Frailty is known as a geriatric syndrome characterized by a decline of function or physiological systems, leading to loss of homeostatic capacity [1]. Frailty syndrome results in an aging-related state of vulnerability1, including falls, fractures, disability and a negative general health status [2]. Increasing the chances of morbidity and mortality [3]. There are many risk factors for frailty already described in the literature, such as older age, female gender, low socioeconomic status, malnutrition, low levels of physical activity (PA), and longer time spent in sedentary behaviour (SB) [4,5]. Regular PA improves physical and psychological health, as well as maintains autonomy in older adults [6]. Kehler and Theou [7]. In a review, reported an association between PA and lower risk of developing or alleviating the severity of the frailty syndrome. Conversely, insufficient PA is related to an increase in adverse health outcomes and, consequently, to a greater probability of frailty in older adults [8]. In addition, excessive SB and inactive lifestyle habits showed a negative association with frailty [9]. According to a longitudinal investigation, each additional hour per day in SB increases the probability of becoming frail by 36% after two years of follow-up [10]. However, it remains unclear whether there are unique or independent effects of SB on frailty7, which indicates that these findings are inconsistent, varying according to assessment methods and cut-off points for consider exposure to high SB [11]. Despite the growing number of studies aimed to evaluate the association of PA and SB with frailty, these factors are divergent in the literature, as it is not yet clear whether this association occurs directly or whether it can be mediated by other variables. Thus, for a better understanding of the relationship between the frailty syndrome and behavioural factors, it is crucial to consider interactions between multiple bio psychosocial aspects (e.g., biological, physiological, and pharmacological) related to lifestyle [12]. In this context, studies have been adopting structural equation modelling analyses in order to verify possible factors that may mediate harmful health outcomes [4, 13]. However, to the best of our knowledge, the effect of PA and SB variables in relation to the presence of the frailty syndrome considering the mediation of bio psychosocial factors has not yet been investigated. Therefore, this study aimed to assess the indirect associations of physical activity and sedentary behaviour with frailty syndrome in older adults.

Study Design and Study Population

This was a cross-sectional study conducted in Alcobaça, Bahia, Brazil, as part of the project Estudo Longitudinal de Saúde do Idoso de Alcobaça (ELSIA), which aims to examine the life and living conditions of the older adults living in the city of Alcobaça, Bahia, Brazil. The study population comprised people of both sexes aged 60 years or more, living in the urban area of the municipality and registered in Family Health Strategy. Information on eligibility criteria and data collection procedures has already been described by da Silva et al [8].

Ethical Procedures

All experimental procedures were approved by the University Human Research Ethics Committee of the Federal University of Triângulo Mineiro (no. 966.983/2015) and conformed to the principles outlined in the Declaration of Helsinki. All participants gave written informed consent for study participation.

Frailty syndrome

Frailty syndrome was diagnosed according to the adapted version of the original Cardiovascular Health Study model1, considering the following four components:

• unintentional weight loss
• exhaustion evaluated by self-report of fatigue
• muscle weakness
• slowness assessed by slow walking speed

Unintentional weight loss was assessed by the following question: “In the past year, have you lost more than 4.5 kg unintentionally (i.e., no diet or exercise)?” An answer of “yes” met the criterion for frailty in this category, adding one point to the overall assessment of frailty. Exhaustion was defined based on the following two questions from the Geriatric Depression Scale (Short Form – GDS-15), adapted for the Brazilian population [14]. “Did you stop doing many of your activities and interests?” and “Do you feel full of energy?” A positive answer to the first question and/or a negative answer to the second question were considered to be signs of exhaustion/fatigue, and one point was added to the assessment of frailty. Muscle weakness was evaluated through handgrip strength assessed using a SAEHAN hydraulic dynamometer (Saehan Corporation SH5001, Korea). The test was performed according to the recommendations of the American Society of Hand Therapists. The cut-off points by Fried et al [1]. Adjusted for sex and body mass index, were used to classify handgrip strength. Slowness, adjusted for sex and height, was assessed by time in seconds to complete a 4.57-m walk test [1]. Individuals who scored above the cut-off point in the walking test and those who were unable to perform the test due to physical limitations were considered to be positive for slowness, and one point was added to the overall assessment of frailty.

Frailty syndrome was scored through an ordinal variable system with scores ranging from 0 to 4 points. Scoring for each of the four frailty criteria was performed. The overall score was classified according to the following classification scheme: 0 to 2 points = not frail, and ≥ 3 points = frail [1].

Sociodemographic Variables

Sociodemographic variables consisted of age, gender (male, female), and marital status (with partner, without partner).

 Depressive symptoms

Depressive symptoms was evaluated by the short-version of the Geriatric Depression Scale (GDS-15), translated and validated for Brazilian population [14]. The GDS-15 is a 15-item scale using yes/no response options: 10 items indicate the presence of depressive symptoms when answered positively and five (items 1, 5, 7, 11, and 13) imply depressive symptoms when answered negatively. The total score for the scale ranges from 0 to 15 points, in which the higher the score, the worse the depressive symptoms.

Functional capacity

The Basic Activities of Daily Living (BADL), commonly referred to as the Katz ADL Index, was used to assess functional status as a measurement of the participant’s ability to perform BADL independently [15]. The Index ranks adequacy of performance in the six functions of bathing, dressing, toileting, transferring, continence, and feeding. Participants are scored for independence (0, 1 or 2 points) in each of the six functions. The total score for the scale ranges from 0 to 12 points, in which the higher the score, the worse the participants ability to perform ADL. The Lawton Instrumental Activities of Daily Living (IADL) Scale was used to assess participant’s ability to perform tasks such as using a telephone, doing laundry, and handling finance [16]. The total score for the scale ranges from 0 to 14 points, in which the lower the score, the worse the participant’s ability to perform IADL.

Self-Efficacy for Walking and Moderate To Vigorous Physical Activity

A self-efficacy scale for PA, validated for Brazilian population, was used to evaluate self-efficacy walking and moderate-vigorous physical activity (MVPA) [17]. The scale consisted of eight items with dichotomous answers (yes = 1 point/ no = 0), independently for walking (four items) and MVPA (four items). The total score for each block (walking or MVPA) of the scale ranges from 0 to 4 points, in which the higher the score, the higher the walking or MVPA self-efficacy.

Diseases, Falls, Hospitalizations And Medications

The number of diseases was evaluated through self-report from a list of diseases related to the circulatory, respiratory, musculoskeletal, digestive and genitourinary systems, metabolic diseases, neoplasms, and ear, eyes, nervous system, blood, infectious and parasitic diseases[18]. The number of falls, as well as the number of hospitalizations, was measured according to the number of occurrences of these events in the last 12 months prior to the interview. The number of medications was evaluated based on the question “How many medications do you currently use?” with those in continuous use being counted.

Health Status

Health status was assessed through the participants’ self-perception of health at the time of the interview, using the Visual Analog Scale. The scale is numbered from 0 to 100, in which 0 means the worst health the participant could imagine, and 100 the best health the participant could imagine[19,20].

 Physical activity and sedentary behavior

PA and SB were measured using the long form of the International Physical Activity Questionnaire (IPAQ), adapted for Brazilian older adult [21, 22]. For SB, participants reported the time spent sitting on weekdays and weekend days. A weighted average [(week × 5) + (weekend × 2)]/7 was used to estimate time spent in sedentary behavior during a typical day.

 Statistical Analysis

Data were entered in duplicate in the Epidata software (version 3.1b). Statistical analyses were performed using the software Statistical Package for Social Sciences (SPSS, version 21) and Analysis of Moment Structures (AMOS, version 24). Test of normality was performed on all continuous variables and verified by the Kolmogorov-Smirnov test. Descriptive statistics were used to calculate frequency (absolute and relative) for comparing the distribution of the sample and calculations of dispersion (standard deviation and standard error). Mann-Whitney U test was used to compare independent variables regarding frailty.

Direct and indirect associations of PA and SB with frailty were evaluated through an application of Structural Equation Modeling analysis, Path Analysis [23, 24]. Composed by two steeps. First, analysis of an initial hypothetical model was performed, and the variables were previously tested through bivariate associations with the determination of Pearson's Correlation Coefficients (p < 0.05). Second, the hypothetical model was re-specified regarding its quality criteria.

Path diagrams were used to represent the initial hypothetical model and the final model of the present study, with the relationships of the independent variables (PA level and SB), mediators (depressive symptoms, BADL, IADL, self-efficacy for walking, self-efficacy for MVPA, number of diseases, number of falls, number of hospitalizations, number of medication and health status) and dependent variable (frailty).

For the goodness of fit analysis of the model, the following parameters were considered: Chi-square statistic (χ2) with p > 0.05; Goodness of Fit Index (GFI) ≥ 0.95; Comparative Fit Index (CFI) ≥ 0.95; Tucker-Lewis Index (TLI) ≥ 0.90 and Root Mean Error of Approximation (RMSEA) ≤ 0.05[24].

Overall, data from 456 older adults (284 women [62.3%], 70.1 ± 8.21 years old, height 1.57 ± 9.60 m, and body mass 67.91 ± 14.4 kg) were analyzed in this study. Most of the participants reported to without a partner. Table 1 shows the distribution of variables used in the theoretical model regarding frail and non-frail older adults (Table 1).

Table 1: Variables of the theoretical model according to the frailty syndrome.

IADL: Instrumental Activities of Daily Living; BADL: Basic Activities of Daily Living; MVPA: moderate-vigorous physical activity. SE: Standard Error.

The analysis of the proposed hypothetical model to explain the relationship between PA and SB and frailty syndrome (Figure 1) did not indicate satisfactory indices of goodness-of-fit: χ2 (df=10) = 755.3735, p < 0.001, CFI = 0.3585, GFI = 0.7794, TLI = -0.1120, RMSEA = 0.1867(Figure 1).

Figure 1: Estimated hypothetical model for the association of physical activity level and sedentary behavior with frailty syndrome. MVPA: moderate-vigorous physical activity.

Considering the low quality of fit of the initial tested model, the model was re-specified. First, the non-significant pathways were eliminated and then Modification Index calculations were performed, which suggested the inclusion of correlations between the errors of the mediating variables. Thus, the final estimated model (Figure 2).

Figure 2: Estimated explanatory model for the association of physical activity level and sedentary behavior with frailty.

Presented acceptable goodness-of-fit indices: χ2 (df= 4) = 7.003, p = 0.135, CFI = 0.9933, GFI = 0.9962, TLI = 0.9533, RMSEA = 0.0407. PA showed indirect associations with frailty syndrome, being mediated by depressive symptoms (β = -0.0372, p = 0.011), IADL (β = -0.0555, p < 0.001), BADL (β = -0.0099, p = 0.015) and number of medications (β = -0.0098, p = 0.046). The association of SB with frailty syndrome was mediated by the number of medications (β = 0.0164, p < 0.001), number of hospitalizations (β = 0.0142, p = 0.002), BADL (β = 0.0176, p < 0.001) and IADL (β = 0.0561, p < 0.0010). Table 2 presents the direct and indirect standardized regression coefficients, which were obtained by multiplying the coefficients of the direct paths between the variables (Table 2).

Table 2: Direct and indirect standardized coefficients for the variables analyzed in the model.

IALD: Instrumental Activities of Daily Living; BADL: Basic Activities of Daily Living.

Our study found that physical activity was indirectly associated with the frailty syndrome, moderated by depressive symptoms, which goes against the fact that regular participation in physical activity is positively associated with social relationships [25]. Depressive symptoms can be reduced by engaging in physical activity [26]. In order to maintain mental health and ensure psychological vitality [27], especially in older adults, who are more susceptible to changes in health dimensions [28]. In addition, physical activity interventions alleviate depressive symptoms similar to antidepressant medications [29]. Previous studies have addressed the relationship between depressive symptoms and frailty in older adults [30,31]. This relationship may be attributed to the somatic symptoms of the frailty phenotype, including low physical activity, which overlap with depression [32]. A previous study showed that the higher the level of frailty, the more depressive symptoms are present compared to those individuals with a lower level of frailty [30]. It can also be inferred that depressive symptom act both as a moderator and a result of the frailty syndrome. This fact corroborates the findings of Monin et al [4]. In which also used path analysis and highlighted bidirectional pathways and the overlap of frailty and depressive symptoms, indicating that more severe states of frailty were associated with greater depressive symptoms, and vice versa. We also found that the number of medications moderated the association between physical activity and sedentary behavior with frailty syndrome. In a previous cross-sectional study, it was found an inversely proportional association between low physical activity and polypharmacy in older adults with multimorbidity in other words, the shorter the time of physical activity, the greater the probability of using medications. Thus, increasing physical activity levels represents an important recommendation to reduce the risk of polypharmacy in this population [33]. Husson et al also verified that the lack of physical activity is one of the variables associated with a greater number of medications in older adults [34]. Regarding sedentary behavior, we also found an association between this variable and the use of multiple medications, in which the probability of being categorized as “sedentary” increases with each additional medication prescribed [35]. Additionally, it is known that the use of multiple medications is considered one of the main concerns of the elderly population [36]. As it is related to higher health costs, the use of a large amount of medication has shown a positive correlation with frailty (r = 0.94, p = 0.016) [37]. In a review that included 25 studies on the relationship between the number of drugs and frailty, it was observed that the probability of being frail can increase with each drug added to the treatment, thus, this factor is recognized as a major contributor to development of fragility [38]. We also found that sedentary behavior was associated with frailty moderated by hospitalization. In a previous prospective study that evaluated associations for all causes of hospitalization, it was found a correlation between sedentary behavior and hospitalization, in which participants who reported sitting for less than eight hours a day had a 14% lower risk of being hospitalized [39]. Furthermore, through an investigation that used accelerometry to measure the time spent on different behaviors, it was found that more time exposed to sedentary behavior increased the risk of more days of hospitalization [40]. During hospitalization, sedentary behavior is common, as patients spend long periods in bed, regardless of their main reason for hospitalization [41]. This factor can lead patients to compromise their independence, with losses in muscle strength and functional performance, especially in older adults [42]. The literature has been showed an influence of frailty on the consumption of health and medical care services, and an increase in hospitalization of older adults [43], which predicts a longer hospital stay, exposing this population to higher readmission rates in the hospital environment [44]. Moreover, frail older adults are more likely to be hospitalized when compared to non-frail older adults [45]. Also, the level of frailty is also a determinant of the risk of hospitalization [46]. Therefore, there is a need for strategies that can reverse or mitigate this scenario. Our results showed that both physical activity and sedentary behavior, moderated by ADLs, are associated with frailty syndrome. Also, an indirect association showed that the number of frailty criteria [1]. Mediated the relationship between the number of diseases and the inability to perform ADLs. These results are relevant, since the more frailty criteria, the greater the dependence on the execution of ADLs13. Moreover, it is important to emphasize that frailty syndrome is associated with the inability to perform the BADL and IADL, both from a physical and social perspective [47]. That is, reduced participation in activities in groups and social support networks, loss of contacts and decreased self-management skills in fulfilling their needs [48]. In another study, it was found that all components of the frailty syndrome, except unintentional weight loss, are associated with the inability to use transport, shop, clean the house and prepare meals [49]. Thus, functional incapacity represents one of the main and most serious consequences of frailty [50]. In the present study, it was observed that physical activity exerts a positive effect on the functional capacity of BADL and IADL. This data is in line with those reported by Connoly, Garvey and McKee [51]. In which the lack of physical activity represented a risk factor for deficiencies in BADL and IADL in older adults. In another study, Crevenna and Dorner [52]. Found that older adults (≥ 65 years old) who did not meet the minimum requirements for aerobic physical activity had more deficits in BADL and IADL. Regarding sedentary behavior, we found a negative effect on functional capacity, in which the longer the time spent sitting, the worse the ADLs performance. Some previous studies have pointed out the causal relationship between these variables. Scher et al [53]. showed that older adults who have some dysfunction spend an average of 5.8 to 10.3 hours/day of their waking hours exposed to sedentary behavior compared to older adults without any impairment in ADLs. Dunlop et al [54]. Found that the odds of disability for ADLs were more than 50% (odds ratio: 1.52 [95% confidence interval: 1.10; 2.10]) for each one-hour increase in sedentary time, regardless of the time spent in MVPA. Our study is not without limitations. First, the cross-sectional design of this study does not allow us to confirm causality and effect between the investigated variables. Second, the use of self-report instruments to measure the investigated can lead to forgetfulness and evaluation bias, although this is mitigated through previous training of the interviewers. Conversely, we used scales previously validated in Brazilian population. Moreover, it was constructed a theoretical model following the structural equation modeling, as it explains the associations between physical activity and sedentary behavior with the frailty syndrome, taking into account biopsychosocial factors.

Path analyses performed in the present study indicated indirect but no direct associations between physical activity and sedentary behavior with frailty syndrome in Brazilian older adults. Moreover, indirect associations were observed between physical activity and frailty syndrome moderated by depressive symptoms, IADL, BADL and number of medications. Associations with frailty syndrome were moderated by IADL, BADL, number of hospitalizations, and number of medications. Therefore, to develop and implement information, recommendation and intervention strategies for the population regarding health conditions and beneficial behaviors related to the frailty syndrome is needed.

We would like to thank all of the participants who volunteered their time to participate in the study, Brazil Alcobaça City Hall, the Nova Filosofia Municipal Laboratory, LACEN-BA Network, Teixeira de Freitas, Bahia. This work was supported in part by National Council for Scientific and Technological Development (MCTI / CNPQ / Universal 14/2014) and financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES).

This work was supported in part by Conselho Nacional de Desenvolvimento Científico e Tecnologico (MCTI / CNPQ / Universal 14/2014) and financed in part by the Coordenação de Aperfeicoamento de Pessoal de Nível Superior – Brasil (CAPES).

Approved by the Human Research Ethics Committee of the Human Research Ethics Committee of the Federal University of Triangulo Mineiro (number 966.983/2015).

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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