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SOCIAL VULNERABILITY PREDICTS FRAILTY: TOWARDS A DISTINCTION BETWEEN FRAGILITY AND FRAILTY?

 

H. Amieva1, C. Ouvrard-Brouillou1, J.-F. Dartigues1, K. Pérès1, M. Tabue Teguo1,2, A. Avila-Funes1,3

 

1. Univ. Bordeaux, Inserm, Bordeaux Population Health Research Center, team Psychoepidemiology of aging and chronic diseases, UMR 1219, Bordeaux, France; 2. Department of Geriatrics, University Hospital of Guadeloupe, Pointe-à-Pitre, France; 3. Department of Geriatric Medicine, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico.

Corresponding Author: Hélène Amieva, Inserm, Bordeaux Population Health Research Center, team Psychoepidemiology of aging and chronic diseases, UMR 1219, University of Bordeaux, 146 Rue Léo Saignat, 33076 Bordeaux cedex, France, Helene.Amieva@u-bordeaux.fr

J Frailty Aging 2022;in press
Published online March 24, 2022, http://dx.doi.org/10.14283/jfa.2022.24

 


Abstract

Background: All definitions of frailty converge in two aspects: the notion of loss or decline and the ability to predict negative health outcomes. Numerous factors were reported to be associated with frailty among which biological, psychological, economic and social factors. Whether the latter contribute at the same level is a relevant question, as social vulnerability does not refer to an ongoing process of decline leading a person to become frail but rather to a relativity stable state making the person fragile. Thus, social vulnerability should increase the risk of frailty.
Objectives: This study aims at assessing whether social vulnerability increases the risk of incident frailty.
Methods: 1531 participants aged 65 or older from the PAQUID cohort study were included. Cox regression models tested the association between social vulnerability index (SVI, based on 28 social items) and frailty index (FI, based on 25 health-related items) over the 27 years of follow-up.
Results: Adjusted for age and sex, higher SVI was associated with increased risk of incident frailty (HR=3.85, 95% CI=1.87–7.94, p<.001). After additional control for IADL disability and comorbidities, higher SVI was associated with increased risk of frailty (HR=3.40, 95% CI=1.63–7.07, p<.05). The association remained significant after controlling for MMSE (HR=2.34, 95% CI=1.08–5.07, p<.05).
Discussion: Poor social status is a risk factor of frailty. From a conceptual point of view, our results claim for a distinction between the concepts of frailty and fragility, the first one being the consequence of an ongoing decline, the other one related to a relatively stable condition of fragility, mainly explained by unfavorable social conditions.

Key words: Social vulnerability index, frailty index, cohort studies.


 

Introduction

Whatever the conceptual view, frailty is defined as a decline in physical reserve across multiple physiological systems entailing diminished resistance to stressors. Several definitions of frailty have been proposed among which Fried’s phenotype (1-2), Rockwood’s cumulative decline model (3-5), or Gobbens et al’s multidimensional definition (6). Those definitions present important differences in the way frailty is conceptualized, some exclusively considering physical components (1-2, 7), others involving both physical and psychosocial markers (6), while others consider frailty as a cumulative decline in many physiological systems and thus, the resultant of diseases, disabilities, and deficits accumulation (3-5). Nonetheless, despite such differences, all models converge in two aspects; i) they define frailty with respect to the notion of loss or decline and ii) with respect to its ability to predict negative health outcomes.
Numerous factors have been reported to be associated with frailty. It would be difficult and out of the objective if this article to do an exhaustive list of these factors, but it may be relevant to draw a picture of the diversity of such reported associated conditions. One of the first factors reported was sarcopenia (8-9). From then, a wide range of biological factors have been evidenced among which cardiovascular factors, such as smoking status, alcohol intake, cholesterol, systolic and diastolic blood pressure, body mass index, prior cardiovascular disease (10-13), reduced carotid intima-media thickness (14) or cerebrovascular damage such as loss of white matter integrity (15). Infectious factors have also been related to frailty as for example, biomarkers of the immune-endocrine axis such as level of white cell counts (16).
A variety of factors related to psychological health status has also been frequently reported as correlates of frailty. Those factors include cognitive functioning (10-11, 17), depressive symptoms (10, 13, 17) and anxiety (19) known to be more frequently encountered in frail elderly population as compared to non frail population, or associated to more negative outcomes in frail older adults. Other psychological outcomes like self-esteem (20), quality of life (21-22), psychological well-being (23) or perceived self-efficacy (10) have also been shown to be frequently associated with frailty.
Finally, another category of factors that have been suspected to contribute to frailty syndrome are sociodemographic and psychosocial factors such as level of education (10, 13), socioeconomic status (24-25), income (10,13), geographical deprivation (17, 25), living situation (13) and loneliness (26-28).
Regarding the latter factors, i.e. psychosocial factors, the evidence for their contribution to frailty has two major implications. On the one hand, it strengthens the conceptions of frailty which define it as a multifactorial concept by considering not only physical aspects but also the psychological and social sources of frailty, thereby providing a more holistic and integrated view of the frailty concept. On the other hand, the counterpart of it is that the long list of associated factors may add a certain confusion to the frailty concept. Indeed, making the inventory of factors associated to frailty without attempting to understand at what level they may act, does not help better understanding the essence of frailty. Rather, it contributes to see frailty as an umbrella concept where all types of weaknesses in older adults appear as a potential component of frailty. Instead, one should wonder whether all the many variables associated with unfavorable health trajectories in older adults constitute real risk factors of frailty, or, whether they are markers of an ongoing decline leading to frailty.
The question is particularly relevant for social factors. Social vulnerability is defined as the accumulation of multiple and varied social problems and represents a risk factor both for poor health outcomes and poor health care provision and planning (29). An elderly person with low social resources may experience an increased risk of adverse health events, not due to an already established decline process (as frailty is essentially defined), but because he/she does not have enough support to overcome significant adverse life events if they occur. For instance, an elderly person living alone, in a rural area, with poor family and social network and limited income who experiences a fall will undoubtedly have a more challenging recovery due to less access to care, lack of informal temporary help when returning home after hospitalization, as well as lack of psychological reassurance to overcome the fear of falling again, frequently encountered in the post-fall syndrome. Altogether, psychosocial conditions will give rise to an unfavorable prognosis (i.e. increased risk of hospitalization, institutionalization, disability and even probably death) even though the person did not meet in the first place any criterion of frailty according to most frailty definitions. Therefore poor social condition does not refer to an ongoing process of decline leading an elderly person to eventually become frail but rather to a relativity stable state making the person fragile.
Consistently, the index of social vulnerability proposed by Andrew et al. (30) has been shown to be associated with mortality independently of frailty status. Such results have been replicated in a different cohort study, confirming the non-overlapping contribution of the social vulnerability and frailty concepts in the prediction of mortality (31). Therefore, fragility (i.e. social vulnerability) and frailty may be close but distinct concepts. It should be relevant to pursue further research and improve our understanding by highlighting that social vulnerability is not solely a factor associated with frailty as many others, rather, it may be a risk factor for frailty. Indeed, even if social vulnerability and frailty are two conditions leading to negative health-related events, social vulnerability is specific to individuals’ living conditions and therefore, precedes frailty. In that context, very little research has been done looking at frailty as an endpoint. Our hypothesis is that social vulnerability should consequently increase the risk of frailty. If so, it would be an additional argument for drawing a clear distinction between these two concepts.
The present study takes advantage of the PAQUID survey, a large population-based study involving a long-term follow-up (27 years) to assess the predictive value of social vulnerability on frailty incidence.

 

Methods

Study population and protocol

The PAQUID study is a French epidemiological study relying on a population-based sample of 3777 community-dwelling individuals aged 65 and over, randomly selected from the electoral rolls in 75 different sites of South-Western France (32). The participants were representative of the community-dwelling older adults of the area in terms of age and sex (33). Participants were evaluated at home at the initial visit (V0) and at 1 (V1), 3 (V3), 5 (V5), 8 (V8), 10 (V10), 13 (V13), 15 (V15), 17 (V17), 20 (V20), 22 (V22), 25 (V25) and 27 (V27) years. At each follow-up visit, tests and scales of cognitive performances, functional abilities, and mental health were administered by trained psychologists. Among the tests, the Mini-Mental State Examination (MMSE) (34) was used as an index of global cognitive function. Disability was scored using the Activities of Daily Living (ADL) (35) and Instrumental ADL (IADL) (36) scales. Information on comorbidities, living conditions, and social network was also collected. The study has received the approval of Ethics Committee of the Bordeaux University Hospital, and participants gave their written informed consent.

Social vulnerability and frailty indices

The social vulnerability index (SVI) was computed at baseline according to previously published methods (30). Twenty-eight self-reported items covering social domains were included as detailed in table 1: socio-economic status, living situation, social support, socially oriented activities of daily living telephone and transports, social engagement, life satisfaction and perceptions, life control. Each item was dichotomized when the social deficit was binary (a score of 0 if a deficit was absent and 1 if it was present), or graded with intermediate values if the social deficit was ordered-response (e.g., 0, 0.5, 1). Any participant with more than 5 missing values in the 28 social deficits considered was excluded from the analysis. The overall score corresponds to the sum of reported deficits divided by the total number of items for which the participant has provided an answer (i.e., 23 to 28). The score ranges from 0 to 1, higher score indicating higher social vulnerability.
The frailty index (FI) was computed at each follow-up visit according to previously published methods (37). Twenty-five to thirty-six self-reported health-related items were considered for each follow-up visit as presented in Table 2, including disability (mobility, IADL, ADL), self-reported pathologies (myocardial infarction, stroke…), diagnosed diseases and measured symptoms (cognition, depression, sensory impairment, hypertension). Each item was dichotomized when the health deficit was binary (0 if a deficit was absent and 1 if it was present), or graded with intermediate values if the health deficit was ordered-response as done previously for the SVI (e.g., 0, 0.5, 1). At each follow-up, the index was calculated if participants had more than 90% available data for the items considered (i.e., exclusion of any participant with more than 3 missing values in the 25 (V3), 26 (V5), 27 (V8 and V10) or 29 health deficits considered (V13 to V27), or more than 4 missing values in the 36 health deficits considered (V0) was excluded from the analysis). The overall score corresponds to the sum of reported deficits divided by the total number of items for which the participant has provided an answer. The score ranges from 0 to 1, higher score indicating higher level of frailty. The cut-off of 0.2 points was used to discriminate the frail and robust participants as stated in the original publication (37).
Both indices have already been validated in the PAQUID cohort (31). As recommended in previous work, no deficits overlapped between the two indices, i.e. the items computing the SVI and FI were mutually exclusive (30).

Covariates

The covariates included IADL limitation (disability is considered if the participant needs assistance for at least one activity) and the sum of comorbidities at baseline including hypertension, myocardial infarction, angor, diabetes, dyspnea, history of stroke, dementia and depression.

Study sample

Among the 3777 participants of the PAQUID cohort, we excluded 464 who had missing data in the FI (baseline or further visits). In order to study the incidence of frailty, we also 1782 participants who were frail at the baseline visit. The study sample consisted of 1531 participants.

Statistical analysis

First, baseline characteristics of participants were described in terms of proportions for categorical variables and in terms of mean and standard deviation for continuous variables. We used linear regression models to test the association between age and SVI, and a T-test to compare SVI between men and women. Comparison between future frail subjects and non-frail were performed using χ² tests and mean comparisons as appropriate. Cox regression models assessing the association between SVI and incidence of frailty (defined by cut-point 0.2) with progressive adjustment have been performed. Model 1 was adjusted for age and sex. Model 2 was additionally adjusted for IADL-disability and comorbidities. Model 3 was additionally adjusted for MMSE score. Results are presented as hazard ratios (HRs) and 95% confidence intervals (95% CIs). All statistical analyses considered a two-tailed P value below 0.05 to be statistically significant and were performed with R software, version 3.3.2.

Table 1. Social Vulnerability Index Items, PAQUID Subsample, n=1531

Table 2. Frailty Index Items collected at each follow-up visit, PAQUID Subsample, n=1531

 

Results

Participants

At baseline, the mean age was 72.38 (SD=5.55) and men accounted for 44.09% of the sample. The mean SVI was 0.32 (SD=0.09). SVI increased with age (p<.05), and men had a lower SVI than women (0.29 vs 0.34, p<.001).

Incidence of frailty

Throughout the 27 years of follow-up, 60.7% of the study sample became frail according to the FI. Table 3 presents the characteristics of the two groups (i.e., future frail older adults vs future non-frail ones). As may be seen, at baseline, future frail participants had higher score in SVI. They also were older, more frequently women and tended to have lower MMSE score compared to the non-frail group.

Table 3. Baseline Characteristics of Participants, PAQUID Subsample, n=1531

Note. SD, Standard deviation; IADL, Instrumental Activities of Daily Life scale; MD, Missing data.

 

Social vulnerability and risk of frailty

Table 4 displays the results of the Cox model assessing the risk of occurrence of frailty associated to social vulnerability, with progressive adjustment for confounders. Adjusted for age and sex, higher SVI was associated with increased risk of frailty (HR=3.85, 95% CIs=1.87–7.94, p<.001), results still significant after further adjustment for disability and comorbidities (HR=3.40, 95% CIs=1.63–7.07, p<.05). Finally, additionally controlling for MMSE score yielded an association that remained statistically significant (HR=2.34, 95% CIs=1.08–5.07, p<.05).

Table 4. Cox Proportional Hazards Model of the Risk of Frailty at 27-Year Follow-Up According to SVI, PAQUID Subsample, n=1531

a. Hazard Ratio. b. 95% Confidence Intervals. c. Social Vulnerability Index. Model 1: n = 1528; adjusted for age and sex. Model 2: n = 1524; adjusted for age, sex, IADL disability and comorbidities. Model 3: n = 1510; adjusted for age, sex, IADL disability, comorbidities and MMSE score.

 

Discussion

Based on a large population-based sample, our study shows that a poor social condition predicts the incidence of frailty in older adults, an association found after controlling for numerous medical factors including frailty level condition at baseline. Our results are consistent with previous studies reporting that social vulnerability and frailty are independent factors of mortality (30-31), and also with more theoretical papers or reviews discussing the role of that social and environmental factors play in predicting the risk of frailty in older adults (29, 38).
Such results lead to two main conclusions; firstly, that a poor social condition and frailty are related but distinct conditions, and secondly, that the former contributes to the latter. In other words, in the long list of factors reported to be associated with frailty, social and living conditions factors, rather than markers of frailty should be considered as risk factors of frailty.
This assertion may have both theoretical and practical implications. From a theoretical point of view, our results showing that social vulnerability predicts frailty claim for a distinction between frailty and what could be called fragility. As previously mentioned, nearly all definitions of frailty encompass two notions, i.e. the notion of loss or decline and the ability of the concept in predicting negative health outcomes. In this case, both conditions (i.e. frailty and fragility) have in common an increased risk of negative health outcomes, yet, one is the consequence of an ongoing decline, while the other one refers to a stable condition making the individual more fragile. Such a view leads to propose a distinction between frailty as the result of a process of decline of intrinsic factors, and a relatively stable condition of fragility, due to extrinsic factors, mainly (although not exclusively) unfavorable living and social conditions, making the person more vulnerable to health incidents independently of his/her current health condition. In other words, the term fragility could be used in older adults to refer to a relatively stable state of vulnerability for adverse health outcomes due to social and living conditions, whereas the term frailty should be preferred to refer to a process of declining physiological and physical conditions.
This conception distinguishing frailty and fragility (due to social vulnerability) also has practical implications. If frailty and fragility (i.e. social vulnerability) are close but distinct concepts, the underlying mechanisms should be substantially different which calls for different interventional strategies. In a prevention perspective, socially vulnerable elderly population could be a relevant target population. Indeed, among the numerous social deficits, some of them are modifiable and could be targeted in future prevention programs aiming for instance at promoting social interactions. New technologies could help overcome social participation challenges faced by older persons and facilitate social inclusion via virtual co-located activities. Such interventions could in turn, reduce or delay the incidence of frailty. Obviously, further research is needed to assess the benefits of such programs in socially vulnerable elderly population.
Our study has several strengths: the large sample, the population-based design, as well as the prospective follow-up allowing investigating frailty incidence along a long period of follow-up. Another strength is the variety of data collected in participants encompassing clinical, medical, psychological and social information which allowed computing the two indices (i.e. SVI and FI) both relying on an important amount of information (more than 50 deficits for the two indices). Both SVI and FI indices have been previously validated not only in their original study (30, 37) but also in French population (31, 39). The main limitation of this study is precisely related to the calculation of the FI requiring an important number of information for each individual. As 464 participants had at least one missing data making it impossible to compute the FI, they had to be excluded from the study sample.

 

Conclusion

If frailty is undeniably a multidimensional condition, with physical and psychosocial factors contributing to its development, a better understanding of the role and position of these factors in the pathway to frailty is needed. In a preventive perspective, this work highlights the relevance to distinguish factors that pre-exist and characterize an older person as fragile (he/she is not frail but has a greater risk of becoming so because of his/her living conditions making him/her more vulnerable) from factors that co-exist with a state of decline and loss and are therefore markers of frailty.

 

Funding: The PAQUIS study was supported by AGRICA; ARMA; Caisse Nationale d’Assurance Maladie des Travailleurs Salariés; Caisse Nationale de Solidarité pour l’Autonomie; Conseil Général de la Dordogne; Conseil Général de la Gironde; Conseil Régional d’Aquitaine; Fondation de France; France Alzheimer; GIS Longévité; Institut National de la Santé et de la Recherche Médicale; Ipsen; Mutuelle Générale de l’Education Nationale; Mutualité Sociale Agricole; NOVARTIS Pharma; Roche; and SCORInsurance.

Conflict of Interest: The authors have no conflicts.

Author Contributions: H Amieva wrote the manuscript, designed and supervised the study. C Ouvrard conducted the statistical analysis and interpreted the data. J-F Dartigues is the PI of the PAQUID study. C Ouvrard, J-F Dartigues, M Tabue Teguo and A Avila-Funes provided critical revisions of the manuscript.

Ethical standards: This study is in accordance with the international ethical standards of research and with the 1964 Helsinki Declaration.

 

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