world population, it is unclear how this entity can be measured and studied. The current study expands the evidence of the WHO conceptual framework of healthy aging through the multidimensional measure of FA. Thanks to a broad range of variables relative to the two pillars of the WHO framework, IC, and environment, we developed an integrative approach of healthy aging. Indeed, beyond the well-known IC that a person

can draw on in daily life, we also considered their living environment which could constitute promising and concrete levers of action to foster healthy aging when IC worsens. To explore the predictive relevance of such a construct, we explored the relation between our FA measure with subsequent objective and subjective negative outcomes. Lower levels of FA were significantly associated with higher risks of death, disability, poor perceived health, and loss of life satisfaction.

There is a growing evidence on the IC components [9–11, 14, 27, 28], but components that may contribute to define FA/healthy aging are not well established yet and various factors are reported in the literature [5, 18, 19, 29, 30]. A recent systematic review identified that the components of healthy aging mostly explored
<table><caption>**Table 3** Associations between the functional ability levels and negative outcomes</caption><thead><tr><th>FA Levels</th><th>Total<sup>#</sup></th><th>Number of events recorded</th><th>Adjusted HR<sup>+</sup> [95% CI]</th><th>p value of Wald test</th></tr></thead><tbody><tr><td><strong>Incident death</strong></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>n = 586</td><td>n = 122 (%*)</td><td></td><td></td></tr><tr><td>Low</td><td>163</td><td>60 (38.8)</td><td>2.19 [1.30–3.68]</td><td>0.003</td></tr><tr><td>Medium</td><td>127</td><td>23 (18.1)</td><td>1.42 [0.79–2.57]</td><td>0.239</td></tr><tr><td>High</td><td>96</td><td>17 (17.7)</td><td>1.76 [0.93–3.33]</td><td>0.080</td></tr><tr><td>Very High</td><td>200</td><td>22 (11.0)</td><td>1</td><td></td></tr><tr><td><strong>Subsequent IADL-disability</strong></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>n = 463</td><td>n = 158 (%)</td><td></td><td></td></tr><tr><td>Low</td><td>83</td><td>48 (57.8)</td><td>3.13 [1.99–4.92]</td><td>&lt;0.001</td></tr><tr><td>Medium</td><td>105</td><td>43 (41.0)</td><td>2.12 [1.35–3.33]</td><td>0.001</td></tr><tr><td>High</td><td>88</td><td>31 (35.2)</td><td>2.07 [1.27–3.37]</td><td>0.003</td></tr><tr><td>Very High</td><td>187</td><td>36 (19.3)</td><td>1</td><td></td></tr><tr><td><strong>Subsequent poor perceived health</strong></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>n = 484</td><td>n = 52 (%)</td><td></td><td></td></tr><tr><td>Low</td><td>109</td><td>24 (22.0)</td><td>3.97 [1.85–8.53]</td><td>&lt;0.001</td></tr><tr><td>Medium</td><td>102</td><td>13 (12.7)</td><td>2.15 [0.96–4.84]</td><td>0.063</td></tr><tr><td>High</td><td>85</td><td>4 (4.7)</td><td>0.80 [0.25–2.53]</td><td>0.706</td></tr><tr><td>Very High</td><td>188</td><td>11 (5.9)</td><td>1</td><td></td></tr><tr><td><strong>Subsequent poor life satisfaction</strong></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>n = 426</td><td>n = 135 (%)</td><td></td><td></td></tr><tr><td>Low</td><td>89</td><td>38 (42.7)</td><td>1.87 [1.15–3.03]</td><td>0.011</td></tr><tr><td>Medium</td><td>91</td><td>33 (36.3)</td><td>1.55 [0.97–2.48]</td><td>0.070</td></tr><tr><td>High</td><td>74</td><td>25 (33.8)</td><td>1.48 [0.89–2.45]</td><td>0.129</td></tr><tr><td>Very High</td><td>172</td><td>39 (22.7)</td><td>1</td><td></td></tr></tbody></table>

were related to physical (diet, physical activity), mental/ cognitive (outlook/attitude, faith, self-awareness) and social environment (financial security, social support) factors [29]. Other factors have also been considered such as sensory factors (vision, hearing), cognition (e.g., numeracy, orientation in time), mobility (e.g., getting up, climbing, walking), capacities in daily living (e.g., dressing, cooking, managing medications, etc.), and mental health (e.g., loneliness, hopefulness, depression) [18]. Whilst our analyses confirmed the role of most of these factors, our FA indicator includes more in-depth characteristics of the individual's environment (e.g., availability of a car, frequency of visits to the General Practitioner, professional and family caregiver support, etc.). The present study provides additional insight on how the environment may compensate or exacerbate the IC deterioration and contribute to the construct of FA and thereby on healthy aging issue.

Only few studies have explored FA/healthy aging according to the theoretical framework proposed by the WHO by studying simultaneously the two pillars (IC and environment) [17–19]. Beyond the difficulties met

due to the large panel of data necessary to construct the FA measure, it is also important to note that there is still no consensus on the methodological approaches to be used to define FA/healthy aging [2, 3, 17–19, 30]. For example, in a study performed by Rivadeneira et al., the multidimensional model of healthy aging was designed by using six subdomains of IC (physical, mental, cognitive, and psychological indicators) and two domains relative to living environment (included social and political environment). In their study, the authors defined two a priori theoretical healthy and less healthy groups based on presence/absence of adverse conditions and poor living environment [17]. Although this binary approach has the advantage of being less methodologically complex, it appears to be limited in exploring the contribution of the living environment to the FA levels. Indeed, an identification of individuals with impaired IC but good environment (compensatory scenario), and those with both altered IC and unfavorable environment (exacerbation scenario) as we propose may be a more relevant approach in research work to better understand the complex and critical role of environmental factors in FA.

## Predictive value of FA

As reported in previous studies, we found that the lower FA levels were associated with mortality (up to twofold higher risk of death compared to the high FA level). Gao et al. had reached the similar conclusion in China with younger (44% were aged < 60 years) and less educated participants (45% had not reached elementary school) than ours [18]. They found that the death risk was significantly lower (HR = 0.51 [95%CI: 0.31–0.86]) among individuals with higher level of FA compared to those with low FA level. It is well established that reduced components of IC and/or poor living environment (e.g., lack of social support, loneliness, poor/difficult access to healthcare) increased all-cause mortality [15, 16, 27, 31–33], but these results did not combine factors related to both IC and living environment. Unlike us and Gao et al., Lee et al. recently reported that FA was less predictive of mortality (HR = 1.53 [95%CI: 1.00–2.33]) [34]. Their FA indicator was measured by the Functional Autonomy Measurement System (SMAF), which assesses basic and IADL, communication, and mental functions [34]. These slight discrepancies in the conclusions between studies highlight once again that the components and approach used to define FA are critical to its capacity to predict health outcomes. More research addressing the complex issues of operationalization of the measures is needed. Our study also shows that lower levels of FA were associated with disability. Several previous studies have shown that lower IC increased the risk of IADL-disability [10, 11, 15, 16]. However, since our FA indicator goes beyond the IC, our results seem to confirm that a poor environment

<footnote>*Adjusted for age at baseline, and sex; \*Percentages of incident cases are presented by row. \#For each analysis, the reported sample size indicates participants with complete data/observations on all variables included in the Cox model</footnote>
exacerbated individuals' limitation to stay active, and mobile. Contrary to our expectations, we observed in our sample that when IC was low, a better environment had no compensatory role in the relationship between low levels of FA and the occurrence of disability (also for death). Further research modeling the evolution of the two pillars of FA may be the best approach to clarifying the compensatory/exacerbating hypothesis of the living environment in the case of IC decline.

Interestingly our results also confirmed the predictive value of our FA measure on subjective negative outcomes (i.e., perceived health and life satisfaction), confirming that healthy aging goes beyond the biomedical factors and refers to well-being, as suggested by the WHO in its conceptual framework. An important result worth highlighting is that, unlike the results observed for objective outcomes, the environment had a certain influence on subjective ones. Indeed, we observed that among participants with a high level of IC, a degraded environment contributed to an increased risk of reporting poor perceived health and life satisfaction. In this study, overall, participants with low FA but also intermediate levels (in a lesser extent) were significantly more likely to experience bad perceived health and poor life satisfaction. Consistently with our findings, Gao et al. also observed that a low FA score was significantly associated with poorer short-term self-rated health [18]. Another study in the Philippines conducted in 2 316 individuals aged 50 years and over reported that having good FA was positively and significantly associated with good subjective well-being (defined using information on quality of life and life satisfaction) [19]. Several works have previously demonstrated that impairments in domains that contributed to define our FA, such as physical status [35, 36], cognition [37, 38], and social support [39, 40], are associated with worsening well-being. By combining all these domains into a single entity, our results reinforce the hypothesis that FA is a valid predictor of well-being in old age. Although our study primarily focused on measuring FA and its predictive role in adverse health outcomes, it is important to note that, actions and initiatives promoting healthy aging, such as those mentioned in United Nations Decade of Healthy Ageing (2021–2030) or The European Innovation Partnership on Active and Healthy Aging, could have a real impact in enabling older adults to continue doing the things that matter to them and in fostering well-being in aging [41–43]. A healthy lifestyle, including balanced nutrition, regular physical activity, sustained social participation after retirement, adapted housing, and feeling supported by close relatives, can enhance FA and reduce the risk of functional decline [44]. These aspects align with the strategic priorities defined by international frameworks aimed at supporting autonomy and quality of life in later years.

## Limitations and strengths

The main limitation of this study is the non-representativeness of the sample. Indeed, the AMI participants were retired farmers living in rural area and the participants included in the analyses were younger and healthier than the excluded ones. Second, our small sample size may also explain the fact that we did not reach statistical significance in intermediate levels of FA (medium and high) for some of the outcomes explored despite the high risks observed in these groups. Third, although we analyzed a wide range of variables to have an integrative measure of FA, some potentially relevant data could not be explored, such as leisure activities, distance to healthcare providers, accessibility of grocery stores, availability of services, or participants' attitudes and beliefs that may have an important contribution to FA as previously published [5, 7, 8]. Finally, in this study, we did not use a global FA score (combining the IC and environment scores), preferring a qualitative FA index to classify people according to different profiles. A global FA score does not allow to highlight the specificities and possible compensatory effects of the environment. Indeed, as illustrated in eTable S5, the same global FA score can be obtained from very contrasting IC and environment profiles. This could hide the specificities of the FA profiles, and the risks associated with them.

Despite these limitations the current investigation has several strengths. This research is among the rare epidemiological studies exploring FA through a real multidimensional approach. Exploring jointly IC and environment, our study confirmed the importance of these two pillars of FA for assessing healthy aging and understanding the offsetting and exacerbating effect of environment in FA. The use of SEM analyses to obtain latent scores allowed us to rule out the constraint on which individual weights should be used for each variable selected to create the single construct for our subdomains. Although we did not validate the construct of our subdomains in separate samples, all our models had a very good fit performance. In addition, most of the factors identified are quite easy to assess. Finally, thanks to longitudinal data, we could also show that FA predicted well the occurrence of objective and subjective negative outcomes.

## Conclusion

Although this study did not aim to validate the theoretical concept of FA as the WHO proposed, our findings support the relevance of the two pillars of FA that are IC and living environments. Indeed, low level of FA (copresence of altered IC and poor environment) increased the risks of all the adverse outcomes, whatever subjective and objective confirming that healthy aging is not only about health but also well-being. Given these results, in
addition to clinical actions targeting IC, environment may be an avenue for public policies in the perspective of improving FA, thereby supporting healthy aging. Such a view is consistent with the person-centered approach of healthy aging consisting in holistic care of the person where care and services are aligned with the individual's needs and priorities. Further research conducted in other populations from various geographic areas is needed to first increase the evidence on the components of FA construct considering cultural, organizational, personal perspectives differences and then to better understand the contributions of each of them to healthy aging. In a longer term, such research could lead to benefits in clinical practice to routinely follow common and operational healthy aging criteria to early detect alert signs and propose appropriate holistic intervention.

### Abbreviations

AMI Aging Multidisciplinary Investigation

CFA Confirmatory Factor Analyses

CI Confidence Intervals

DWLS Diagonally Weighted Least Square

FA Functional Ability

HR Hazard Ratio

IC Intrinsic Capacity

IADL Instrumental Activities of Daily Living

SEM Structural Equation Modeling

WHO World Health Organization

### Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12877-025-06328-3.

Supplementary Material 1

### Acknowledgements

We would like to thank Céline Meillon for her advice on the data curation process.

### Author contributions

AG: conceptualization, methodology, data curation, formal analysis, data visualization, interpretation, validation, and writing the original draft. CPL: methodology, data visualization, interpretation, validation, draft reviewing, and editing.LL: interpretation, validation, draft reviewing, and editing.HA: interpretation, validation, draft reviewing, and editing.KP: conceptualization, methodology, data visualization, interpretation, validation, project administration, funding acquisition, supervision, draft reviewing, and editing. AG and KP accessed and verified the data.Final approval of the version to be published: All authors.

### Funding

The AMI project was supported by AGRICA (CAMARCA, CRCCA, CCPMA PREVOYANCE, CPCEA, AGRI PREVOYANCE), la Mutualité Sociale Agricole (MSA) de Gironde, la Caisse Centrale de la Mutualité Sociale Agricole (CCMSA). Healthy aging research was funded by the Region Nouvelle Aquitaine (AAPR2021-232020-11814310), Malakoff Humanis and CARSAT Aquitaine. The funders had no role in study design, data collection, statistical analysis, interpretation of the data. There also had no role in preparation and publication of the manuscript.

### Data availability

Data cannot be made publicly available because there are still ongoing scientific valorization. Nevertheless, the datasets generated and analyzed

during the study may be made available upon reasonable request to the corresponding author.

### Declarations

#### Ethics approval and consent to participate

The AMI cohort was approved by the Ethics Review Board "Comité de Protection des Personnes Sud-Ouest Outre-Mer (Southwest and Overseas Individuals Protection Committee)" (IRB: 2006-A00595-46) and all participants gave written informed consent. All methods were performed in accordance with the relevant guidelines and regulations embodied in the Declaration of Helsinki.

#### Consent for publication

Not applicable.

#### Competing interests

The authors declare no competing interests.

Received: 26 June 2023 / Accepted: 22 July 2025

Published online: 26 September 2025

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