Background
Frailty is a condition that has broadly been investigated in geriatrics and gerontology fields in the last decades. Although there are important conceptual variations, frailty has been commonly defined as reduced physiological reserves and diminished resistance capacities of the human body in response to stressful internal or external situations [
1]. Based on that definition, Fried and colleagues (2001) proposed a phenotype for frailty using the physical criteria of the Cardiovascular Health Study [
2]. According to this phenotype, individuals with three or more of the following criteria are considered frail: unintentional weight loss, self-reported exhaustion, low physical activity level, muscle weakness, and slow walking speed. Those with one or two criteria are considered pre-frail. Although the physical phenotype has standardized the measurement, there is still great variability in the results across studies [
3].
On the other hand, other researchers have adopted a multidimensional approach to evaluate frailty. Some studies have demonstrated the importance of considering both psychological and social dimensions beyond physical criteria [
4‐
6]. A group of Dutch and North American experts developed an integrative definition of frailty as a dynamic state that affects the individual in one or more functioning domains (physical, psychological, and social), which increases the risk of adverse health outcomes [
4]. Notably, frailty has been found to be a more robust indicator than chronological age for some negative outcomes related to aging, such as institutionalization, falls, hospitalization, mortality [
2,
7], and low quality of life [
8], and it has been also considered to be a state that precedes functional disability [
7].
There are several multidimensional instruments available for assessing frailty in the literature, such as the Frailty Index [
9], Tilburg Frailty Indicator [
8,
10], Groningen Frailty Indicator [
11], Comprehensive Frailty Assessment Instrument (CFAI) [
11,
12], and Edmonton Frailty Scale [
13]. The Frailty Index or Accumulated Deficit Index developed by Rockwood and Mitnitski was the first proposed instrument that incorporated the multidimensional nature in the operational definition of frailty [
10]. Afterward, the Tilburg Frailty Indicator was proposed to identify the three functioning domains (social, psychological, and physical) [
4]. Recently, the International Clinical Practice Guidelines for Physical Frailty indicated the physical phenotype as a good instrument for classifying the frailty stage but pointed out the need to complement information from other human functioning domains, including social, psychological, and physical parameters [
14].
Corroborating this discussion, systematic review on the prevalence of frailty in community-dwelling older adults based on 21 cohorts involving 61,500 participants found that the reported prevalence rates differed substantially between the included studies, ranging from 4 to 59.1%. According to the authors, this finding is strongly related to the diversity of frailty conceptualizations. Using physical criteria, the prevalence ranged from 4 to 17%. On the other hand, studies that used broad definitions of frailty incorporating physical, psychological, and/or social dimensions of frailty found prevalence rates from 4.2 to 59.1% [
15]. Similarly, a recent systematic review on the prevalence of frailty in Latin American and Caribbean countries showed a large variation of prevalence, with rates ranging from 7.7 to 42.6% [
16]. In Brazil, a recent study comparing the prevalence of frailty using the physical phenotype and the Tilburg Frailty Indicator among older users of primary health care found frailty prevalence of 23.5 and 35.8%, respectively [
17].
Although frailty is a dynamic and multidimensional condition, most studies usually use physical criteria to evaluate frailty [
11]. On the other hand, an approach by integrating health, functioning, social involvement, and well-being [
9,
18] is appropriate and quite important in clinical settings. Nevertheless, few previous studies have taken a multidimensional approach to frailty in Brazil [
17,
19,
20].
The Frailty in Brazilian Older People Study (FIBRA-BR) analyzed community-dwelling older adults using the physical phenotype as a theoretical framework, which improved the understanding of frailty in Brazil. However, a multidimensional approach could broaden the knowledge by including other indicators related to aging and thereby initiate new areas of research. Therefore, the objectives of the present study were to create a three-dimensional model to assess frailty in older Brazilian adults based on the Tilburg Frailty Indicator [
4] and variables available in the FIBRA-BR study database and to compare the dimensions of the model created between the categories of the physical frailty phenotype.
Discussion
The purpose of this study was to explore the frailty data in a model composed of three dimensions (physical, social, and psychological) and comparing these dimensions among the frailty categories of the physical phenotype proposed by Fried and colleagues [
2] using a large sample of older Brazilian adults. Our final model was composed of the following variables: urinary incontinence, fecal incontinence, sleeping disorder, and living alone (physical dimension); not having someone who could help when needed, not visiting others, and not receiving visitors (social dimension); poor self-rated health, depressive symptoms, concern about falls, feelings of sadness, and memory problems (psychological dimension). In addition, we found that the three dimensions of our multidimensional model are mostly capable to discriminate among non-frail, pre-frail, and frail older adults. Specifically, we observed that frailty scores in the three dimensions increased as the frailty level in the physical phenotype increased. Also, we observed that self-rated health, urinary incontinence, visiting others, receiving visitors, depressive symptoms, concern about falls, feelings of sadness, and memory problems were significantly associated with the physical phenotype.
Our findings suggest the value of considering other criteria, such as social and psychological in addition to physical criteria in studies on frailty. The multiple comparisons of dimensions scores of the multidimensional frailty model among the physical phenotype categories (non-frail, pre-frail, and frail) revealed differences in all dimensions, with one exception. We found that there was not a statistically significant difference in the physical dimension score between pre-frail and frail older adults. This result demonstrates that it is difficult to distinguish between these two physical phenotype categories categorized by the presence of one to two or by three or more frailty criteria. It also reinforces the previous findings that the transition between pre-frailty and frailty is very common [
29,
30].
Many studies have demonstrated a need for a holistic perspective in the management of frail older adults [
8]. These studies also showed that several frail older adults change their categories when the classification criteria changed from a physical to a multidimensional approach and that this creates problems for providing appropriate care and delays the diagnosis of frailty [
6,
31]. Thus, using the variables of the dimensions of our model might help to identify more precisely and early the older adults’ frailty.
Regarding individual variables of physical dimension defined after factorial analysis (urinary incontinence, fecal incontinence, sleeping disorder, and living alone), only urinary incontinence was associated with physical phenotype and was more prevalent as the frailty level in the physical phenotype increased. These results suggest a dose-response relationship and indicate the importance of identifying and proposing preventive actions to help control urinary incontinence. Notably, the low percentage of self-reported urinary incontinence in our study (23.1%) might be explained by the older adults’ misinterpretation who do not consider any involuntary urine loss as urinary incontinence. In addition, older adults tend to deny that they have this health problem due to embarrassment [
32].
In disagreement with the model initially proposed from the literature review (Fig.
1a), in the present study, the variable living alone was placed in the physical domain after factorial analysis (Fig.
1b). Moreover, a low percentage of participants reported living alone (about 13%), and this variable was not significantly associated with the physical frailty phenotype. Unlike the present study, Op Het Veld et al. (2015) showed that frail older adults according to physical phenotype were more likely to live alone than those in the other two categories. This divergence between studies might somewhat be explained by Brazilian family arrangements, which are characterized by financial interdependence in families [
33]. Thus, regardless of the frailty level, few older adults live alone in Brazil.
Previous studies showed that the living alone variable was related to the social network and social connectedness [
18,
34,
35]. On the other hand, literature also reports older adults who live alone might have physical problems that limit their mobility and keep them housebound, which tends to exacerbate their physical problems [
36]. Further, living alone might be related to personal strategies and everyday lifestyle adaptations intended to compensate for functional losses, and it might indicate functional decline caused by loss of physiological reserves, decreased physical fitness, and consequent physical frailty [
37]. Thus, living alone is also related to the physical dimension, as we found in the present study.
The variables visiting others, receiving visitors, and having someone who could help when needed have composed the social dimension of our multidimensional frailty model. The network of social support (making and receiving visits) decreased as the frailty level in the physical phenotype increased. These results corroborate other studies showing the association between physical frailty criteria and the size of social support network [
1,
18,
36]. Unlike the present study, other authors found no difference between the social dimension and frailty categories [
10,
12,
18]. For example, Op Het Veld et al. (2015) found no difference in the social support network among the three categories of physical phenotype, although frail older adults became more family dependent as they lose other types of social support. These studies evaluated the social support network as a family dependent, locally integrated, neighborhood-focused and private [
18], loneliness [
12], and having someone close to the older adults [
10], whereas the present study evaluated as the self-report of visiting and receiving visits.
The community-dwelling older Brazilian adults with low income and without the support of public policies present a limited social support network, besides the family [
25]. The older Brazilian adults habitually visit others as an important social activity, and physical frailty decreases their ability to do so. Older adults with relatively large social networks apparently have more opportunities to go out to socialize, interact with others, and control the adverse effects of frailty [
30]. A previous study showed that older adults with weak or small social support networks were relatively depressed and had limited regular activities [
33]. A Dutch study found that the loss of relationships, social support (visits), and other aspects of the social dimension of the frailty integrated model were associated with low quality of life [
38]. Therefore, promoting social activities and involvement might help to prevent social vulnerability and avoid its negative consequences [
39].
Statistically significant associations were found between all variables of the psychological dimension and the physical phenotype. Thus, poor self-rated health, depressive symptoms, concern about falls, feelings of sadness, and memory problems could complement the physical phenotype proposed by Fried and colleagues [
2]. These results might help to guide programs to protect older adults and reduce psychological frailty and its consequences. In line with our findings, previous studies showed a higher proportion of participants with depressive symptoms evaluated by the GDS-15 [
40] and high concern about falls [
41] measured with the FES-I among frail older adults compared to non-frail older adults.
Self-rated health is an indicator of health in aging, regardless of the frailty level [
18]. The integrated frailty model proposed by Gobbens and colleagues (2010) includes self-rated health in the physical dimension [
4]. However, we found that self-rated health was a better fit in the psychological than the physical dimension. This result might reflect subjective well-being that includes individuals’ considerations of non-physical health aspects, such as life satisfaction or general happiness. In addition, self-rated health might be influenced by feelings about functioning and/or autonomy rather than disease and illness [
42]. From this perspective, health and well-being could be a psychological dimension, as our study found.
This study has some limitations. First, a great number of participants enrolled in the FIBRA-BR study were excluded from the analyses due to missing data, which could interfere in the inference ability of our study. Second, other variables such as loneliness, network size, contact frequency, and emotional support were not investigated in the FIBRA-BR study. Therefore, future studies should include these variables to provide further insight into multidimensional approaches for frailty in low-and-middle-income countries, such as Brazil. Lastly, due to the eligibility criteria of the FIBRA-BR study, our results cannot be generalized for older adults with greater functional or cognitive decline. On the other hand, the current study presents some strengths that should be highlighted. This study was conducted with a large sample of older adults of both sexes from various Brazilian cities with different human development indexes, which enhances the generalization of our findings. The variables included in our model are easily obtained in clinical practice. Thus, our multidimensional frailty model has the potential to be used in this setting. Lastly, the adoption of standardized procedures, extensive training of the field personal, and face-to-face interviews at older adults’ homes contributed to the high quality of data collected.
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