Clinical and functional predictors of mortality in octogenarians: limitations of the Fried frailty phenotype for risk stratificationAbstract
Objective To evaluate frailty as a predictor of mortality in octogenarians.
Methods This retrospective cohort study included individuals aged 80 years or older who were followed from 2016–2018 through 2024–2025. Sociodemographic, clinical, and functional variables, including the presence of frailty, were analyzed, with all-cause mortality as the outcome. Data analysis included descriptive statistics and multivariable Cox regression to estimate the factors associated with mortality.
Results Osteoporosis, urinary incontinence, and severe depressive symptoms were identified as predictors of mortality. The Fried frailty phenotype did not demonstrate significant predictive value for mortality in the sample analyzed.
Conclusion Frailty, when assessed on the basis of specific clinical and functional conditions, was relevant for predicting mortality among the oldest-old, whereas the Fried frailty phenotype showed limitations in this age group. These findings reinforce the need for more sensitive instruments for prognostic assessment in individuals aged 80 years or older.
Keywords
Aged, 80 and over; Mortality; Retrospective Studies; Urinary Incontinence; Depression; Frailty.
Resumo
Objetivo Avaliar a fragilidade como preditora de óbito em octogenários.
Métodos Estudo de coorte retrospectiva realizado com indivíduos com 80 anos de idade ou mais, acompanhados do período de 2016–2018 até 2024–2025. Foram analisadas variáveis sociodemográficas, clínicas e funcionais, incluindo a presença de fragilidade, tendo o óbito por todas as causas como desfecho. A análise dos dados incluiu estatística descritiva e regressão de Cox multivariada para estimar os fatores associados ao óbito.
Resultados Osteoporose, incontinência urinária e depressão grave foram identificadas como fatores preditores de óbito. O fenótipo de fragilidade de Fried não apresentou boa acurácia para predição de mortalidade na amostra analisada.
Conclusão A fragilidade, quando avaliada por meio de condições clínicas e funcionais específicas, mostrou-se relevante para a predição de óbito em pessoas idosas longevas, enquanto o fenótipo de Fried apresentou limitações nesse grupo etário, reforçando a necessidade de instrumentos mais sensíveis para avaliação prognóstica em octogenários.
Palavras-chave
Octogenários; Mortalidade; Estudos Retrospectivos; Incontinência Urinária; Depressão; Fragilidade.
INTRODUCTION
Brazil is experiencing rapid population aging, with an annual growth rate exceeding 4% between 2012 and 2022. Projections indicate that, by 2030, older adults will account for approximately 30% of the population, outnumbering children and adolescents. Nevertheless, socioeconomic inequalities that affect their living conditions persist. Of particular importance is the expansion of the population aged 80 years or older, which is predominantly female and has a high prevalence of functional limitations. Over the past 15 years, the number of oldest-old adults with disabilities is estimated to have increased by 77%1,2.
The risk of developing frailty increases significantly with advancing age and is influenced by comorbidities, physical inactivity, unhealthy dietary habits, and unfavorable socioeconomic conditions. Frailty is a state of physiological vulnerability associated with aging, characterized by reduced physiological reserves and a diminished ability to respond to adverse events. It is associated with a greater risk of falls, loss of autonomy, and mortality and is distinct from disability, social vulnerability, and multimorbidity3.
Frailty therefore has important prognostic value, enabling the screening of older adults at greater risk of adverse events4 and supporting targeted therapeutic interventions. Evidence indicates that frailty, functional limitations, and social isolation increase the risk of mortality independently of chronic diseases and sociodemographic factors5,6. These findings may inform care protocols in primary health care, particularly for individuals aged 80 years or older, given the heterogeneity of the older population and its differing needs for monitoring and care7.
Analyzing trends in health care expenditures and causes of mortality among the oldest-old is essential to overcoming the reductionist view that aging alone determines greater use of health care resources. Increased costs are more strongly associated with clinical profile, disability, multimorbidity, and proximity to death than with chronological age. Although mortality among the oldest-old has been increasingly investigated, chronological age and specific diagnoses continue to be emphasized as the main predictors of mortality. This approach may have limitations in this age group, in which traditional risk factors tend to have lower discriminatory ability8,9.
Accordingly, the present study was based on the hypothesis that frailty is an independent predictor of mortality among individuals aged 80 years or older. Therefore, this study aimed to evaluate frailty as a predictor of mortality among the oldest-old, thereby contributing to improvements in risk stratification and to the provision of care focused on functional status.
METHODS
This analytical, comparative, retrospective cohort study was conducted in two data collection phases. The first phase was conducted between 2016 and 2018 under a protocol approved by the Research Ethics Committee (approval No. 8,423,250; CAAE No. 50075215.2.0000.0029). Individuals aged 80 years or older who were voluntarily recruited from the geriatric outpatient clinic of the Universidade Católica de Brasília (UCB) were eligible. After providing written informed consent, individuals with moderate or severe dementia were excluded. Dementia severity was determined through cognitive assessment using the Mini-Mental State Examination (MMSE), based on cutoff scores adjusted for educational attainment.
During the first phase, data were collected from 222 participants on sociodemographic characteristics, previously diagnosed chronic diseases, urinary incontinence, frailty status, depressive symptoms assessed using the Geriatric Depression Scale (GDS), cognitive performance assessed using the MMSE, and risk of sarcopenia. A convenience sample was used, comprising eligible participants recruited from the outpatient clinic. This sampling strategy is frequently adopted in studies involving adults of advanced age because of the difficulty of accessing this population. Assessments were conducted on dates and at times previously scheduled with the participants at the UCB facilities. Details of the recruitment procedures, blood collection, and physical assessments have been described in previous studies10-13.
During the second data collection phase, which was approved by the Research Ethics Committee (approval No. 8,423,250; CAAE No. 75167923.6.0000.0029) and conducted between 2024 and 2025, surviving participants who voluntarily consented to participate were reassessed for frailty using the same procedures applied during the first phase. For participants who had died, information was obtained from family members or caregivers through interviews, review of a copy of the death certificate, and consultation of the National Registry of Deceased Persons (Cadastro Nacional de Falecidos [CNF], Brazil).
Participants were contacted using the telephone numbers and addresses provided during the first phase, and the responsible caregiver or family member was identified. Interviews were conducted by telephone, in person at the UCB facilities, or at the participant’s home, according to the respondent’s preference.
Figure 1 shows the numbers of individuals assessed at baseline, followed up, and included in the analysis.
Flowchart of the cohort recruitment and follow-up process (n = 129). Brasília, Federal District, 2026.
The sample size was not calculated a priori because the study used a previously established open cohort comprising a convenience sample. Therefore, all eligible individuals assessed at baseline who met the inclusion criteria and had complete data for the variables of interest were included. The final sample size (n = 129) was thus determined by the number of participants successfully followed up and the number of deaths observed during the follow-up period.
The study complied with the ethical and scientific principles established by Brazilian National Health Council Resolution No. 466 of December 12, 2012, and Resolution No. 510 of April 7, 2016, which establishes the standards applicable to research in the Human and Social Sciences involving data obtained directly from participants. The principles and guidelines of the Brazilian General Data Protection Law (Law No. 13,709/2018) were also observed, ensuring the confidentiality, privacy, and protection of the information collected.
All responses were recorded into the REDCap platform (Research Electronic Data Capture), with access restricted to authorized researchers. During the second phase of the study (2024–2025), which involved telephone interviews and administration of the Geriatric Depression Scale and the Mini-Mental State Examination, additional measures were adopted to ensure participant privacy, informed consent, and data security throughout all stages of the study.
Data analysis was conducted in three sequential stages. First, a comprehensive descriptive analysis of the study variables was performed. For continuous variables, measures of central tendency and dispersion were calculated, including the mean, standard deviation, percentiles, median, and minimum and maximum values. Categorical variables were summarized using absolute frequencies and proportions. The normality of the distributions was assessed using the Shapiro–Wilk test, in accordance with recommendations established in the literature on nonparametric statistics14.
Survival analysis was performed using the Kaplan–Meier estimator15. Time was calculated from the date of the first-wave assessment until death (the last contact with the patient while alive). Predictors of mortality were analyzed using the Cox proportional hazards model. The proportional hazards assumption was assessed.
Use of Artificial Intelligence
The authors declare that only academic and editorial support resources permitted under the guidelines of the Brazilian Journal of Geriatrics and Gerontology (RBGG) were used. Their use was restricted to spelling and grammar checking, language editing, stylistic refinement, and textual organization of the manuscript. No resources were used to generate data, formulate hypotheses, interpret results, or replace the authors’ scientific judgment. The final content was critically reviewed and approved by all authors, who assume full responsibility for the manuscript.
DATA AVAILABILITY
The complete dataset supporting the findings of this study is available from the corresponding author upon reasonable request.
RESULTS
Participants were followed for 9 years. At the end of this period, only 14.1% had survived (95% CI). Table 1 presents the baseline sociodemographic and anthropometric characteristics of the sample according to vital status at follow-up. Most surviving participants were female (64.86%). The median age of the surviving participants at the time of the first data collection phase was 91 years, whereas the median age of the participants who died was 85 years.
Baseline sociodemographic characteristics of the sample according to vital status at follow-up. Brasília, Federal District, 2025.
Table 2 presents the baseline clinical and functional characteristics, including cognition assessed using the Mini-Mental State Examination (MMSE), mood assessed using the Geriatric Depression Scale (GDS), number of chronic diseases, self-rated health, and screening for sarcopenia and frailty, according to vital status at follow-up.
Baseline cognition (MMSE), mood (GDS), chronic diseases, self-rated health, and screening for sarcopenia (SARC-F) and frailty (Fried frailty phenotype), according to vital status at follow-up. Brasília, Federal District, 2025.
At the baseline assessment conducted during the first data collection phase, participants who remained alive at the end of follow-up exhibited better cognitive performance than those who died, although the prevalence of cognitive impairment was high and similar in both groups. Regarding mood, survivors had lower GDS scores and a higher proportion of individuals classified as normal. Conversely, participants who had died by the time of the second data collection phase had a higher median GDS score and a more balanced distribution across the normal, depressive symptoms, and severe depressive symptoms categories.
At baseline, hypertension was the most prevalent chronic condition among both participants who remained alive and those who died during follow-up, followed by diabetes mellitus, heart disease, and cancer, with similar proportions between the groups. Some conditions were more frequent at baseline among participants who subsequently died, including arthritis/rheumatism, lung disease, depression, osteoporosis, and urinary incontinence. In both groups, most participants reported having one to three chronic diseases. Regarding baseline self-rated health, survivors were predominantly classified in the fair to very good categories, whereas participants who died more frequently rated their health as fair or good.
The proportion of individuals at risk of sarcopenia was similar among survivors and participants who died. Regarding frailty status, prefrailty predominated in both groups. However, the proportion of frail individuals was higher among participants who died than among survivors, whereas non-frail status was more frequent among survivors.
Table 3 compares frailty classifications between the first and second data collection phases among surviving participants. Classifications from the first phase are presented in the rows, and those from the second phase are presented in the columns. Five individuals initially classified as non-frail progressed to frailty. Among the 26 participants classified as prefrail during the first phase, 11 remained prefrail, 14 progressed to frailty, and one reverted to non-frail status. Only one participant was classified as frail during the first phase and remained frail during the second phase.
Frailty classification according to the Fried frailty phenotype at baseline and follow-up (second assessment). Brasília, Federal District, 2025.
Univariable Cox regression models were fitted for the outcome of death. Only variables that met the proportional hazards (PH) assumption were included in these models, thereby ensuring the statistical validity of the results.
Age, MMSE score, baseline depression, and the frail category of the frailty classification showed evidence of violation of the proportional hazards assumption (p<0.05) and were therefore excluded from the primary survival analysis. The remaining variables met the assumption and remained eligible for inclusion in the Cox regression models.
Table 4, Panel A, presents the results of the univariable models for the predictors that met the proportional hazards assumption.
Cox regression models for mortality. Panel A: Univariable analyses of variables that met the proportional hazards assumption. Panel B: Final multivariable model. Brasília, Federal District, 2025.
Being married was associated with a lower risk of mortality (HR =0.46; 95% CI: 0.22–0.95; p=0.037). Among the clinical conditions, osteoporosis (HR =2.24; 95% CI: 1.33–3.79; p=0.003), urinary incontinence (HR =1.79; 95% CI: 1.07–2.99; p=0.026), and risk of sarcopenia (HR =2.23; 95% CI: 1.37–3.61; p=0.001) were associated with a higher risk of death.
In the emotional domain, assessed using the Geriatric Depression Scale, the presence of depressive symptoms was associated with an increased risk of mortality (HR =2.18; 95% CI: 1.17–4.03; p=0.013). This association was even stronger for the severe depressive symptoms category (HR =4.16; 95% CI: 2.23–7.76; p<0.001) compared with the normal reference category.
A multivariable Cox proportional hazards regression model was fitted to identify predictors of mortality. The five candidate variables that showed statistically significant associations in the univariable analysis were marital status, osteoporosis, urinary incontinence, depression, and risk of sarcopenia.
Table 4, Panel B, presents the final model obtained using backward stepwise selection based on the likelihood-ratio test. The model included 67 participants, among whom 47 deaths occurred. Marital status and severe depressive symptoms remained predictors of mortality among the oldest-old. Being married was associated with a lower risk of mortality than being single (HR =0.315; 95% CI: 0.120–0.827; p=0.019), whereas the severe depressive symptoms category was associated with a higher risk of death than the normal GDS category (HR =4.154; 95% CI: 2.018–8.548; p<0.001).
Given the limited sample size, the hazard ratio estimates showed some imprecision, as indicated by the wide 95% confidence intervals. Further studies with larger samples are therefore needed to strengthen the available scientific evidence.
DISCUSSION
The primary objective of this study was to evaluate the ability of frailty, assessed using the Fried frailty phenotype, to predict mortality in octogenarians. The predictive value of sociodemographic factors, the presence and number of chronic diseases, risk of sarcopenia, depressive symptoms, and urinary incontinence was also investigated, given the recognized impact of these factors in the literature.
Multivariable Cox regression analysis showed that marital status and depressive symptoms remained associated with mortality after simultaneous adjustment for the variables included in the model.
Being married was associated with a lower hazard of death, consistent with findings from recent studies. A cohort study involving 82,091 US adults aged 60 years or older also found an association between marriage and lower mortality16, as did a Swedish study17 involving 5,572,011 individuals. In this context, Potente, Palumbo, and Jalovaara18 also emphasized the positive effect of educational attainment on longevity among individuals who were married or living with a partner. They noted that this benefit tended to be greater among men than among women, a finding also reported by Requena and Reher19.
Regarding depressive symptoms, as assessed using the GDS, mortality risk increased progressively with symptom severity. Participants classified as having depressive symptoms had an approximately twofold higher risk of death, although the association was of borderline statistical significance (p=0.056), indicating a trend toward an increased risk of mortality in this population.
In contrast, the severe depressive symptoms category was strongly and statistically significantly associated with mortality, with a more than fourfold higher risk of death compared with participants without depressive symptoms. This finding reinforces the importance of depression as an independent prognostic factor in older adults. This relationship was described in a meta-analysis by Felipe et al.20, who identified a 44% increase in the relative risk of death among older adults with depressive symptoms. The prevalence of depressive symptoms among Brazilian older adults is estimated at 21%21. This condition has also been associated with a higher incidence of cardiovascular diseases and all-cause mortality, with the magnitude of the association increasing according to symptom severity22.
Notably, the most prevalent chronic conditions in the sample, namely hypertension, diabetes mellitus, cardiovascular disease, and cancer, were not statistically significant predictors of mortality. The Fried frailty classification, which was the primary focus of this study, was also not significantly associated with mortality. Conversely, osteoporosis, urinary incontinence, and severe depressive symptoms as classified using the GDS were associated with mortality in the sample.
These findings suggest that, in this population, such conditions may serve as markers of frailty, particularly in deficit accumulation models, such as the Frailty Index, or in multifactorial approaches. The Fried frailty phenotype used in this study focuses predominantly on physical components, including weight loss, exhaustion, low muscle strength, slow walking speed, and low physical activity23. This interpretation is consistent with the meta-analysis by Tan et al.24, which demonstrated a consistent association between frailty and mortality risk among older adults up to 90 years of age but found no statistically significant association among individuals older than 90 years.
In addition to the findings of the multivariable analysis, the clinical relevance of urinary incontinence, osteoporosis, and risk of sarcopenia should be emphasized, as these variables were associated with mortality in the univariable analysis.
Urinary incontinence was associated with a higher risk of mortality. It is a common geriatric syndrome recognized for its adverse effects on health and socioeconomic conditions and has also been associated with an increased risk of all-cause mortality among older adults. In this population, urinary incontinence may be strongly related to cognitive decline, physical inactivity, immobility, sarcopenia, and impairment in activities of daily living. Together, these factors contribute to more sedentary behavior25. Moreover, urinary incontinence frequently reflects underlying conditions, including frailty, falls, infections, and other comorbidities, which may also increase mortality risk26.
Urinary incontinence represents a sign of systemic vulnerability and an important clinical marker of frailty, particularly among the oldest-old. Although it is not included in the original criteria of the Fried frailty phenotype, it is strongly associated with low physical activity, weakness, slowness, and exhaustion. In Rockwood’s deficit accumulation model, urinary incontinence is frequently included as one of the deficits contributing to a higher Frailty Index, particularly among adults of very advanced age24,27.
The presence of osteoporosis was associated with more than twice the risk of death in the sample analyzed (HR = 2.24), corroborating findings from an Asian study28 that identified a significant association between osteoporosis risk, assessed using the Osteoporosis Self-assessment Tool for Asians (OSTA)29, and all-cause mortality among older adults. A bidirectional causal relationship between osteoporosis and frailty was also demonstrated by Que et al.30, and an association between these conditions was reported in a meta-analysis of 9,664 patients conducted by Hu et al.31. In addition, Shamsalinia et al.5 reported a strong influence of frailty syndrome on osteoporosis severity. The association between the two conditions may be explained by shared multisystem mechanisms30.
The association between sarcopenia and mortality was also reported by Zhang and Zeng32, who identified a significant association between sarcopenia and all-cause mortality. Similar findings were reported in a systematic review and meta-analysis33 that included adults from different settings and countries and used different methods to screen for sarcopenia and frailty. These findings reinforce the consistency of this association across different populations and clinical settings.
Although the present study did not demonstrate an association between frailty identified using the Fried frailty phenotype and mortality among the oldest-old, the findings indicate that osteoporosis, urinary incontinence, and depression are important and frequently interrelated markers of frailty in this population23,27,34.
The Fried frailty phenotype, developed using data from the Cardiovascular Health Study, was established on the basis of a population composed predominantly of relatively healthy individuals aged 65 to 75 years23. Both the findings presented in this study and those of previous research have demonstrated important limitations when this phenotype is applied to the oldest-old24,35.
In this context, several hypotheses should be considered. Individuals aged 80 years or older have likely undergone an intense process of selective survival, in which the frailest individuals died before reaching this age. Thus, certain components traditionally associated with frailty in this age group may reflect adaptations to advanced aging rather than necessarily indicating pathological states. Reduced muscle strength and slow walking speed, for example, tend to be highly prevalent and may therefore have lower discriminatory ability. Moreover, at very advanced ages, the baseline risk of mortality is high regardless of frailty status, which may attenuate the predictive ability of the classification.
Several limitations should be considered when interpreting the findings. First, this was an observational cohort study, which precludes establishing causal relationships between the variables investigated and mortality. In addition, although adjustments were made for potential confounding factors, the influence of residual confounding due to unmeasured variables cannot be ruled out.
Although the proportion of missing data was low and did not change the direction of the observed associations, the possibility of information bias cannot be completely excluded. The potential for bias related to the time interval between the assessment of clinical variables and outcome follow-up should also be considered, because health conditions, functional status, and psychosocial characteristics may change over time and influence the magnitude of the associations identified.
Possible changes in participants’ clinical conditions and treatments during the follow-up period must also be considered, including treatment modifications, the onset of new comorbidities, and functional decline. These factors were not fully captured in the analyses. Despite these limitations, the present findings contribute to the understanding of factors associated with mortality among older adults and reinforce the importance of multidimensional assessment in this population.
CONCLUSION
Based on the findings of this study, frailty identified using the Fried frailty phenotype did not show significant predictive ability for mortality among the oldest-old. In contrast, marital status, depressive symptoms, osteoporosis, urinary incontinence, and risk of sarcopenia showed important associations with mortality, with severe depressive symptoms standing out as an independent predictor of mortality.
These findings reinforce the importance of a broader approach to frailty that incorporates markers of biological and functional vulnerability in the context of advanced longevity. From a clinical perspective, the results suggest that the early identification and management of these conditions may support risk stratification and the planning of more individualized care for octogenarians and other adults of advanced age.
These findings are consistent with the concepts of phenotypic and biological frailty in the context of advanced longevity, suggesting that certain clinical and functional conditions reflect greater systemic vulnerability and may have greater predictive ability than the conventional frailty phenotype among the oldest-old.
The protective association observed among married participants should also be highlighted, as it reinforces the importance of social determinants and interpersonal support for survival at more advanced ages. Similarly, the strong association between depressive symptoms and mortality emphasizes the need for greater attention to mental health in the care of the oldest-old.
Although limited by its observational design and by possible clinical changes during follow-up, this study contributes to a broader understanding of factors associated with mortality among octogenarians and nonagenarians. The findings reinforce the need for comprehensive geriatric assessment strategies that extend beyond the physical components of frailty, facilitating the early identification of potentially modifiable conditions and supporting more comprehensive interventions aimed at promoting longevity and better quality of life.
Future research should include longitudinal studies with repeated measurements of inflammatory biomarkers and functional assessments, as well as the development of integrative models combining clinical conditions, functional status, and biological indicators. Such approaches may improve mortality prediction and contribute to a better understanding of the mechanisms involved in advanced aging.
Funding
References
-
1 Brasil. Ministério da Saúde. Guia de cuidados para a pessoa idosa. Brasília: Ministério da Saúde; 2023. Disponível em: https://bvsms.saude.gov.br/bvs/publicacoes/guia_cuidados_pessoa_idosa.pdf. Acesso em: jul; 2026.
» https://bvsms.saude.gov.br/bvs/publicacoes/guia_cuidados_pessoa_idosa.pdf. Acesso em: jul; 2026. -
2 Organização Pan-Americana de Saúde. Envelhecimento Saudável. Washington (DC): OPAS. Disponível em: https://www.paho.org/pt/envelhecimento-saudavel. Acesso em: jul. 2026.
» https://www.paho.org/pt/envelhecimento-saudavel. Acesso em: jul. 2026. - 3 Doody P, Lord JM, Greig CA, Whittaker AC. Frailty: pathophysiology, theoretical and operational definition(s), impact, prevalence, management and prevention, in an increasingly economically developed and ageing world. Gerontology. 2023;69(8):927-945. https://doi.org/10.1159/000528561.
- 4 Lourenço RA, Moreira VG, Mello RGB, Santos IS, Lin SM, Pinto ALF, et al. Consenso brasileiro de fragilidade em idosos: conceitos, epidemiologia e instrumentos de avaliação. Geriatr Gerontol Aging. 2018;12(2):121-135. https://doi.org/10.5327/Z2447-211520181800023.
- 5 Shamliyan T, Talley KMC, Ramakrishnan R, Kane RL. Association of frailty with survival: a systematic literature review. Ageing Res Rev. 2013;12(2):719-736. https://doi.org/10.1016/j.arr.2012.03.001.
- 6 Francisco PMSB, Assumpção D, Borim FSA, Yassuda MS, Neri AL. Risco de mortalidade por todas as causas e sua relação com estado de saúde em uma coorte de idosos residentes na comunidade: Estudo FIBRA. Cien Saude Colet. 2021;26(12):6153-6164. https://doi.org/10.1590/1413-812320212612.32922020.
- 7 Benzinger P, Eidam A, Bauer JM. Klinische Bedeutung der Erfassung von Frailty. Z Gerontol Geriatr. 2021;54(3):285-296. https://doi.org/10.1007/s00391-021-01873-z.
- 8 Hazra NC, Rudisill C, Gulliford MC. Determinants of health care costs in the senior elderly: age, comorbidity, impairment, or proximity to death? Eur J Health Econ. 2018;19(6):831-842. https://doi.org/10.1007/s10198-017-0926-2
- 9 Espinosa O, Bejarano V, Franky I, Pagali S, Drummond M, Franco OH. Mortality causes and health spending by gender and health conditions in octogenarians, nonagenarians and centenarians in Colombia. Sci Rep. 2025;15(1). . https://doi.org/10.1038/s41598-024-84150-4 .
-
10 Neri AL, Arbex S, Assumpção D, Sanches YM, Portella MR, Doring M, et al. As características de saúde de octogenários recrutados em diferentes contextos evidenciam a heterogeneidade do envelhecimento. Estud Interdiscip Envelhec. 2023:1-16. https://doi.org/10.22456/2316-2171.132938.
» https://doi.org/10.22456/2316-2171.132938. - 11 Rocha Filho EA, Koeche C, Bueno FF, Toledo O, Alves VP, Silva HS, et al. Unraveling the intertwined threads of insomnia and sarcopenia in cognitive and functional impairment in octogenarians. BMC Geriatr. 2025;25(1):868.https://doi.org/10.1186/s12877-025-06398-3.
- 12 Amorim DNP, Nascimento DC, Stone W, Alves VP, Moraes CF, Silva KHCV. Muscle quality is associated with history of falls in octogenarians. J Nutr Health Aging. 2021;25(1):120-125. https://doi.org/10.1007/s12603-020-1485-2.
- 13 Rodrigues IFA, Alves VP, Gomes LO, Pereira DS, Nóbrega OT, Silva KHCV. Associação entre eventos estressores e citocinas inflamatórias e anti-inflamatórias em pessoas idosas longevas. Rev Bras Geriatr Gerontol. 2021;24(1):e200350. https://doi.org/10.1590/1981-22562021024.200350
- 14 Conover WJ. Practical nonparametric statistics. 3rd ed. New York: Wiley; 1999.
- 15 Kleinbaum DG, Klein M. Survival analysis: a self-learning text. 2nd ed. New York: Springer; 2005.
- 16 Wang L, Yi Z. Marital status and all-cause mortality rate in older adults: a population-based prospective cohort study. BMC Geriatr. 2023;23(1):132. https://doi.org/10.1186/s12877-023-03880-8.
- 17 Lindmarker J, Kolk M, Drefahl S. Cohabitation and mortality across the life course: a longitudinal cohort study with Swedish register-based sibling comparisons. Eur J Popul. 2025;41(1):12.https://doi.org/10.1007/s10680-024-09722-6 .
- 18 Potente C, Palumbo L, Jalovaara M. Partner’s education and mortality in Finland: a study of married and cohabiting unions among cohorts born between 1932 and 1970. Eur J Popul. 2025;41(1):29. https://doi.org/10.1007/s10680-025-09752-8.
- 19 Requena M, Reher D. Partnership and mortality in mid and late life: protection or selection? Soc Sci Med. 2021;279:113971. https://doi.org/10.1016/j.socscimed.2021.113971.
- 20 Felipe LRR, Barbosa KSS, Virtuoso Junior JS. Sintomatologia depressiva e mortalidade em idosos da América Latina: uma revisão sistemática com metanálise. Rev Panam Salud Publica. 2022;46:e205. https://doi.org/10.26633/RPSP.2022.205.
- 21 Meneguci J, Meneguci CAG, Moreira MM, Pereira KR, Tribess S, Sasaki JE, et al. Prevalência de sintomatologia depressiva em idosos brasileiros: uma revisão sistemática com metanálise. J Bras Psiquiatr. 2019;68(4):221-230. https://doi.org/10.1590/0047-2085000000250.
- 22 Rajan S, McKee M, Rangarajan S, Bangdiwala S, Rosengren A, Gupta R, et al. Association of symptoms of depression with cardiovascular disease and mortality in low-, middle-, and high-income countries. JAMA Psychiatry. 2020;77(10):1052-1063.https://doi.org/10.1001/jamapsychiatry.2020.1351.
- 23 Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001;56(3):M146-M156. https://doi.org/10.1093/gerona/56.3.M146.
- 24 Tan JA, Koh JH, Merchant RA, Tan LF. Frailty as a predictor of mortality in the oldest old: a systematic review and meta-analysis. Geriatr Gerontol Int. 2024;25(1):102-107.https://doi.org/10.1111/ggi.15025.
- 25 Jerez-Roig J, Farrés-Godayol P, Yildirim M, Escribà-Salvans A, Moreno-Martin P, Goutan-Roura E, et al. Prevalence of urinary incontinence and associated factors in nursing homes: a multicentre cross-sectional study. BMC Geriatr. 2024;24(1). https://doi.org/10.1186/s12877-024-04748-1.
- 26 Peng X, Hu Y, Cai W. Association between urinary incontinence and mortality risk among US adults: a prospective cohort study. BMC Public Health. 2024;24(1). https://doi.org/10.1186/s12889-024-20091-x.
- 27 Rockwood K, Mitnitski A. Frailty in relation to the accumulation of deficits. J Gerontol A Biol Sci Med Sci. 2007;62(7):722-727. https://doi.org/10.1093/gerona/62.7.722.
- 28 Pan XB, Ma QY, Gao T, Zhang T, Xun J, Ma XT, et al. Osteoporosis risk and its association with all-cause and cause-specific mortality among the elderly: a 16-year nationwide cohort study. BMC Geriatr. 2025;25(1). https://doi.org/10.1186/s12877-025-05843-7.
- 29 Koh LK, Sedrine WB, Torralba TP, Kung A, Fujiwara S, Chan SP, et al. A simple tool to identify Asian women at increased risk of osteoporosis. Osteoporos Int. 2001;12(8):699-705.https://doi.org/10.1007/s001980170070.
- 30 Que Z, Lin Y, Chen D, Xiao K, Xu W, Sun N, et al. The association between osteoporosis and frailty: a cross-sectional observational study and Mendelian randomization analysis. J Orthop Surg Res. 2024;19(1).https://doi.org/10.1186/s13018-024-04875-w. .
- 31 Hu Y, Xu H, Ji W, Yang J, Li H, Li K, et al. Prevalence of frailty in senile osteoporosis: a systematic review and meta-analysis. Arch Gerontol Geriatr. 2024;130:105718.https://doi.org/10.1016/j.archger.2024.105718 .
- 32 Zhang S, Zeng Z. Sarcopenia associated with all-cause mortality risk. J Coll Physicians Surg Pak. 2025;35(12):1536-1540. https://doi.org/10.29271/jcpsp.2025.12.1536.
- 33 Xu J, Wan CS, Ktoris K, Reijnierse EM, Maier AB. Sarcopenia is associated with mortality in adults: a systematic review and meta-analysis. Gerontology. 2022;68(4):361-376. https://doi.org/10.1159/000517099.
- 34 Dudinskaya EN, Vorobyeva NM, Onuchina JS, Machekhina LV, Selezneva EV, Ovcharova LN, et al. The association of osteoporosis and geriatric syndromes in the elderly: data from the Russian epidemiological study EVKALIPT. Arch Osteoporos. 2023;18(1):30. https://doi.org/10.1007/s11657-023-01217-x.
- 35 Fierro-Marrero J, Reina-Varona Á, Paris-Alemany A, Touche RL. Frailty in geriatrics: a critical review with content analysis of instruments, overlapping constructs, and challenges in diagnosis and prognostic precision. J Clin Med. 2025;14(6):1808. https://doi.org/10.3390/jcm14061808.
