Frailty among Community Dwelling Older Adults: Prevalence and Associated Factors

Abstract

Background: Frailty is an important and a highly prevalent health problem in older adults that has a negative impact on health related outcomes. The importance of studying frailty comes from the fact that its merely associated with aging but not an inevitable process. 

Aim: To assess prevalence of frailty and its associated factors among community-dwelling older adults. 

Method: A community based cross sectional study was used withcluster sampling technique targeted 300 older adults in six urban and rural regions affiliated to Dakahlia governorate.  Data was collected using, Mini-mental State Examination, demographic and health-related data structured interview questionnaire, Katz and Akpom scale, Lawton and Brody scale,  the Mini Nutritional Asses sment questionnaire and  Frailty was measured using survey of health, and aging, and retirement in Europe of the frailty indicator. 

Results: Prevalence of frailty was 64.7%  among  the studied older adults, and only 5.3% were non frail. Age, current work, comorbidity, polypharmavy, IADL, and malnutrition were significant independent predictors for frailty (β 0.136, -0.148, 0.117, 0.118, -0.209, and 0.401 respectively), p < 0.05 for all, and responsible for 72.4% of frailty (R² = .724). 

Conclusion: It can be concluded that frailty was highly prevalent in community-dwellers in Egypt urban and rural regions.  Risk factors of frailty include female gender, widohood, illiteracy, living arrangements, previous hospitalization, drug compliance, periodic checkup, engagement into social practices, and smoking. Moreover Older adults' age, work status, income, comorbidities, polypharmacy, functional status, and nutritional status were found as the main factors associated with frailty.

Recommendations: Assessment of associated risk factors of frailty  in older adults should be done through community-based healthcare programs for early diagnosis and management.

Introduction:

An “older adult” or elderly is defined as an individual over the age of 60 years. Elderly population is growing rapidly worldwide. In 2030, elderly population in the world will be1 in 6 people as they will increase from 1 billion in 2020 to 1.4 billion 2030 and in 2050 will double to 2.1 billion (World Health Organization, 2022). In the Arab world, Egypt has the highest percentage of elderly (7.2%) in which the percent of older people was 7.2% in 2013, 8.1% in 2016, and projected to be 9.2% in 2021, and it is predictable to reach 20.8% in 2050 (Aly, Dessoki, Eldeeb, & Mohamed, 2021).

Old age represents a transitional period where older adults meet changes in physical health and social roles; these transitional changes are significant (Sun et al., 2021).resulting insignificant adverse outcomes including frailty development (Delbari, Zanjari, Momtaz, Rahim, &Saeidimehr, 2021).‏Frailty in older adults is known to be reversible condition and considered a strong, common and independent predictor of disability characterized by physical, social, psychological, and economical aspects. Despite, frailty is a lifelong condition; it is not an inevitable consequence from the process of aging (Galluzzoet al., 2022 &Hazuda et al., 2021).

According to Fried et al. (2001) frailty defined as "A condition meeting 3 of the 5 phenotypic criteria namely, unintentional weight loss, exhaustion, low grip strength, slowed waking speed and low physical activity". However, a common definition and assessment tools for clinical practice and research is yet to be achieved, the conceptual and theoretical basis of frailty, as a dynamic, complex, and multifaceted process, is well established (Galluzzoet al., 2022).

The prevalence of frailty varies considerably, typically as a result of varying definitions, assessment tools, as well as varying populations, and diagnostic criteria (Richards, D’Souza, Pascoe, Falloon & Frizelle, 2019). The prevalence of frailty among community-dwelling older adults ranges from 4.9% to 27.3% worldwide (Jang & Kim, 2021).Recent systemic review and meta-analysis (2018) reported the prevalence in community dweller older adults to be 17.4% (95% CI 14.4% to 20.7%) (Siriwardhana, Hardoon, Rait, Weerasinghe &Walters, 2018). In Egypt, Frailty prevalence was 77.1% among elderly in nursing homes compared to 66.3% among community dwellers (Sabbour, Abdul Rahamn, Amin, & Mohamed, 2018) and was 58.7% in study done on elderlies in primary health care centers (Naeem, Mostafa, & El-Said, 2020).

Frailty progression extent a wide range of risk factors includes (i) socio-demographic influences such as poverty, low education level, and living alone, advanced age, and sedentary lifestyles (Walters et al., 2017), (ii) psychological factors, (iii) nutritional issues (iv) polypharmacy; (v) diseases and complications such as cancer, endocrine disorders, dementia (Moon, Huh, Won & Kim, 2019; Di Ciaula & Portincasa, 2020). Frailty captures the combined effects of age-related diseases and an increased vulnerability to adverse health outcomes (Belloet al., 2021).

Therefore, minimizing the number of frail elderly is crucial both to prolong the healthy life span of older adults and to lower medical and long-term care costs. On the other hand, nurses in all healthcare settings (e.g., primary care, hospital, nursing home) are in frequent contact with frail elders (Gobbens, Vermeiren, Van Hoof, & van der Ploeg, 2022) and play a vital role in assessing high risk elderly for frailty in their area of practice using validated assessment and screening tools. Also, nurses should direct patients and caregivers to supportive services and interventions to reduce frailty risk, as well as preventing or delaying adverse health outcomes (Craig, 2019). So, this study aimed to shed light on the frailty among community-dwelling older adults.

Aim of the study

The aim of this study was to assess prevalence of frailty and its associated factors among community-dwelling older adults.

Research questions:

• What is the prevalence of frailty among community-dwelling older adults?

• What are the associated factors of frailty among community-dwelling older adults?

Method:

Study Design:

Community-based cross-sectional research design was used.

Setting:

The study was targeted 3 urban and 3 rural areas affiliated to Dakahlia governorate in Egypt to produce nationally representative samples. Starting with urban areas; representing 3 out of 18 centers of Dakahlia selected randomly namely; Mansoura, Dekernes and Mitt-Salsil. While rural areas representing 3 villages selected randomly from each selected urban area; 1 out of 57 villages affiliated to Mansoura namely Baramoun, 1 out of 33 villages affiliated to Dekernes namely Ashmon, and finally, 1 out of 5 villages affiliated to Mitt-Salsil namely Al-Eitihad.

Subjects:

Sample Size Calculation:

The sample size was calculated using DSS research software (https://Dss.research.com). A previous study found the prevalence ‎of frailty among the elderly was 36.4% ‎(Boulos, Salameh, &Barberger-Gateau, 2016) and it was expected to be 46.4% in our locality, with an alpha error of 5%, study ‎power of 80%. Then the calculated sample size was 300 older adults (150 elderly subjects in urban and 150 elderly ‎subjects in rural areas) as in the following table (1)

Tools Of Data Collection:

Tool I: Mini– Mental State Examination (MMSE): This tool developed by Folstein (1999) and translated into Arabic language validated and tested for its reliability (r = .093) by Abd El Moniem, (2012). It was designed for assessing the elder's cognitive function and consists of 11 items that investigate the memory, orientation to time, person and place, and attention. The MMSE scale score is 30 points and classified as follows: - Score of 24–30 indicates normal cognitive function. - Score of 18–23 indicates mild cognitive impairment. - Score of 0–17 indicates severe cognitive impairment.

Tool II: Demographic and Health-Related Data Structured Interview questionnaire:

This tool was developed after a review of relevant literature and divided into two parts: Part (1): Demographic characteristics of the elderly such as age, gender, level of education, marital status, income, occupation before retirement, and living condition. Part (2): Health-related data such as a medical history of chronic diseases, intake of medications, previous hospitalization, previous surgery, drug compliance, Body Mass Index (BMI).Part (3): Lifestyle -related data such as consumption pattern of different foods, smoking consumption, caffeine intake and social engagement.

Tool III: Katz and Akpom scale: This tool was developed by Katz &Akpom, (1976) to assess functional status by assessing the client’s ability to perform independently six activities of daily living (ADL) (bathing, dressing, toileting, transferring, continence, and feeding). Translated into Arabic language and tested for validity and reliability (r = 0.83) by Sorour, Khalil, Sharaan, & El Geneidy, (2019). A score of 6 or less considered Independent, 7 to 12 considered partially dependent, and 13 to 18 considered totally dependent.

Tool IV: Lawton and Brody scale: This tool was developed by Lawton & Brody, (1969) to assess ability to perform eight domains of instrumental activities of daily living (IADL) (ability to use the telephone, go shopping, food preparation, house-keeping, laundry, transportation, responsibility for own medication and ability to handle finances). Translated into Arabic language and tested for validity and reliability (Cronbach’s alpha α = 0.923) by Rasheedy, &Abou-Hashem, (2020). Females are scored on all 8 areas of function, but in males the domains of food preparation, housekeeping, laundering are excluded. Therefore, the score ranges from 0 (low function, dependent) to 8 (high function, independent) in female, and 0 through 5 for male. Participants' functional level was then categorized as independent (≥ 75%), assisted (25% <75%) or dependent (< 25%) accordingly (Naeem et al., 2020).

Tool V: Mini Nutritional Assessment Questionnaire (MNA®):

This tool was developed by Guigoz&Vellas, (1999) and used to assess nutritional status among elderly people. This tool includes18 questions with score less than 17 considered malnourished, 17–23.5 considered at risk of malnutrition and 24–30 considered normal nutritional status (Vellas et al., 2006).

Tool VI: Survey of Health, Aging, and Retirement in Europe of the Frailty Indicator (SHARE FI):This tool was developed by Alcser& Benson,(2005) to evaluate frailty which approximate Fried's frailty definition which include 5 criteria; exhaustion, weight loss, weakness, slowness and low physical activity. Frailty is defined in terms of three categories each of which is defined by the sum of the number of individual criteria present (0: non- frail "robust'', 1 or 2: prefrail, and 3, 4 or 5: frail) (Romero-Ortuno, Walsh, Lawlor& Kenny, 2010).

Data Collection Process:

Phase I: Preparatory phase included:-Administrative stage: An official approval was obtained from the dean of Faculty of Nursing- Mansoura University to be used in the selected setting in order to obtain the approval and to permit for the researcher to carry out the study. Literature review; reviewing national and international literatures on the various aspects of older adults, frailty, and activity level, were proposed from scientific published articles, internet searches, and textbooks which was a guide for developing the study tools. Developing the study tools of data collection, tool I (Demographic and Health-Related Data Structured Interview Schedule)‎ was developed and then the researcher translated tool V (MNA‎) & tool VI (SHARE-FI) into the Arabic language and the validity of the translation were checked by an expert of English language from the Faculty of Education. To ensure the validity of the translation, a backup translation technique had been used in this study.

Content validity of the study tools (tool I, tool II, tool III, tool IV, tool V & tool VI) were tested by a jury of five experts in the fields of Gerontological Nursing and occupational health in Community Medicine. Accordingly, there was no recommended modifications had been done and the final forms were used for data collection. Then, the interview schedule had been put in its final form. Face validity; it was carried out by conducting a pilot study on 10% of the study subjects (30) older adults to ensure the clarity, feasibility, and applicability of the developed tools and to estimate the time needed to fill the questionnaire sheet, and they were excluded from the study sample. The time needed to fill the interview schedule was 40–45 min. The reliability; tool V (MNA‎) & tool VI (SHARE-FI) had been tested by means of the Cronbach Alpha test (α = .834, and, α = .831, respectively).

Ethical considerations approval was obtained from the Research Scientific Ethical Committee of Faculty of Nursing, Mansoura University, consent was obtained from each study subjects enrolled in the study, after clarification of the aim of the study, the researcher highlighted that the collected data was treated confidentially and only used for the study. Safety, anonymity, and privacy had been assured throughout the whole study. Each older adult was assured that their participation was voluntary, and they have the right to refuse to participate or withdraw from the study at any time without penalty.

Phase II: Operational phase; this phase extended over a period of5 months; started from the beginning of March 2020 and ended in July 2020. This phase consisted of the following steps: The researcher used to go to the previously selected setting 6 hours/ day, 3 days/week, Study subjects who match sample criteria and accept to participate in the study were interviewed individually; starting by the researcher introduced herself then explanting the aim of the study to collect the necessary data using all study tools. Assessing cognitive status using tool I (MMSE) (participates who scoring less than 24 were excluded), demographic, health-relevant data, life style using tool II, functional status through tool III & IV, nutritional status via tool V (MNA) and frailty via tool VI (SHARE-FI).Comorbidity; defined as the coexistence of two or more chronic conditions (Fan et al., 2021),polypharmacy ≥ 5 drug use were accepted as polypharmacy includes over the counter medication and/or complementary and alternative medicines (Pazan, &Wehling, 2021).

• Hand Grip Strength (HGS) The researcher was used a Futaba Professional Hand Grip Dynamometer; capacity (CAP); 0-130Kg, older adults asked to squeeze the dynamometer with maximal effort for two trials on each hand. The highest recorded HGS on each hand through two consecutive measurements between each attempt, they took break of 1 min, the highest of the four had been selected (Endo, Sato, Kakisaka, &Takikawa, 2021).Weight; so, it was measured using a Granzia Ultra-slim Digital Standing Bathroom Scale, Elega EB9380 - CAP up to 180 kg; with and accuracy of 0.1 kg. Height; was measured using a measuring tape; EMVANV - A UK Brand CAP 0-150 cm. Body mass index (BMI); was then calculated using the following equation: \(\frac{\text{w}\text{e}\text{i}\text{g}\text{h}\text{t} \left(\text{i}\text{n} \text{k}\text{g}\right)}{\text{h}\text{e}\text{i}\text{g}\text{h}\text{t} \left(\text{m}2\right)}\) (Undiyaundeye, Ekeng, &Ubi, 2021).

Statistical Analysis Of The Data: -

The data collected were coded, tabulated, and analyzed using the statistical package of social science (SPSS) version 21. Descriptive appropriate statistical tests were utilized as frequent, percentage, mean, and standard deviation. As well as inferential statistics were used; Reliability Statistics was assessed using Cronbach's Alpha test; is an international measure of reliability with a maximum value 1.0 (high reliability) and the minimum accepted value is 0.65 below this value indicate unreliable tool. Pearson’s Chi square used to compare categorical variables and to study bivariate associations between explanatory variables and Monte Carlo exact test used as alternatives if there were many small expected values. Pearson coefficient used to correlate between two normally distributed quantitative variables. Multivariate linear Regression used to detect the most independent predictors for frailty. A significant level (the p-value) ≤ 0.05 was considered significant. Graphs were done for data visualization by Spss.

Results:

The age of the studied older adults was in between 61 and 93years, with a mean age of 67.99 ± 6.32 years. Males were more prevalent (57.3%), 94.3% were suffering from chronic diseases, and90.8% had more than one disease (multi- morbidity), and 67.0% had polypharmacy of the studied older adults.

Table 1 shows that, the self-reported exhaustion in the past week or one month earlier was the most prevalent frailty criteria (86.3%) while; low physical activity was the least prevalent frailty criteria (54.7%).Based on SHARE FI, Frailty was present in more than two third of the studied older adults (64.7%) and only 5.3% were robust with Mean ± SD (3.36 ± 1.62).

Table (2) shows that, frailty prevalence increases with age; older adults aged 70 years and above were frail with the highest percentage (84.3%).Frailty was more prevalent among female (79.7%), widow (87%), illiterate (81.5%), house wife (78.7%), those who didn’t work after retirement (79.5%), those who hadn’t enough monthly income (87.6%), lived with other than family (100%) with highly significant relationship. While, place of residence either urban areas (66.7%) or rural areas (62.7%) not affect frailty prevalence (p = 0.746).

X  ² : Chi-Square tests P: p-value for the association between different categories

*: Statistically significant at p ≤ 0.05**: Statistically highly significant at p ≤ 0.01

 ^b Other Living arrangements: likefriends, son, and siblings

^ P value based on Monte Carlo exact probability

Figure 1, shows strong positive correlation between frailty, and ADL (P < 0.001). Figure 2shows strong negative correlation between frailty, and IADL (P < 0.001). As well, Fig. 3shows strong negative correlation between frailty and nutritional status (p < 0.001).

Table 5 shows that, body weight, height, BMI, calf circumference (CC), mid arm circumference (MAC) and handgrip strength (HGS) of the studied older adults were negatively correlate to frailty (P < 0.001 for all),

Table 6 revealed that, age, current work, comorbidity, polypharmacy, IADL and malnutrition were significant independent predictors for frailty (β 0.136, -0.148, 0.117, 0.118, -0.209, and 0.401 respectively), p < 0.05for all, and responsible for 72.4% of frailty (R² = .724).

Discussion:

Ageing leads to coexistence of several pathological conditions producing a negative impact on health status that may lead to frailty (Richter et al., 2021). Frailty is considered to be a serious public health concerns that results in severe adverse health outcomes as decrease quality of life, functional disability, increase hospitalization and death rate (Lyu, Wang, Jiang, Wang, & Cui, 2021).The importance of studying frailty comes from the fact that it is merely associated with aging and not an inevitable process; hence, it can be prevented or treated. Unfortunately, frailty prevalence among the elders in Egypt is barely known (Naeem et al., 2020). Therefore, this study aimed to study the prevalence and associated factors of frailty among community dwelling older adults.

In studying frailty prevalence, we found that according to the SHARE frailty index, around 64.7% of the 300 elderly participants were considered as frail, whereas 30% were prefrail and only 5.3% were robust (non frail). The high frailty prevalence in the current study may not be surprising but rather expected for many reasons; first, the fact that our study was carried out in two settings, urban and rural areas may partly explain this high prevalence. In deed the elderly population in our study may be more vulnerable because of due to the lower socioeconomic status and limited access to health care services which have been associated with frailty. Finally, most of the geriatric syndromes and factors attributing to the development of frailty were very common in the studied older adults.

Previous studies reported slight differences in prevalence rates of frailty among elderly people; study done in Egypt by Gasser, Elbanouby, Abou-Hashem, &Maamoun (2020) showed that the prevalence of frailty and pre-frailty was 48% and 22.1% respectively according to the clinical frail scale, Sabbour et al (2018) depicted that71.7% of the 350 elderly participants were considered as frail, whereas 22.6% were considered as prefrail and only 5.7% as robust and Tayel and Elkady(2016) where they found that 58.7% of the elderly residents in geriatric homes were frail.

Whilst many other studies reported a much lower rate, the prevalence of frailty was 33.5% in the study of Naeem et al., (2020) in Egypt, 26%in the study of Rivas-Ruiz et al., (2019) in Spain, 34% in the study of Thompson et al., (2018) in Australian. However, recent systematic review report the prevalence of frailty to be 14.6% (95% CI = 10.9% to 18.8%) according to the Fried frailty phenotype (To, Doan, Ho, & Liao, 2022).The difference between our study and other studies may be due to many factors including study settings "eg: our sample were collected from community and other studies collected participants from geriatric homes or outpatient clinic", study population, sample size, and assessment tools. There is an association between all these factors and the different risk of frailty and prefrailty among the elderly (Ofori-Asenso et al., 2018).

The present study revealed that frailty encountered more with increasing age and in female older adults with significant relation. This may be due to the hypotheses of the fact that females live longer than males. The physiological changes, co-morbidity and disability that occurs along body systems that accompanied aging make older females more-frail than male (Gordon et al., 2017).This result in agreement with the studies done in Korea by Kim, Yang, & Kim, (2021), in Latin America by Da Mata et al., (2021), and in Italy, by Collins et al., (2020), in U.S. by Denfeld et al., (2021), in China by Zhang et al., (2020).On the other hand, studies done in Korea by Kim et al., (2021), in Malaysia by Norazman, Adznam, &Jamaluddin, (2020), found no association for frailty and sex despite of the higher percentage of frailty in female than in male.

Living alone, being widow and lower socioeconomic status (SES) as measured by low education and/or low income and occupation, has been was correlating with frailty in this study. Similar findings were reported in prior studies; study done in China by Kong, Lyu, Yao, Yang, & Chen, (2021), meta-analyses from studies done by Kojima, Walters, Iliffe, Taniguchi, & Tamiya, (2020), and by Kojima, Taniguchi, Kitamura, & Fujiwara, (2020), showed that being unmarried were have a twice risk to be frail than being married, studies done in Italy by Salaffi, Di Carlo, Carotti, Farah, &Giovagnoni, (2021), in Spain by Soler-Vila et al., (2016),‏ which found relationship between lower educational level and frailty, study done in Egypt by Saudi, Tosson, &Salama, (2021), in China by Zhang et al., (2020), and in Belgium Maseda et al., (2018) found that those elderlies with low income were frail. Moreover, Van der Linden (2020) in Switzerland, and Srivastava, &Muhammad (2022) in India found positive relationship between lower SES and development of frailty in elderly.

Frailty was found to be linked to various risk factors among which is the comorbidities and polypharmacy. When assessing medical history of the studied older adults via self-reported number of diagnosed chronic diseases and number of medications used, it was found that the majority of those who had more than one disease, and who took more than 5 medications were frail with highly statistically significant association. This may be justified by the fact that geriatric comorbidities courses decline in many physiological systems in older adults that leads to homeostatic imbalance or frailty and increased risk to adverse drug events and medication-related harm (Liau et al., 2021).In the line with current result, studies done in Egypt by Saudi et al., (2021), Gasser et al., (2020) in India by Panda, Pathak, Islam, Agarwalla, Singh, & Singh, (2020).

Moreover, the prevalence of frailty was higher among older adult who not engage in social practice, ex-smoker and intake caffeine daily in the current study. This result supported by; study done in China by Wang, Chen, & Zhou, (2021)& in Korea by Chon, Lee, Kim, & Lee,(2018)which revealed that participating in social activities had a significantly lower frailty risk than participants who never engaging in those activities. Contrariwise, studies done in Canada by Verschoor et al., (2021), in Korea by Jung, Lyu, & Kim, (2021), in China by Li, Xue, Odden, Chen, & Wu, (2020), found that the majority of those who were current-smoked, were frailer but without statistically significant association. In inverse, study done in China by Jing et al., (2020),‏ found that non-tea drinkers were more likely to frailty than tea drinkers, and in Spain by Machado-Fragua, Struijk, Graciani, Guallar-Castillon, Rodríguez-Artalejo, F., & Lopez-Garcia, E. (2019), and by Brunelli et al., (2021), showed no association between coffee/tea consumption/day and frailty.

The present results found negative correlation between body weight, & body mass index (BMI), HGS, mid-arm circumference (MAC), and calf circumference (CC) of the studied older adults with frailty. This result may be because of those who with week hand grip strength reduced their physical ability and increased their fragility which were considerable factors in the frailty, and those with too low body weight also had decreased in overall strength.In the line with the current results, studies done in China by Yuan, Chang, & Wang, (2021), in San Francisco by Lai, Dodge, McCulloch, Covinsky, & Singer, (2020),and in Australia by Tembo et al., (2020), shown that BMI were associated with frailty. In the agreement with current results, studies done in Egypt by Naeemet al., (2020), and in Italy by Valentini, Federici, Cianfarani, Tarantino, &Bertoli, (2018), found statistical correlation between frailty and hand grip strength. In the accordance to present results, study done in China by Liang, Li, Lin, Ju, &Leng, (2021) found that, there was statistically association was found with MAC & CC.

Disability is historically known as having difficulty in performing the essential activities to independent living i.e. difficulties in performing activities of daily living (ADL) and/or instrumental activities of daily living (IADL). Frailty is a well-known predictor of disability (Kojima, 2017). Supporting this, the current study showed that, older adults who were frail were dependent in ADL and IADLs, with statistically significant association between frailty and AD& IADL. Similar result was reported by the study done in Egypt by Saudi et al., (2021),&Naeem et al., (2020)and in Sri Lanka by Siriwardhana, Weerasinghe, Rait, Scholes, & Walters, (2020), showed that frailty was significantly associated with ADL and IADL.

When studying frailty and nutritional status, a strong negative association between frailty and malnutrition was found. Thus, among frail studied older adults, the majority had poor nutritional status. This finding points toward the fact that malnutrition usually occurs due to inability to regulate nutritional needs, or poor absorption of nutrients, and then lead to sever weight loss, state of easy fatiguability, tired, exhausted, increased vulnerability and lack power that end by increased vulnerability or frailty and vice versa, alongside the significant association of poor oral health with frailty that found by Bassim et al., (2020). Further studies were in the line with the present result, study done in Egypt by Shokry, Hamza,Fouad, Mohammed, &Aly, (2021) &Sabbour et al., (2018),in China by Zhang, Zhang, Hu, Meng, Xi, Xu, & Yu, (2021),Zhang et al., (2020), their analysis showed that, malnutrition was significantly associated with frailty. Similarly, study done in Korea by Seo et al., (2021), and in Netherlands by Benraad, (2021), found negative correlation of frailty with nutritional status.

Present study revealed that age, current work, comorbidities, polypharmacy, IADL and nutritional status were significant independents predictors for frailty. Similarly, studies done in China, by Xu et al., (2021), found age, multimorbidity, and IADL scores showed significant associations with frailty (all P < 0.05),in Indonesia by Setiati et al., (2019), found age as predictors for frailty, and in Italy, by Valentini et al., (2018), found IADL predictors for frailty. This result may be justified as older adults are at greater risk of iatrogenic events due to the age-related functional deficits, disease progression, comorbidities, and polypharmacy. Also older adults complain limited physical activity, feel exhausted, lack energy, and weight loss. All these conditions make older adults more prone to frailty syndrome (Muacevic et al., 2021).

In the light of the finding of this study and the fact that frailty is a highly prevalent syndrome in aging populations, it is essential to assess and manage frailty properly. In this regard, knowledge about frailty-associated factors and the complexity of their determinants support the construction of early preventive and intervention measures (Pegorari, & Tavares, 2020).

Strength and limitation:

To our knowledge, researches in frailty are rarely covered in the developing countries, especially in Egypt. This study highlighted frailty as critical problems for older adults which will contribute to the literature on frailty among older adults in Egypt; the study evaluated an extensive list of sociodemographic factors, lifestyle and health relevant, and clinical characteristics, functional, nutritional status, that could influence the frailty among community-dwelling older adults. The study was conducted in 6 geographical regions (3 urban and 3 rural areas) in Dakahlia, which may result in the generalizability of the findings. However, there are some limitations. First, cross-sectional study design may limits the ability to conclude the direction of causality. Second, self reported information in the questionnaire may be affected by memory and information bias due to educational inequality.

Conclusion:

Frailty was highly prevalent in community-dwellers in Egypt urban and rural regions. Risk factors of frailty include female gender, widowhood, illiteracy, living arrangements, previous hospitalization, drug compliance, periodic checkup, engagement into social practices, and smoking. Moreover older adults' age, work status, income, comorbidities, polypharmacy, functional status, and nutritional status were found as the main factors affecting frailty. Hence, it is important to identify older adults who are frail, in order to provide comprehensive care to improve the outcome for this vulnerable population and increased attention should also be placed on intervention studies that look at the impact on the frailty of older adults.

Recommendations:

1. Assessment of assosiated risk factors of frailty in older adults should be done through community-based healthcare programs for early diagnosis and management.

2. Develop standardized care for older adults with frailty, in acute care and primary care settings. Since there are no specific guidelines for providing care to frail, such standard care may include for example; comprehensive geriatric assessment, continuous monitoring for risk factors and early symptoms, educational programs, and orientation to available resources and cost-effective services that supports ageing in place for the elderly.

3. Designing an educational program about frailty, how to manage associated symptoms and locate resources that may decrease its progress to mitigate negative consequences and provide older adults with clear educational materials regarding primary, secondary, and tertiary prevention.

4. Implementation of an intervention program is especially important for older adults and family caregivers in which elderly individuals can be empowered to live independently within their communities. This would enable the senior and community as a whole to build resilience and thereby combat frailty.

Declarations:

Acknowledgements

The authors would like to acknowledge all the participants for their co-operation.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Declaration of Competing Interest

The authors declared no potential conflicts of interest.

References:

1. World Health Organization (2022). Ageing and health. Available at: https://www.who.int/news-room/fact-sheets/detail/ageing-and-health
2. Aly, A. G., Dessoki, H. H., Eldeeb, A. M., & Mohamed, A. S. E. (2021). Challenges being Faced by the Elderly People in Accessing Health Services in Beni-Suef University Hospital. NILES journal for Geriatric and Gerontology, 4(2), 346-364.‏
3. Sun, C., Ding, Y., Cui, Y., Zhu, S., Li, X., Chen, S., ...& Yu, Y. (2021). The adaptation of older adults’ transition to residential care facilities and cultural factors: A meta-synthesis. BMC geriatrics, 21(1), 1-14.‏
4. Delbari, A., Zanjari, N., Momtaz, Y. A., Rahim, F., &Saeidimehr, S. (2021). Prevalence of frailty and associated socio-demographic factors among community-dwelling older people in southwestern Iran: a cross-sectional study. Journal of Diabetes & Metabolic Disorders, 1-10.‏
5. Galluzzo, L., Noale, M., Maggi, S., Feraldi, A., Baldereschi, M., Di Carlo, A., Onder, G., & ILSA Working Group. (2022). Frailty Prevalence, Incidence, and Association with Incident Disability in the Italian Longitudinal Study on Aging. Gerontology, 1-12.‏
6. Hazuda, H. P., Pan, Q., Florez, H., Luchsinger, J. A., Crandall, J. P., Venditti, E. M., ... & Bray, G. A. (2021). Association of Intensive Lifestyle and Metformin Interventions with Frailty in the Diabetes Prevention Program Outcomes Study. The Journals of Gerontology: Series A.‏
7. Fried, L.P., Tangen, C.M., Walston, J., Newman, A.B., Hirsch, C., Gottdiener, J., Seeman, T., Tracy, R., Kop, W.J., Burke, G. (2001). Frailty in older adults: Evidence for a phenotype. J. Gerontol. Ser. A Biol. Sci. Med. Sci., 56, 146–156
8. Richards, S. J., D’Souza, J., Pascoe, R., Falloon, M., &Frizelle, F. A. (2019). Prevalence of frailty in a tertiary hospital: A point prevalence observational study. Plos one, 14(7), e0219083.
9. ‏Jang, H. Y., & Kim, J. H. (2021). Factors Associated with Frailty According to Gender of Older Adults Living Alone. In Healthcare 9(4) p. 475. Multidisciplinary Digital Publishing Institute.‏In 2017; 17: 2629–2634.
10. Siriwardhana, D. D., Hardoon, S., Rait, G., Weerasinghe, M. C., & Walters, K. R. (2018). Prevalence of frailty and prefrailty among community-dwelling older adults in low-income and middle-income countries: a systematic review and meta-analysis. BMJ open, 8(3), e018195.‏
11. Sabbour, S. M., Abdul Rahamn, S. A., Amin, G. E. E., & Mohamed, B. A. (2018). Frailty and malnutrition among Egyptian elderly: prevalence and risk factors in nursing home and community dwelling elderly. The Egyptian Journal of Geriatrics and Gerontology, 5(2), 1-5.‏ ‏
12. Naeem, E. H., Mostafa, N. S., & El-Said, S. M. S. (2020). Prevalence of frailty among elderly patients attending primary health care centers in sixth of October city, 7(2):5-11.
13. Walters, K., Frost, R., Kharicha, K., Avgerinou, C., Gardner, B., Ricciardi, F., ...&Iliffe, S. (2017). Home-based health promotion for older people with mild frailty: The Home-Health intervention development and feasibility RCT. Health Technology Assessment (Winchester, England), 21(73), 1.
14. Moon, J. H., Huh, J. S., Won, C. W., & Kim, H. J. (2019). Is Polypharmacy associated with cognitive frailty in the elderly? Results from the Korean frailty and aging cohort study. The journal of nutrition, health & aging, 23(10), 958-965.
15. Di Ciaula, A., &Portincasa, P. (2020). The environment as a determinant of successful aging or frailty. Mechanisms of Ageing and Development, 111244.‏https://doi.org/10.1016/j.mad.2020.111244.
16. Bello, G. A., Ornstein, K. A., Lucchini, R. G., Hung, W. W., Ko, F. C., Colicino, E., ... & Todd, A. C. (2021). Development and Validation of a Clinical Frailty Index for the World Trade Center General Responder Cohort. Journal of Aging and Health, 0898264321997675.‏
17. Gobbens, R. J., Vermeiren, S., Van Hoof, A., & van der Ploeg, T. (2022). Nurses’ Opinions on Frailty. In Healthcare (Vol. 10, No. 9, p. 1632). MDPI.‏
18. Craig, L. (2019). The role of the registered nurse in supporting frailty in care homes. British Journal of Nursing, 28(13), 833-837.‏
19. Boulos, C., Salameh, P., &Barberger-Gateau, P. (2016). Malnutrition and frailty in community dwelling older adults living in a rural setting. Clinical nutrition, 35(1), 138-143.‏
20. Folstien, M. (1999). Mini-Mental State, a practical method for grading the cognitive state of patients for the clinician in clinical Gerontological Nursing: A Guide to Advanced Practice. 2nd. London: WB Saunders Company.
21. Abd El Moniem, M. (2012). Comparative study of the effect of three types of restorative Nursing Interventions on the health-related functional status of geriatric patients with Parkinson's disease. Unpublished doctorate thesis, Alexandria: university of Alexandria, Faculty of Nursing.
22. Katz, S., &Akpom, C. A. (1976). A measure of primary sociobiological functions. International journal of health services, 6(3), 493-508.‏
23. Sorour, D. M., Khalil, M. I. M., Sharaan, M. A., & El Geneidy, M. M. (2019). Effect of Deep Breathing Exercises versus Incentive Spirometry on Pulmonary Complications among Geriatric Patients Undergoing Upper Abdominal Surgery. International Journal of Novel Research in Healthcare and Nursing, 6(3), 537-555.
24. Lawton, M. P., & Brody, E. M. (1969). Assessment of older people: self-maintaining and instrumental activities of daily living. The gerontologist, 9(3_Part_1), 179-186.‏
25. Rasheedy, D., &Abou-Hashem, R. M. (2020). Overestimated functional dependency in older patients: Can we blame gender difference, unneeded assistance or assessment tools? Archives of gerontology and geriatrics, 88, 104018.‏
26. Guigoz, Y., &Vellas, B. J. (1999). The Mini Nutritional Assessment (MNA) for grading the nutritional state of elderly patients: presentation of the MNA, history and validation. In Nestle Nutritional Workshop Series Clinical and Performance Programme 1 (2) pp. 3-11.‏
27. ‏Vellas, B., Villars, H., Abellan, G., Soto, M. E., Rolland, Y., Guigoz, Y., Morley, J.E., Chumlea, W., Salva, A., Rubenstein, L.Z., & Garry, P. (2006). Overview of the MNA®-Its history and challenges. Journal of Nutrition Health and Aging, 10(6), 456.‏
28. Alcser, K. H., & Benson, G. (2005). The SHARE train-the-trainer program. The Survey of Health, Ageing and Retirement in Europe–Methodology. Mannheim: MEA, 70-74.‏
29. Romero-Ortuno, R., Walsh, C. D., Lawlor, B. A., & Kenny, R. A. (2010). A frailty instrument for primary care: findings from the Survey of Health, Ageing and Retirement in Europe (SHARE). BMC geriatrics, 10(1), 1-12.
30. Fan, Z. Y., Yang, Y., Zhang, C. H., Yin, R. Y., Tang, L., & Zhang, F. (2021). Prevalence and patterns of comorbidity among middle-aged and elderly people in China: a cross-sectional study based on CHARLS data. International journal of general medicine, 14, 1449.‏
31. Pazan, F., &Wehling, M. (2021). Polypharmacy in older adults: a narrative review of definitions, epidemiology and consequences. European Geriatric Medicine, 1-10.‏
32. Endo, K., Sato, T., Kakisaka, K., &Takikawa, Y. (2021). Calf and arm circumference as simple markers for screening sarcopenia in patients with chronic liver disease. Hepatology Research, 51(2), 176-189.‏doi: 10.1111/hepr.13589.
33. Undiyaundeye, F. A., Ekeng, E. B., &Ubi, G. M. (2021). Correlation and Regression Analysis of Age and Body Mass Index (BMI) Among Nsidung Fisher Folks, Calabar South, Cross River State, Nigeria: The Counselor Sensitization Strategy. Annual Research & Review in Biology, 77-85.‏
34. Richter, D., Guasti, L., Walker, D., Lambrinou, E., Lionis, C., Abreu, A., &Asteggiano, R. (2021).Frailty in cardiology: definition, assessment and clinical implications for general cardiology. A consensus document of the Council for Cardiology Practice (CCP), Association for Acute Cardio Vascular Care (ACVC), Association of Cardiovascular Nursing and Allied Professions (ACNAP), European Association of Preventive Cardiology (EAPC), European Heart Rhythm Association (EHRA), Council on Valvular Heart Diseases (VHD), Council on Hypertension (CHT), Council of Cardio-Oncology (CCO), Working Group (WG .... European Journal of Preventive Cardiology, 29(1), 216-227
35. Lyu, H., Wang, C., Jiang, H., Wang, P., & Cui, J. (2021). Prevalence and determinants of frailty in older adult patients with chronic coronary syndrome: a cross-sectional study. BMC geriatrics, 21(1), 1-9.‏
36. Gasser, H. M., Elbanouby, S. M., Abou-Hashem, R. M., &Maamoun, M. M. (2020). Relationship between frailty status and polypharmacy and co-morbidities among elderly patients attending outpatient clinics at Ain Shams University Hospitals. Eur J GeriatrGerontol, 7, 1-7.‏
37. Tayel, DI., and Elkady, HM. (2016). Frailty in relation to poor dietry intake among institutionalized elders in alexandria, Egypt. International Journal of Advanced Scientific and Technical Research, (1), 404-14
38. Rivas-Ruiz, F., Machón, M., Contreras-Fernández, E., Vrotsou, K., Padilla-Ruiz, M., Diez Ruiz, A. I., ...& Group GIFEA. (2019). Prevalence of frailty among community-dwelling elderly persons in Spain and factors associated with it. European Journal of General Practice, 25(4), 190-196.‏
39. Thompson, M. Q., Theou, O., Adams, R. J., Tucker, G. R., &Visvanathan, R. (2018). Frailty state transitions and associated factors in South Australian older adults. Geriatrics & gerontology international, 18(11), 1549-1555.‏
40. To, T. L., Doan, T. N., Ho, W. C., & Liao, W. C. (2022). Prevalence of Frailty among Community-Dwelling Older Adults in Asian Countries: A Systematic Review and Meta-Analysis. In Healthcare (Vol. 10, No. 5, p. 895). Multidisciplinary Digital Publishing Institute.‏
41. Ofori-Asenso, R., Chin, K. L., Mazidi, M., Zomer, E., Ilomaki, J., Zullo, A. R., ...&Liew, D. (2019). Global incidence of frailty and prefrailty among community-dwelling older adults: a systematic review and meta-analysis. JAMA network open, 2(8), e198398-e198398.‏
42. Gordon, E. H., Peel, N. M., Samanta, M., Theou, O., Howlett, S. E., & Hubbard, R. E. (2017). Sex differences in frailty: a systematic review and meta-analysis. Experimental gerontology, 89, 30-40.
43. Kim, Y. M., Yang, N., & Kim, K. (2021). Effects of Perceived Food Store Environment on Malnutrition and Frailty among the Food-Insecure Elderly in a Metropolitan City. Nutrients, 13(7), 2392.‏
44. Da Mata, F. A. F., Miranda Forte Gomes, M., Lício Ferreira Santos, J., Aparecida de Oliveira Duarte, Y., & Gomes Pereira, M. (2021). Depression and frailty in older adults: A population-based cohort study. PloS one, 16(3), e0247766.‏
45. Collins, J. T., Short, R., Carter, B., Verduri, A., Myint, P. K., Quinn, T. J., Vilches-Moraga, A., J. Stechman M., Moug, S., McCarthy, K., & Hewitt, J. (2020). The clinical frailty scale: estimating the prevalence of frailty in older patients hospitalized with COVID-19. The COPE studies. Geriatrics, 5(3), 58.‏
46. Denfeld, Q. E., Habecker, B. A., Camacho, S. A., Roberts Davis, M., Gupta, N., Hiatt, S. O., Medysky, M. E., Purnell, J. Q., Winters-Stone, K., & Lee, C. S. (2021). Characterizing Sex Differences in Physical Frailty Phenotypes in Heart Failure. Circulation: Heart Failure, 14(9), e008076.‏
47. Zhang, X., Liu, Y., Van der Schans, C. P., Krijnen, W., &Hobbelen, J. S. M. (2020). Frailty among older people in a community setting in China. Geriatric nursing, 41(3), 320-324.‏
48. Kim, Y. M., Yang, N., & Kim, K. (2021). Effects of Perceived Food Store Environment on Malnutrition and Frailty among the Food-Insecure Elderly in a Metropolitan City. Nutrients, 13(7), 2392.‏
49. Norazman, C. W., Adznam, S. N. A., &Jamaluddin, R. (2020). Malnutrition as key predictor of physical frailty among Malaysian older adults. Nutrients, 12(6), 1713.‏
50. Kong, L. N., Lyu, Q., Yao, H. Y., Yang, L., & Chen, S. Z. (2021). The prevalence of frailty among community-dwelling older adults with diabetes: a meta-analysis. International Journal of Nursing Studies, 103952.
51. Kojima, G., Walters, K., Iliffe, S., Taniguchi, Y., & Tamiya, N. (2020). Marital status and risk of physical frailty: a systematic review and meta-analysis. Journal of the American Medical Directors Association, 21(3), 322-330.‏
52. Kojima, G., Taniguchi, Y., Kitamura, A., & Fujiwara, Y. (2020). Is living alone a risk factor of frailty? A systematic review and meta-analysis. Ageing research reviews, 59, 101048.‏
53. Salaffi, F., Di Carlo, M., Carotti, M., Farah, S., &Giovagnoni, A. (2021). Frailty prevalence according to the Survey of Health, Ageing and Retirement in Europe-Frailty Instrument (SHARE-FI) definition, and its variables associated, in patients with symptomatic knee osteoarthritis: findings from a cross-sectional study. Aging Clinical and Experimental Research, 33(6), 1519-1527.‏
54. Soler-Vila, H., García-Esquinas, E., León-Muñoz, L. M., López-García, E., Banegas, J. R., & Rodríguez-Artalejo, F. (2016). Contribution of health behaviours and clinical factors to socioeconomic differences in frailty among older adults. J Epidemiol Community Health, 70(4), 354-360.‏
55. Saudi, R., Tosson, E., &Salama, H. (2021). Association between frailty status and cognitive performance of elderly patients attending the Family Medicine Outpatient Clinic in Ismailia, Egypt. Family Medicine & Primary Care Review, 23(2), 232-238.
56. Maseda, A., Diego-Diez, C., Lorenzo-López, L., López-López, R., Regueiro-Folgueira, L., &Millán-Calenti, J. C. (2018). Quality of life, functional impairment and social factors as determinants of nutritional status in older adults: The VERISAÚDE study. Clinical nutrition, 37(3), 993-999.‏
57. Van der Linden, B. W. A., Cheval, B., Sieber, S., Orsholits, D., Guessous, I., Stringhini, S., ... &Cullati, S. (2020). Life course socioeconomic conditions and frailty at older ages. The Journals of Gerontology: Series B, 75(6), 1348-1357.‏
58. Srivastava, S., & Muhammad, T. (2022). Socioeconomic vulnerability and frailty among community-dwelling older adults: cross-sectional findings from longitudinal aging study in India, 2017–18. BMC geriatrics, 22(1), 1-11.‏
59. Liau, S. J., Lalic, S., Sluggett, J. K., Cesari, M., Onder, G., Vetrano, D. L., Morin, L., Hartikainen, S., Hamina, A., Johne, K., Edwin, C. K., Visvanathan, R., & Bell, J. S. (2021). Medication management in frail older people: consensus principles for clinical practice, research, and education. Journal of the American Medical Directors Association, 22(1), 43-49.‏
60. Panda, M., Pathak, R., Islam, F., Agarwalla, R., Singh, V., & Singh, F. (2020). Interplay of multimorbidity and polypharmacy on a community dwelling frail elderly cohort in the peri-urban slums of Delhi, India. Journal of Family Medicine and Primary Care, 9(3), 1647.‏
61. Wang, Y., Chen, Z., & Zhou, C. (2021). Social engagement and physical frailty in later life: does marital status matter?. BMC geriatrics, 21(1), 1-11.‏ ‏
62. Chon, D., Lee, Y., Kim, J., & Lee, K. E. (2018). The association between frequency of social contact and frailty in older people: Korean Frailty and Aging Cohort Study (KFACS). Journal of Korean medical science, 33(51).‏
63. Verschoor, C. P., Dales, R. E., Duong, M., Bourque, C., Mian, O., Ma, J., & Griffith, L. E. (2021). Respiratory Symptoms Are Associated with Frailty in Older Adults with Normal Spirometry, Independent of Smoking, in the Canadian Longitudinal Study of Aging. Respiratory Care. 66 (12) December 2021. 1848-1857; DOI: https://doi.org/10.4187/respcare.09225
64. Jung, Y., Lyu, J., & Kim, G. (2021). Multi-group frailty trajectories among older Koreans: Results from the Korean Longitudinal Study of Aging. Archives of Gerontology and Geriatrics, 98, 104533.‏
65. Li, Y., Xue, Q. L., Odden, M. C., Chen, X., & Wu, C. (2020). Linking early life risk factors to frailty in old age: evidence from the China Health and Retirement Longitudinal Study. Age and ageing, 49(2), 208-217.‏
66. Jing, Z., Li, J., Wang, Y., Ding, L., Tang, X., Feng, Y., & Zhou, C. (2020). The mediating effect of psychological distress on cognitive function and physical frailty among the elderly: Evidence from rural Shandong, China. Journal of affective disorders, 268, 88-94.‏
67. Machado-Fragua, M. D., Struijk, E. A., Graciani, A., Guallar-Castillon, P., Rodríguez-Artalejo, F., & Lopez-Garcia, E. (2019). Coffee consumption and risk of physical function impairment, frailty and disability in older adults. European journal of nutrition, 58(4), 1415-1427.‏
68. Brunelli, L., Davin, A., Sestito, G., Mimmi, M. C., De Simone, G., Balducci, C., ...&Guaita, A. (2021). Plasmatic hippuric acid as a hallmark of frailty in an Italian cohort: the mediation effect of fruit-vegetable intake. The Journals of Gerontology: Series A.‏ 76, Issue 12, December 2021, Pages 2081–2089, https://doi.org/10.1093/gerona/glab244
69. Yuan, L., Chang, M., & Wang, J. (2021). Abdominal obesity, body mass index and the risk of frailty in community-dwelling older adults: a systematic review and meta-analysis. Age and Ageing.‏ 50, (4 July 2021), Pages 1118–1128.
70. Lai, J. C., Dodge, J. L., McCulloch, C. E., Covinsky, K. E., & Singer, J. P. (2020). Frailty and the burden of concurrent and incident disability in patients with cirrhosis: a prospective cohort study. Hepatology communications, 4(1), 126-133.‏
71. Tembo, M. C., Holloway-Kew, K. L., Sui, S. X., Dunning, T., Low, A. C., Yong, S. J., & Pasco, J. A. (2020). Prevalence of frailty in older men and women: cross-sectional data from the Geelong Osteoporosis Study. Calcified tissue international, 107(3), 220-229.
72. Valentini, A., Federici, M., Cianfarani, M. A., Tarantino, U., &Bertoli, A. (2018). Frailty and nutritional status in older people: The Mini Nutritional Assessment as a screening tool for the identification of frail subjects. Clinical interventions in aging, 13, 1237.‏
73. Liang, H., Li, X., Lin, X., Ju, Y., &Leng, J. (2021). The Correlation Between Nutrition and Frailty and the Predictive Value of Different Nutritional Indexes for Frailty.‏ https://assets.researchsquare.com/files/rs-820407/v1/99c3140a-2e1a-445d-8c48-78d2ff789c28.pdf?c=1631888407 acessed at 19 december 2021.
74. Kojima, G. (2017). Frailty as a predictor of disabilities among community-dwelling older people: a systematic review and meta-analysis. Disability and rehabilitation, 39(19), 1897-1908.‏
75. Siriwardhana, D. D., Weerasinghe, M. C., Rait, G., Scholes, S., & Walters, K. R. (2020). Association between frailty and disability among rural community-dwelling older adults in Sri Lanka: a cross-sectional study. BMJ open, 10(3), e034189.‏
76. Bassim, C., Mayhew, A. J., Ma, J., Kanters, D., Verschoor, C. P., Griffith, L. E., &Raina, P. (2020). Oral health, diet, and frailty at baseline of the Canadian longitudinal study on aging. Journal of the American Geriatrics Society, 68(5), 959-966.‏
77. Shokry, M. M., Hamza S. A., Fouad N. T., Mohammed M. H., Aly W. W., (2021). The Relationship Between Vitamin C and Frailty Among Elderly Patients with Type 2 Diabetes Mellitus.‏ DOI : https://doi.org/10.33879/AMH.121.2020.07026
78. Zhang, Q., Zhang, M., Hu, S., Meng, L., Xi, J., Xu, A., & Yu, S. (2021). Prevalence and risk factors of preoperative frailty in Chinese elderly inpatients with gastric and colorectal cancer undergoing surgery: a single-center cross-sectional study using the Groningen Frailty Indicator. Supportive Care in Cancer, 1-10.‏
79. Seo, A. R., Kim, M. J., Kim, B., Seo, Y. M., Lee, G. Y., Park, K. S., &Yoo, J. I. (2021). Associations between Frailty in Older Adults and Malnutrition in Rural Areas: 2019 Updated Version of the Asian Working Group for Sarcopenia. Yonsei Medical Journal, 62(3), 249.‏
80. Benraad, C. E. M. (2021). Geriatric syndromes and multimorbidity in older adults with psychiatric disorders: An integrated perspective (Doctoral dissertation, sn: sl).
81. Xu, L., Zhang, J., Shen, S., Liu, Z., Zeng, X., Yang, Y., ...& Chen, X. (2021). Clinical frailty scale and biomarkers for assessing frailty in elder inpatients in China. The journal of nutrition, health & aging, 25(1), 77-83.
82. Setiati, S., Laksmi, P. W., Aryana, I. S., Sunarti, S., Widajanti, N., Dwipa, L., ...&Chotimah, S. C. (2019). Frailty state among Indonesian elderly: prevalence, associated factors, and frailty state transition. BMC geriatrics, 19(1), 1-10.‏
83. Valentini, A., Federici, M., Cianfarani, M. A., Tarantino, U., &Bertoli, A. (2018).
84. Muacevic, A., Adler, J., Papathanasiou, I., Rammogianni, A., Papagiannis, D., Malli, F., ...&Fradelos, E. (2021). Frailty and Quality of Life among Community-Dwelling Older Adults. Cureus, 13(2).‏ DOI: 10.7759/cureus.13049
85. Pegorari, M. S., & Tavares, D. M. D. S. (2020). Frailty-associated factors among Brazilian community-dwelling elderly people: longitudinal study. Sao Paulo Medical Journal, 137, 463-470.‏