Original Research

Vulnerability among rural older adults in southern Brazil: population-based study


name here
Tatiane Nogueira Gonzalez
1 PhD, Postdoctoral Researcher *

name here
Cristina dos Santos Paludo
2 PhD

name here
Rodrigo Dalke Meucci
3 PhD, Professor


*Dr Tatiane Nogueira Gonzalez


1 Postgraduate Program in Health Sciences, Federal University of Rio Grande, Rio Grande, Rio Grande do Sul, Brazil; and Postgraduate Program in Public Health, Federal University of Acre, Rio Branco, State of Acre, Brazil

2 Postgraduate Program in Health Sciences, Federal University of Rio Grande, Rio Grande, Rio Grande do Sul, Brazil

3 Postgraduate Program in Health Sciences, Federal University of Rio Grande, Rio Grande, Rio Grande do Sul, Brazil; and Postgraduate Program in Public Health and Postgraduate Program in Health Sciences, Federal University of Rio Grande, Rio Grande, Rio Grande do Sul, Brazil


14 September 2023 Volume 23 Issue 3


RECEIVED: 29 June 2022

REVISED: 2 May 2023

ACCEPTED: 4 May 2023


Gonzalez TN, Paludo CD, Meucci RD.  Vulnerability among rural older adults in southern Brazil: population-based study. Rural and Remote Health 2023; 23: 7714. https://doi.org/10.22605/RRH7714


This work is licensed under a Creative Commons Attribution 4.0 International Licence


Introduction:  The study aimed to estimate the prevalence of vulnerability, and to identify the associated factors of vulnerability among rural community-dwelling older adults living in the municipality of Rio Grande, Rio Grande do Sul, Brazil.
Methods:  This was a cross-sectional, population-based study of a sample of individuals aged 60 years or older. Data from the first follow-up of the EpiRural Cohort Study (2018–2019) were used. Vulnerability was assessed using the Vulnerable Elders Survey (VES-13). The maximum score is 10 and older adults with scores of 3 or more are classified as vulnerable. Poisson regression with robust adjustment of variance was used for crude and adjusted analyses. For the analysis of the associated factors, a theoretical model was constructed with three hierarchical levels. The variables were adjusted in relation to each other within each level; those with a significance level of 0.20 or less were included in the regression model and adjusted to a higher level, with a subsequent level of significance of 5%.
Results:  The overall prevalence of vulnerability was 40.8% (95%CI 37.5–44.3). Vulnerability was more prevalent among women (PR=1.45; 95%CI 1.23–1.71), older adults who did not work (PR=1.70; 95%CI 1.17–2.45), those who lived without a partner (PR=1.26; 95%CI 1.07–1.47), those with diabetes (PR=1.23; 95%CI 1.03–1.48), those with depression (PR=1.21; 95%CI 1.02–1.42), those with osteoporosis (PR=1.38; 95%CI 1.15–1.66), and those with sarcopenia (PR=1.67; 95%CI 1.38–2.02).
Conclusion:  Vulnerability is common among rural community-dwelling older adults and is associated with sociodemographic and health characteristics.


aged, Brazil, cross-sectional studies, epidemiology, vulnerability, vulnerable elders survey.

full article:


The Brazilian population is aging rapidly. According to projections of the Brazilian Institute of Geography and Statistics, in 2043 a quarter of the population will be older adults1. This process will have implications for the Brazilian health system2. Therefore, screening older adults at risk for worsening health can provide an opportunity for detection and intervention, thus preventing adverse clinical outcomes and enabling the most efficient use of health resources.

Vulnerability, defined as an increased risk of functional decline or death over 2 years3, is one of the adverse outcomes associated with the aging process and is associated with hospitalization and the use of emergency services4. The literature show different data on the prevalence of vulnerability among older adults. In Ireland it is 12.2%5, in Taiwan 35.8%6, in the Netherlands 51.0%7, and in Israel 83.1%8. Risk factors for vulnerability include female sex9-11, widowhood12, lower income, less education, depression13, arterial hypertension, and diabetes mellitus9. 

The identification of vulnerable older adults is carried out using the Vulnerable Elders Survey (VES-13). The VES-13 is a simple tool that since 2014 has been recommended by the Ministry of Health of Brazil for the assessment of vulnerability among older adults in primary care settings14. Although VES-13 was originally developed to identify community-dwelling vulnerable older people, few studies have investigated the prevalence of vulnerability in this population, and even fewer have analyzed its associated factors.

Particularly in rural areas, aging results in greater health needs, in a population that traditionally suffers from a reduced supply of health services15. In most countries, rural areas face transportation and communication difficulties, inequalities in health financing, shortages and uneven distribution of health professionals, with worse working conditions16,17. Developing countries display situations of greater iniquities in rural health18. Brazil, despite the expansion of primary health care in the national territory, still registers strong social and spatial inequality in the provision of services, equipment and health personnel19.

To better understand this older rural population, which is often disregarded in epidemiological studies, it is important to study vulnerability and the factors that influence its development. Therefore, to provide useful insights into vulnerability, and to enhance policymakers’ knowledge of emerging issues and the needs of the growing older population, the present study aims to (1) estimate the prevalence of vulnerability, and (2) identify the associated factors of vulnerability among rural community-dwelling older adults living in the municipality of Rio Grande, Rio Grande do Sul, Brazil.


Design and setting

This study was a cross-sectional analysis of the EpiRural Cohort Study. The EpiRural Cohort Study is a prospective cohort that investigates and monitors the living conditions, health, and use of health services in a representative sample of community-dwelling older adults (≥60 years) living in the rural area of the municipality of Rio Grande in extreme southern Brazil.

Rio Grande is located 250 km from the border with Uruguay and about 300 km from the state capital, Porto Alegre. It has an area of approximately 2709 km², and an estimated population of 210 000, of which 4% live in the rural area, distributed in approximately 3000 households20. Currently, the definition of urban spaces used in Brazil is given by municipal legislation. The Brazilian Institute of Geography and Statistics, therefore, considers the rural area of a municipality to be outside its urban perimeter.

The baseline study was conducted in 2017. The studied population consisted of older adults living in the rural area of Rio Grande. The baseline sample was based on the 2010 Demographic Census. A selection process was used to select 80% of the inhabited permanent households. All the older adults of the chosen households were invited to participate in the study. The institutionalized older adults (long-term institutions, hospitals, and penitentiaries) were not included in the study. The first follow-up of the cohort was carried out between September 2018 and March 2019. Of the 1029 older adults included in the baseline, 862 were followed up, resulting in a follow-up rate of 83.8%. Further information about the research can be found in the methodological article21.


Data collection was performed by six trained interviewers. All the respondents were interviewed face-to-face using structured questionnaires with REDCap (Research Electronic Data Capture)22. Two questionnaires were utilized. The household questionnaire was answered by the head of the household and aimed to characterize the household and family income. The individual questionnaire was answered by the older adult or their caregivers and investigated health issues, use of health services, lifestyle and behaviors. The anthropometric parameters evaluated were weight, knee height and calf circumference, standardized according to the method of Habicht et al23.


Vulnerability was assessed using the VES-13. The VES is a 13-item questionnaire that considers age (one question), self-rated health (one question), physical function (six questions), and functional dependence (five questions). Scores range from 0 to 10, and scores of 3 or more classify older adults as vulnerable3.


The assessed covariates were as follows: sex (male; female); marital status (without a partner; with a partner); education, in complete years of study (none; 1–4; 5–8; ≥9); presence of hypertension (no; yes); diabetes (no; yes); rheumatism/arthritis/arthrosis (no; yes); osteoporosis (no; yes); depression (no; yes); history of ischaemia or stroke (no; yes); fall in the past 12 months (no; yes); use of continuous medication (no; yes); sarcopenia (no; yes), assessed using the Strength, Assistance with walking, Rise from a chair, Climb stairs and Calf Circumference (SARC-Calf); max. 20 points, with a score ≥11 indicating sarcopenia24; and cognitive impairment (assessed through the Mini Mental State Examination (MMSE), with a maximum score of 30, where >23 points indicates normal cognition, 19–23 indicates mild cognitive impairment and ≤18 indicates moderate/severe cognitive impairment)25.

Statistical analysis

Data were analyzed using Stata v13 (StataCorp; http://www.stata.com). The sample description was performed by obtaining the proportion of individuals in each category of variables. Descriptive statistics were used to estimate the prevalence of VES-13 items (absolute and relative frequency). The prevalence between the categorical variables was verified through Pearson’s χ2 test. Crude and adjusted analyses were performed using Poisson regression, with robust adjustment for variance, prevalence ratios (PR), 95% confidence intervals (95%CI) and p-values. The adjusted analysis was performed using the hierarchical level model, in which the variables were adjusted for the same level, in addition to those of the previous level in the model. Those variables with p<0.20 were kept for adjustment, and this method was repeated for the other levels. For ordinal exposures, the p-value of the linear trend test was reported; for the other variables, the Wald test of heterogeneity was used, and p<0.005 was considered to indicate significant associations.

Ethics approval

The EpiRural Cohort Study was approved by the Research Ethics Committee of the School of Medicine of the Federal University of Rio Grande (protocol no: 51/2017; protocol no. 154/2018). Participation was voluntary, and informed consent was obtained. All participants voluntarily signed an informed consent form.


Out of 862 older adults followed, 808 fully answered the VES-13 and were included in the analysis. A majority of the participants were male (55%), with 1–4 years of schooling (49.7%), had monthly family income between 2.0 and 2.99 minimum wages, and were married or living with a partner (62%). Only 13.4% of the older adults worked. A total of 58.6% reported hypertension, 38.8% reported rheumatism/arthritis/arthrosis, 19.4% reported depression, 15.9% reported osteoporosis, 15.6% reported diabetes and 6.3% reported history of ischemia or stroke. A total of 21.4% of the older adults reported falls in the last year, 78.9% reported continuous medication use, 15.3% reported sarcopenia, and approximately 35% had mild cognitive impairment. The prevalence of vulnerability was 40.8% (95%CI 37.5-44.3) (Table 1). The mean VES-13 score was 2.84 points (standard deviation of ±2.97), and the median was 2.00 points. Details of the mean and standard deviation of the VES-13 according to the independent variables are presented in Supplementary Table S1.

Table 2 presents the descriptions of the VES-13 items. A total of 66.4% of the elderly people were aged between 60 and 74 years, and 59.0% self-rated their health as very good/good. Regarding physical function items, 69.0% reported no/little/some difficulty performing heavy housework such as scrubbing floors or washing windows, more than 70% reported no/little/some difficulty in stooping, crouching or kneeling; in lifting, or carrying objects as heavy as 10 pounds (4.5 kg); and in walking a quarter of a mile (400 m). A total of 87.0% had no/little/some difficulty reaching or extending arms above shoulder level, and 94.9% had no/little/some difficulty writing, or handling and grasping small objects. For the functionality items, 74.8% of the older adults had no difficulty shopping for personal items; 76.9% had no difficult in managing money, 89.2% responded that they had no difficulty in doing light housework, and more than 90% had no difficulty walking across the room and bathing or showering.

In the adjusted analysis, female sex (PR=1.45; 95%CI 1.23–1.71), not working (PR=1.70; 95%CI 1.17–2.45), living without a partner (PR=1.26; 95%CI 1.07–1.47), medical diagnosis of diabetes (PR=1.23; 95%CI 1.03–1.48), rheumatism/arthritis/arthrosis (PR=1.22; 95%CI 1.03–1.46), depression (PR=1.21; 95%CI 1.02–1.42), and osteoporosis (PR=1.38; 95%CI 1.15–1.66) were associated with vulnerability. An inverse association was observed between education and vulnerability (p<0.001). Sarcopenic older adults had a 67% greater probability of vulnerability than non-sarcopenic older adults (PR=1.67; 95%CI 1.38–2.02), and cognitive impairment was directly associated with vulnerability (PR=1.39; 95%CI 1.08–1.81 and PR=1.77; 95%CI 1.34–2.34; p<0.001) (Table 3).

Table 1:  Descriptors of the sample of older adults residents in the rural area of the municipality of Rio Grande, Rio Grande do Sul, Brazil, 2018–2019 (n=808)table image

Table 2:  Description of Vulnerable Elders Survey items. EpiRural Cohort Study (2018–2019), Rio Grande, Rio Grande do Sul, Brazil (n=808)table image

Table 3:  Crude and adjusted analysis of associations between vulnerability and independent variables, Rio Grande, Rio Grande do Sul, Brazil, 2018–2019 (n=808)table image


This study evaluated the prevalence of and factors associated with vulnerability among rural community-dwelling older adults in Rio Grande, Brazil. Approximately 4 in 10 older adults were vulnerable. Female sex, living without a partner, not working, having a medical diagnosis of diabetes, rheumatism/arthritis/arthrosis, depression and osteoporosis, and having positive screening for sarcopenia and cognitive deficits were associated with a higher prevalence of vulnerability. Higher education was associated with a lower occurrence of the outcome.

Although health and lifestyle indicators may differ between older adults living in urban and rural areas26, the prevalence of vulnerability found in this study was similar to that reported in other studies. Studies carried out in different populations of urban older adults in different locations, such as the US27,28, Canada29, Ireland30,31, France32 and Taiwan6, reported prevalences ranging from 30% to 50%. In Brazil, studies have reported a similar prevalence of vulnerability, of approximately 50%12,33.

The association between sex and vulnerability identified in this survey was also observed in other studies. In Ireland, women were 50% more likely to be vulnerable10. In Brazil, two studies found a higher prevalence of vulnerability among women9,11. The feminization of aging is already well established, but in our study we did not find any difference in the mean age between men and women. A possible explanation for our findings is that, as they are more concerned with their health, women have more acute perceptions of the signs and symptoms of diseases34.

Our findings are similar to those reported in studies that also demonstrated an inverse relationship between education and income and vulnerability. Higher levels of education imply better living conditions and a greater ability to take care of one’s health35. In addition, higher income and education are related to greater access to basic infrastructure and health services36, favoring a more assisted aging process and, consequently, reducing the occurrence of vulnerability.

No other studies were found that assessed the association between work and vulnerability. A possible explanation for our findings is that, as functional capacity is one of the components of the VES-13 and as work activity presents challenges that encourage the maintenance of functionality among older adults37, it is likely that older adults who work are more independent. Another hypothesis for this finding is the fact that the work activity in the area is more manual. Thus, it is assumed that older adults living in rural areas may have less loss of functionality because they remain active for longer.

The absence of a partner increased the probability of vulnerability by 26%. This association can be explained by the greater attention and care received from a partner, which would lead a person to seek more health services and, thus, increase the chances of diagnosis of health problems and receiving treatment, thus protecting the individual against vulnerability34. Previous research has shown that the absence of a partner can lead to isolation and reduced concern with health, causing worse clinical outcomes among older adults38.

Previous studies carried out in Brazil have shown the association between diabetes, osteoporosis and rheumatism/arthritis/osteoarthritis and vulnerability9,12. It is possible that the greater vulnerability of older adults with these conditions is due to the greater risk of complications and limitations resulting from the processes of disease progression8.

The association between depression and vulnerability corroborates an Irish study in which older adults who reported depressive symptoms were 4.8 times more likely to be vulnerable10. Psychiatric disorders, including depression, are often attributed to the losses of physical and mental functions that accompany the aging process39.

The strong association between continued medication use and vulnerability was lost in the adjusted analysis. On the other hand, a study carried out in Lima, Peru, with the objective of evaluating the pharmacological quality of hospitalized older adults, found that the mean number of medications per patient was 2.940. Other studies have shown that the use of medication may be associated with a decline in functional status in older adults41.

Sarcopenia is characterized by the progressive and generalized loss of skeletal muscle mass and muscle function, which can lead to adverse outcomes such as reduced ability to perform daily activities42. Consequently, sarcopenia generates functional dependence, which is one of the items evaluated by the VES-13. However, it is important to emphasize that the association between sarcopenia and vulnerability was expected, as some items are common to both instruments. However, consistent with our findings, loss of muscle mass was associated with the presence of vulnerability in institutionalized older adults. In a study of elderly Polish subjects, participants with sarcopenia scored three or more points on the VES-1343.

Older adults with greater cognitive impairment become vulnerable as they stop performing the most complex activities of daily living44,45. The performance of activities of daily living depends on satisfactory cognitive ability, and a reduction in cognitive ability or a cognitive impairment will compromise the activities of daily living that are assessed as part of the VES-13 construct.

Our study has some limitations. First, the cross-sectional design does not allow the analysis of the temporality of events, making these susceptible to reverse causality in some associations, such as for the variables of work, depression and sarcopenia. Second, the VES-13 is a simple method for identifying community-dwelling vulnerable older adults, defined as those at increased risk for death or functional decline. Thus, there is no gold standard for vulnerability. However, its cultural adaptation was performed, and the VES-13 proved to be a reliable instrument with regard to the stability and internal consistency of its measurements46.

Despite these limitations, VES-13 is promoted in an official document from the Brazilian Ministry of Health, which favors its use, especially in primary care settings. Furthermore, as it is a simple tool that does not require technological resources and that can be applied by any primary care professional, its use is recommended and opportune. To the best of our knowledge, most previous studies have assessed vulnerability as measured by the VES-13 as an exposure, and ours is the first population-based study to assess vulnerability in a rural setting. We believe that our results can improve knowledge about the health characteristics of rural areas.


The results of this study showed a high prevalence of vulnerability among rural community-dwelling older adults, mainly among females and those who did not live with a partner, had less schooling, diabetes, rheumatism, osteoporosis, depression, sarcopenia and cognitive impairment. This study highlights the groups of older adults with characteristics associated with vulnerability who can be assessed in primary healthcare settings, identified in an active search, and monitored to prevent the development of worse outcomes.


1 Brazilian Institute of Geography and Statistics (IBGE). Population projections: Brazil and Federation Units. [In Portuguese]. 2018. Available: web link (Accessed 1 May 2023).
2 Lima-Costa MF, Veras R. Aging and public health. Cadernos de Saúde Pública 2003; 19: 700-701. DOI link, PMid:12806471
3 Saliba D, Elliott M, Rubenstein LZ, Solomon DH, Young RT, Kamberg CJ, et al. The Vulnerable Elders Survey: a tool for identifying vulnerable older people in the community. Journal of the American Geriatrics Society 2001; 49: 1691-1699. DOI link, PMid:11844005
4 Sternberg SA, Bentur N, Abrams C, Spalter T, Karpati T, Lemberger J, et al. Identifying frail older people using predictive modeling. The American Journal of Managed Care 2012; 18: e392-e397.
5 Sasseville M, Smith SM, Freyne L, McDowell R, Boland F, Fortin M, et al. Predicting poorer health outcomes in older community-dwelling patients with multimorbidity: prospective cohort study assessing the accuracy of different multimorbidity definitions. BMJ Open 2019; 9: e023919. DOI link, PMid:30612111
6 Wang J, Lin W, Chang L-H. The linear relationship between the Vulnerable Elders Survey-13 score and mortality in an Asian population of community-dwelling older persons. Archives of Gerontology and Geriatrics 2018; 74: 32-38. DOI link, PMid:28957686
7 Smets IHGJ, Kempen GIJM, Janssen-Heijnen MLG, Deckx L, Buntinx FJWM, van den Akker M. Four screening instruments for frailty in older patients with and without cancer: a diagnostic study. BMC Geriatrics 2014; 14: 26. DOI link, PMid:24571290
8 Sternberg SA, Levin R, Dkaidek S, Edelman S, Resnick T, Menczel J. Frailty and osteoporosis in older women – a prospective study. Osteoporosis International 2014; 25: 763-768. DOI link, PMid:24002542
9 Cruz DTda, Vieira MdeT, Bastos RR, Leite ICG. Factors associated with frailty in a community-dwelling population of older adults. Revista de Saúde Pública 2017; 51: 106. DOI link, PMid:29166451
10 McGee HM, O'Hanlon A, Barker M, Hickey A, Montgomery A, Conroy R, et al. Vulnerable older people in the community: relationship between the Vulnerable Elders Survey and health service use. Journal of the American Geriatrics Society 2008; 56: 8-15. DOI link, PMid:18184202
11 Masson L, Dallacosta FM. Vulnerability in the elderly and its relationship with the presence of pain. Brazilian Journal of Pain 2019; 2: 213-216. DOI link
12 Barbosa KTF, Costa KN de FM, Pontes M deLde F, et al. Aging and individual vulnerability: a panorama of older adults attended by the Family Health Strategy. Texto & Contexto Enfermagem 2017; 26: e2700015. DOI link
13 Amancio TG, Oliveira MLCde, Amancio VdosS. Factors influencing the condition of vulnerability among the elderly. Revista Brasileira de Geriatria e Gerontologia 2019; 22: e180159. DOI link
14 Ministry of Health of Brazil. Older people's health booklet. [In Portuguese]. 2014. Available: web link (Accessed 1 May 2023).
15 Strasser R. Rural health around the world: challenges and solutions. Family Practice 2003; 20: 457-463. DOI link, PMid:12876121
16 Houghton N, Bascolo E, Cohen RR, Vilcarromero NLC, Gonzalez HR, Albrecht D, et al. Identifying access barriers faced by rural and dispersed communities to better address their needs: implications and lessons learned for rural proofing for health in the Americas and beyond. Rural and Remote Health 2023; 23(1): 7822. DOI link, PMid:36878479
17 Perron D, Parent K, Gaboury I, Bergeron DA. Characteristics, barriers and facilitators of initiatives to develop interprofessional collaboration in rural and remote primary healthcare facilities: a scoping review. Rural and Remote Health 2022; 22(4): 7566. DOI link, PMid:36317229
18 Scheil-Adlung X. Global evidence on inequities in rural health protection. New data on rural deficits in health coverage for 174 countries. Working paper. 2015. Available: web link (Accessed 1 May 2023).
19 Franco CM, Lima JG, Giovanella L. Primary healthcare in rural areas: access, organization, and health workforce in an integrative literature review. Cadernos de Saúde Pública 2021; 37: e00310520. DOI link, PMid:34259752
20 Brazilian Institute of Geography and Statistics (IBGE). Demographic Census 2010: Characteristics of Population and Households – results of the universe: results. [In Portuguese]. 2010. Available: web link (Accessed 1 May 2023).
21 Meucci RD, Farias CP, Paludo CDS, Pagliaro G, Perghler Soare M, Lima SHde, et al. Aging in a rural area in southern Brazil: designing a prospective cohort study. Rural and Remote Health 2022; 22: 6591. DOI link, PMid:35192773
22 Harris PA, Taylor R, Thielke R, Pagliaro G, Soares MP, Lima SHde, et al. Research electronic data capture (REDCap) – a metadata-driven methodology and workflow process for providing translational research informatics support. Journal of Biomedical Informatics 2009; 42: 377-381. DOI link, PMid:18929686
23 Habicht JP. Standardization of quantitative epidemiological methods in the field. [In Spanish]. 1974. Available: web link (Accessed 1 May 2023).
24 Barbosa-Silva TG, Menezes AMB, Bielemann RM, Malmstrom TK, Gonzalez MC. Enhancing SARC-F: improving sarcopenia screening in the clinical practice. Journal of the American Medical Directors Association 2016; 17: 1136-1141. DOI link, PMid:27650212
25 Folstein MF, Folstein SE, McHugh PR. "Mini-mental state": a practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research 1975; 12: 189-198. DOI link, PMid:1202204
26 Perez FP, Perez CA, Chumbiauca MN. Insights into the social determinants of health in older adults. Journal of Biomedical Science and Engineering 2022; 15: 261-268. DOI link, PMid:36419938
27 Greenberg MR, Nguyen MC, Stello B, Goldberg AR, Barraco RD, Porter BG, et al. Mechanical falls: are patients willing to discuss their risk with a health care provider? The Journal of Emergency Medicine 2015; 48: 108-114.e2. DOI link, PMid:25282116
28 Salzman BE, Knuth RV, Cunningham AT, LaNoue MD. Identifying older patients at high risk for emergency department visits and hospitalization. Population Health Management 2019; 22: 394-398. DOI link, PMid:30589614
29 Bongue B, Buisson A, Dupre C, Beland F, Gonthier R, Crawford-Achour R. Predictive performance of four frailty screening tools in community-dwelling elderly. BMC Geriatrics 2017; 17: 262. DOI link, PMid:29126383
30 Cahir C, Moriarty F, Teljeur C, Fahey T, Bennett K. Potentially inappropriate prescribing and vulnerability and hospitalization in older community-dwelling patients. The Annals of Pharmacotherapy 2014; 48: 1546-1554. DOI link, PMid:25248541
31 Wallace E, McDowell R, Bennett K, Fahey T, Smith SM. External validation of the Vulnerable Elder's Survey for predicting mortality and emergency admission in older community-dwelling people: a prospective cohort study. BMC Geriatrics 2017; 17: 69. DOI link, PMid:28320329
32 Belmin J, Khellaf L, Pariel S, Jarzebowski W, Valembois L, Zeisel J, et al. Validation of the French version of the Vulnerable Elders Survey-13 (VES-13). BMC Medical Research Methodology 2020; 20: 21. DOI link, PMid:32024470
33 Cabral JF, Silva AMCda, Mattos IE, Neves AdeQ, Luz LL, Ferreira DB, et al. Vulnerability and associated factors among older people using the Family Health Strategy. [In Portuguese]. Ciência & Saúde Coletiva 2019; 24: 3227-3236. DOI link, PMid:31508743
34 Levorato CD, Mello LMde, Silva ASda, Nunes AA. Factors associated with the demand for health services from a gender-relational perspective. [In Portuguese]. Ciência & Saúde Coletiva 2014; 19: 1263-1274. DOI link, PMid:24820609
35 Colet C de F, Mayorga P, Amador TA. Educational level, socio-economic status and relationship with quality of life in elderly residents of the city of Porto Alegre/RS, Brazil. Brazilian Journal of Pharmaceutical Sciences 2010; 46: 805-810. DOI link
36 Almeida APSC, Nunes BP, Duro SMS, Facchini LA. Socioeconomic determinants of access to health services among older adults: a systematic review. Revista de Saúde Pública 2017; 51: 50. DOI link
37 d'Orsi E, Xavier AJ, Ramos LR. Work, social support and leisure protect the elderly from functional loss: EPIDOSO study. Revista de Saúde Pública 2011; 45: 685-692. DOI link, PMid:21779637
38 Carvalho MLde, Barbosa CNS, Bezerra VP, Santos AMRdos, Silva CRDT, Brito CMSde, et al. Health situation in the perception of elderly widows assisted by primary health care. Revista Brasileira de Enfermagem 2019; 72: 199-204. DOI link, PMid:31826211
39 Funnell E. Depression in the elderly. InnovAiT 2010; 3: 199-208. DOI link
40 Espinoza TJO, Castañeda BC. Assessment of the quality of pharmacologic care in vulnerable elder patients in Guillermo Almenara National Hospital, Lima – Peru. [In Spanish]. Revista Horizonte Médico 2010; 10: 28-36.
41 Peron EP, Gray SL, Hanlon JT. Medication use and functional status decline in older adults: a narrative review. The American Journal of Geriatric Pharmacotherapy 2011; 9: 378-391. DOI link, PMid:22057096
42 Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyère O, Cederholm T, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age and Ageing 2019; 48: 16-31. DOI link, PMid:30312372
43 Pachołek K, Sobieszczańska M. Sarcopenia identification during comprehensive geriatric assessment. International Journal of Environmental Research and Public Health 2021; 19: 32. DOI link, PMid:35010295
44 Tabbarah M, Crimmins EM, Seeman TE. The relationship between cognitive and physical performance: MacArthur Studies of Successful Aging. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences 2002; 57: M228-M235. DOI link, PMid:11909888
45 Beckert M, Irigaray TQ, Trentini CM. Quality of life, cognition and performance of executive functions in the elderly. [In Portuguese]. Estudos de Psicologia (Campinas) 2012; 29: 155-162. DOI link
46 Maia FdeOM, Duarte YAdeO, Secoli SR, Santos JLF, Lebrão ML. Cross-cultural adaptation of the Vulnerable Elders Survey-13 (VES-13): helping in the identification of vulnerable older people. Revista da Escola de Enfermagem da USP 2012; 46: 116-122. DOI link, PMid:23250267