Skip to content
naulon

No retraction, correction or concern found when last checked on Oct 17, 2026.

Global Incidence of Frailty and Prefrailty Among Community-Dwelling Older Adults

Richard Ofori-Asenso, Ken L. Chin, Mohsen Mazidi and 9 more

JAMA Network Open · 2019 · Meta-analysis

doi:10.1001/jamanetworkopen.2019.8398

Abstract

Question. What is the incidence of frailty and prefrailty among community-dwelling adults 60 years or older?

Findings. In this systematic review and meta-analysis involving data from more than 120 000 older adults from 28 countries, the incidence of frailty and prefrailty was estimated as 43.4 and 150.6 new cases per 1000 person-years, respectively. The frailty and prefrailty incidence rates varied by sex, diagnostic criteria, and country income level.

Meaning. Results of this study suggest that the risk of developing frailty and prefrailty is high among community-living older adults; as such, appropriate interventions are needed.

Importance. Frailty is a common geriatric syndrome of significant public health importance, yet there is limited understanding of the risk of frailty development at a population level.

Objective. To estimate the global incidence of frailty and prefrailty among community-dwelling adults 60 years or older.

Data Sources. MEDLINE, Embase, PsycINFO, Web of Science, CINAHL Plus, and AMED (Allied and Complementary Medicine Database) were searched from inception to January 2019 without language restrictions using combinations of the keywords frailty, older adults, and incidence. The reference lists of eligible studies were hand searched.

Study Selection. In the systematic review, 2 authors undertook the search, article screening, and study selection. Cohort studies that reported or had sufficient data to compute incidence of frailty or prefrailty among community-dwelling adults 60 years or older at baseline were eligible.

Data Extraction and Synthesis. The methodological quality of included studies was assessed using The Joanna Briggs Institute’s Critical Appraisal Checklist for Prevalence and Incidence Studies. Meta-analysis was conducted using a random-effects (DerSimonian and Laird) model.

Main Outcomes and Measures. Incidence of frailty (defined as new cases of frailty among robust or prefrail individuals) and incidence of prefrailty (defined as new cases of prefrailty among robust individuals), both over a specified duration.

Results. Of 15 176 retrieved references, 46 observational studies involving 120 805 nonfrail (robust or prefrail) participants from 28 countries were included in this systematic review. Among the nonfrail individuals who survived a median follow-up of 3.0 (range, 1.0-11.7) years, 13.6% (13 678 of 100 313) became frail, with the pooled incidence rate being 43.4 (95% CI, 37.3-50.4; I2 = 98.5%) cases per 1000 person-years. The incidence of frailty was significantly higher in prefrail individuals than robust individuals (pooled incidence rates, 62.7 [95% CI, 49.2-79.8; I2 = 97.8%] vs 12.0 [95% CI, 8.2-17.5; I2 = 94.9%] cases per 1000 person-years, respectively; P for difference <.001). Among robust individuals in 21 studies who survived a median follow-up of 2.5 (range, 1.0-10.0) years, 30.9% (9974 of 32 268) became prefrail, with the pooled incidence rate being 150.6 (95% CI, 123.3-184.1; I2 = 98.9%) cases per 1000 person-years. The frailty and prefrailty incidence rates were significantly higher in women than men (frailty: 44.8 [95% CI, 36.7-61.3; I2 = 97.9%] vs 24.3 [95% CI, 19.6-30.1; I2 = 8.94%] cases per 1000 person-years; prefrailty: 173.2 [95% CI, 87.9-341.2; I2 = 99.1%] vs 129.0 [95% CI, 73.8-225.0; I2 = 98.5%] cases per 1000 person-years). The incidence rates varied by diagnostic criteria and country income level. The frailty and prefrailty incidence rates were significantly reduced when accounting for the risk of death.

Conclusions and Relevance. Results of this study suggest that community-dwelling older adults are prone to developing frailty. Increased awareness of the factors that confer high risk of frailty in this population subgroup is vital to inform the design of interventions to prevent frailty and to minimize its consequences.

Full text

From PubMed Central, U.S. National Library of Medicine, as current on Oct 17, 2026. Paragraph numbers are ours, so an answer can point at one.

Introduction

The increasing average life expectancy has contributed to aging of the world’s population. By 2050, approximately 21.3% of the global population will be 60 years or older, up from 9.2% in 1990. Frailty, a clinical syndrome characterized by marked vulnerability due to decline in reserve and function across multiple physiologic systems, is common among older people., Frailty manifests as the inability to tolerate stressful events and has been associated with adverse outcomes, such as falls, delirium, institutionalization, incident disability, and mortality. Frailty is also an independent risk factor for poor outcomes after surgery (eg, prolonged hospitalizations, increased susceptibility to deconditioning, and faster functional decline) and is associated with higher health care use and corresponding costs. There is a growing interest among stakeholders in aged care to better understand the patterns and determinants of frailty.

Frailty is difficult to diagnose, particularly within primary care settings, due to its coexistence with other age-related conditions and as a result of the lack of a universally accepted clinical definition., There is also debate about frailty screening, especially in relation to screening eligibility, as well as where and when it should be done.

Frailty phenotype and deficit accumulation are 2 main approaches to frailty assessment. Using the phenotype approach, Fried et al defined frailty as a predominantly physical condition requiring the presence of 3 or more of the following 5 components: weight loss, exhaustion, weakness, slowness, and low physical activity. However, Rockwood et al characterized frailty as an accumulation of deficits (symptoms, signs, functional impairment, and laboratory abnormalities) and stipulated that more deficits confer greater risk. These 2 frailty conceptualizations have been extensively validated and are widely used. Beyond these conceptualizations of frailty, several other definitions are present in the literature. Many definitions consider frailty to be a dynamic process with an identifiable intermediate stage, usually referred to as prefrailty.

Since 2000, frailty-related research has increased exponentially. Nonetheless, the epidemiological evidence on frailty is dominated by a focus on prevalence. Incidence remains poorly understood. Although Galluzzo et al previously performed a systematic review on frailty incidence, their analysis focused on European ADVANTAGE Joint Action countries and included 6 studies, with no meta-analysis performed. With a growing worldwide interest in healthy aging, improved understanding of the incidence of frailty may help deepen the discourse around the maintenance of functional ability in old age. Therefore, we conducted a systematic review and meta-analysis to summarize the available global epidemiological data on the incidence of frailty and prefrailty among community-dwelling adults 60 years or older.

Methods

This systematic review and meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) and Meta-analysis of Observational Studies in Epidemiology (MOOSE) reporting guidelines. The study protocol is registered at PROSPERO (CRD42019121302).

Study Eligibility Criteria

Two of us (R.O-A. and K.L.C) independently determined study eligibility, and any disagreements were resolved via consensus involving a third reviewer (D. Liew). The inclusion criteria were cohort studies that reported or had sufficient data to compute incidence of frailty or prefrailty among community-dwelling adults 60 years or older at baseline. Frailty status was considered categorically as robust, prefrail, or frail. Frailty could have been diagnosed by any method, but studies needed to specify their definition. For the Fried phenotype, individuals are often classified as robust, prefrail, or frail if 0, 1 to 2, or 3 or more of the criteria (ie, weight loss, exhaustion, weakness, slowness, and low physical activity) are met, respectively. For the deficit accumulation approach, the definitions of robust, prefrail, and frail were as specified by study authors, as has been done previously., Incidence of frailty was defined as new cases of frailty among robust or prefrail individuals, and incidence of prefrailty was defined as new cases of prefrailty among robust individuals, both over a specified duration. When multiple studies used the same cohort, the study with the most complete data on the largest number of participants was selected.

Exclusion criteria included studies focusing on institutionalized or hospitalized adults, residents of nursing homes (because these populations are often predominantly frail), or populations selected on the basis of an index disease. Studies reporting the mean frailty scores but without data on incidence were excluded, as were randomized clinical trials. Studies of individuals across the life span were excluded unless data were specifically available for those 60 years or older at baseline.

Search and Selection of Studies

In the systematic review, 2 of us (R.O-A. and K.L.C.) undertook the search, article screening, and study selection. MEDLINE, Embase, PsycINFO, Web of Science, CINAHL Plus, and AMED (Allied and Complementary Medicine Database) were searched from inception to January 2019 without language restrictions using combinations of the keywords frailty, older adults, and incidence. eTable 1 in the Supplement lists the search terms and strategy for MEDLINE (via Ovid), which were adapted for other databases. The reference lists of eligible studies were hand searched. Conference abstracts, editorials, and meeting reports were excluded.

Study Quality Assessment and Data Extraction

Two of us (R.O-A. and K.L.C.) evaluated each included study for methodological quality using The Joanna Briggs Institute’s Critical Appraisal Checklist for Prevalence and Incidence Studies. This checklist consists of 9 criteria, and studies were ineligible if fewer than 5 of the criteria were achieved.

The following information was collected from individual articles: study details (authors, year of publication, country, and study name), participant characteristics (sample size and percentage of women), frailty measurement method, duration of follow-up, and incidence data. Sex-stratified or age-stratified incidence data were collected, where available. Authors were contacted for additional data or clarification, when required.

Statistical Analysis

For each study, we recorded or calculated incidence rates of frailty or prefrailty per 1000 person-years based on the event rates and the mean duration of follow-up.,,, Exact methods according to the Poisson distribution were adopted to calculate 95% CIs for incidence rates. There were 2 kinds of studies, including (1) those that used a 100% survivor cohort (ie, assessed frailty status at 2 time points, excluding persons who died in-between) and (2) those that accounted for people in the cohort who died without developing frailty. Therefore, to improve the comparability of these 2 types of studies, as well as to minimize the consequences of survivorship bias, we recalculated the incidence rate in the latter studies (ie, studies that reported transition to deaths) by restricting the sample to the surviving cohort with frailty data.,

A random-effects (DerSimonian and Laird) meta-analysis was conducted using the log-transformed incidence rates and corresponding 95% CIs. The random-effects model was selected a priori due to the anticipated heterogeneity of the included studies. Statistical evidence of between-study heterogeneity was examined using the Cochran Q test and the I2 statistic. I2 values of 25%, 50%, and 75% were considered to be low, moderate, and high degrees of heterogeneity, respectively. The robustness of pooled estimates were assessed via leave-1-out sensitivity analyses. A study was considered to be influential if the pooled estimate without it was not within the 95% CIs of the overall pooled estimate. Sex-specific incidence data were pooled, as were the incidence rates by assessment method. To examine the extent to which the pooled incidence rates were explained by these factors, we also performed random-effects meta-regression using the following variables: measurement method (physical phenotype vs other), country income level (lower-income and middle-income country [LMIC] vs high-income country [HIC]), study region (North America, Europe, Asia, or other), person-years of follow-up (per unit increase), whether the study enrolled only elderly people 70 years or older (no vs yes), study population (mix, female only, or male only), and publication years (2009 or earlier, 2010 to 2014, or 2015 to 2019). The HICs were defined as any country with a gross national income per capita in 2017 of US $12 056 or more. Differences between subgroups were compared via a χ2 test. Publication bias was assessed via visual inspection of funnel plots, and statistical assessment was evaluated using the Egger test.

To provide context of the burden of frailty, data on the proportion of older adults who were nonfrail were pooled using the respective study baseline data, if reported. The meta-analysis was performed using the Freeman-Tukey double arcsine transformed proportions to stabilize the variance.

All analyses were performed using statistical software (Stata, version 15.0/IC; StataCorp LP). Two-tailed P <.05 was considered statistically significant.

Selection Process

Of 15 176 retrieved citations, 142 articles were selected for full-text assessment (Figure 1). After full-text evaluation, 42 studies met the eligibility criteria. Four additional studies were retrieved by reference screening, resulting in a total of 46 studies (involving 48 cohorts) included in the systematic review. No study was excluded on the basis of The Joanna Briggs Institute methodological review.

Study Characteristics

The characteristics of the 46 included studies are summarized in Table 1. The studies involved 120 805 nonfrail (robust or prefrail) older adults from 28 countries. Nine studies were from Asia, 14 from North America, 2 from South America, 15 from Europe, and 4 from Australia, and 2 were cross-regional studies. eFigure 1 in the Supplement shows the geographical spread of the countries where data were collected. The median sample size across studies was 1054 (range, 44-28 181), and the median follow-up was 3.0 (range, 1.0-11.7) years. In 30 studies involving 101 259 participants, 73.3% were women. Frailty was assessed using the original or modified versions of the Fried criteria in 39 studies, 4 studies used the Frailty Index, and 1 study used both the Frailty Index and the Fried criteria, whereas 2 studies used other criteria. Among the studies using the deficit accumulation approach, the number of deficits used ranged from 20 to 44.

In 31 studies, data on baseline proportion of older adults without frailty were available. In these studies, involving 118 411 individuals at baseline, the pooled proportion without frailty was 82.8% (95% CI, 75.8%-88.8%; I2 = 99.8%). The pooled proportion that was nonfrail was 86.5% (95% CI, 78.9%-92.7%; I2 = 99.8%) across studies that used the Fried criteria and 58.9% (95% CI, 44.2%-72.8%; I2 = 99.6%) across studies that used other criteria (P for difference <.001).

Incidence of Frailty

To estimate the global incidence of frailty, data were included from 46 studies.,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, Among people without frailty at baseline who survived a median follow-up of 3.0 (range, 1.0-11.7) years, 13.6% (13 678 of 100 313) became frail. The pooled incidence rate of frailty was 43.4 (95% CI, 37.3-50.4; I2 = 98.5%) cases per 1000 person-years (Figure 2). There was no evidence of publication bias as determined by funnel plot visualization (eFigure 2 in the Supplement) or via the Egger test (P =.48). A leave-1-out sensitivity analysis did not show a dominance of any single study (eTable 2 in the Supplement).

The pooled frailty incidence rate was 40.0 (95% CI, 34.5-48.5; I2 = 98.2%) cases per 1000 person-years when using the Fried phenotype. The pooled frailty incidence rate was 71.3 (95% CI, 56.9-89.3; I2 = 94.0%) cases per 1000 person-years when using other criteria (P for difference =.003).

Among 20 studies that reported transitions to death, the proportion of nonfrail people who died over a median follow-up of 4.5 years was 12.9% (5989 of 46 358). When factoring in the risk of death, the pooled incidence rate of frailty was 35.9 (95% CI, 28.0-46.1; I2 = 98.7%) cases per 1000 person-years (eFigure 3 in the Supplement). Restricting the analyses to those who survived in these 19 studies resulted in a pooled frailty incidence rate of 44.1 (95% CI, 34.0-57.2; I2 = 98.8%) cases per 1000 person-years (eFigure 4 in the Supplement).

Twenty studies reported the incidence of frailty among 19 613 people who were prefrail and 17 523 people who were robust at baseline and who survived over a median follow-up of 3.0 years. During the follow-up, 4.6% (807 of 17 523) of individuals who were robust and 18.5% (3628 of 19 613) of individuals who were prefrail developed frailty. The pooled frailty incidence rates among the robust and prefrail individuals were 12.0 (95% CI, 8.2-17.5; I2 = 94.9%) and 62.7 (95% CI, 49.2-79.8; I2 = 97.8%) cases per 1000 person-years, respectively, with the difference being statistically significant (P value for difference <.001).

Ten studies directly compared frailty incidence between 11 959 men and 13 870 women who survived a median follow-up of 4.0 years. Among the men and women, 9.2% (1099 of 11 959) and 15.6% (2164 of 13 870), respectively, developed frailty. The pooled incidence rates of frailty in men and women in these studies were 24.3 (95% CI, 19.6-30.1; I2 = 89.4%) and 44.8 (95% CI, 36.7-61.3; I2 = 97.9%) cases per 1000 person-years, respectively, with the difference being statistically significant (P value for difference =.01).

Only 2 studies, reported age-stratified frailty incidence rate, with inconsistent age groups being used. Therefore, data were not pooled, although both studies reported consistent increases in frailty incidence with increasing age.

Incidence of Prefrailty

Twenty-one studies,,,,,,,,,,,,,,,,,,,, reported data on the global incidence of prefrailty among 32 268 community-dwelling older adults who were robust at baseline and survived a median follow-up of 2.5 (range, 1.0-10.0) years. During the follow-up, 30.9% (9974 of 32 268) became prefrail. The pooled incidence rate of prefrailty was 150.6 (95% CI, 123.3-184.1; I2 = 98.9%) cases per 1000 person-years (Figure 3). There was no evidence of publication bias as determined by visual inspection of funnel plots (eFigure 5 in the Supplement) or by means of the Egger test. A leave-1-out sensitivity analysis did not alter the results (eTable 3 in the Supplement).

The pooled incidence rate of prefrailty was 150.9 (95% CI, 120.2-182.6; I2 = 98.8%) cases per 1000 person-years when using the Fried phenotype. The pooled incidence rate of prefrailty was 140.4 (95% CI, 97.2-202.9; I2 = 93.4%) cases per 1000 person-years when using other criteria (P for difference =.52).

Among 13 studies that reported transitions to death, the proportion of robust people who died over a median follow-up of 4.0 years was 7.8% (1253 of 16 134). When factoring in the risk of death, the pooled incidence rate of prefrailty was 110.6 (95% CI, 84.8-144.2; I2 = 98.9%) cases per 1000 person-years (eFigure 6 in the Supplement). Restricting the analyses to those who survived in these 13 studies resulted in a pooled prefrailty incidence rate of 122.7 (95% CI, 95.7-157.5; I2 = 98.7%) cases per 1000 person-years (eFigure 7 in the Supplement).

Four studies directly compared incidence of prefrailty among 4003 men and 3655 women who survived a median follow-up of 4.2 years. In all, 32.6% (1305 of 4003) of the men and 40.1% (1465 of 3655) of the women became prefrail, at a pooled incidence rate of 129.0 (95% CI, 73.8-225.0; I2 = 98.5%) and 173.2 (95% CI, 87.9-341.2; I2 = 99.1%) cases per 1000 person-years, respectively (P for difference =.12). No study reported age-stratified prefrailty incidence data.

Meta-regression

In the multivariable random-effects meta-regression, measuring frailty as a physical phenotype was associated with higher incidence than using other methods (adjusted odds ratio [aOR], 1.48; 95% CI, 1.02-2.15), although no statistically significant difference was observed for prefrailty incidence (Table 2). Study region was not significantly associated with frailty and prefrailty incidence, but HICs were associated with a lower incidence of frailty (aOR, 0.63; 95% CI, 0.42-0.95) and prefrailty (aOR, 0.30; 95% CI, 0.21-0.84) compared with LMICs. Studies published after 2009 were associated with lower frailty incidence. The variables included in the multivariable models collectively explained about 63.9% and 38.1% of the between-study variance for frailty and prefrailty incidence, respectively.

Discussion

We performed a systematic review and meta-analysis to estimate the incidence of frailty and prefrailty among community-dwelling older adults. Our results indicate the following: (1) frailty and prefrailty incidence rates were approximately 43 and 151 new cases per 1000 person-years, respectively; (2) the incidence of frailty and prefrailty was higher in women than men; and (3) the incidence of frailty and prefrailty varied by frailty measurement method used and by country income level.

Although not necessarily synonymous with aging, frailty is highly prevalent among older people., Our pooled baseline data suggested that approximately 1 in 6 community-dwelling older people may have frailty. Frailty has been associated with adverse health outcomes, such as falls, disability, and death, as well as increased use of health care resources.,, Therefore, efforts to reduce the burden of frailty could have substantial public health consequences.

Prevention of frailty requires a sound understanding of the risk factors. For example, it has been demonstrated that individual chronic diseases (eg, cancers, type 2 diabetes,,, and depression,,, or their co-occurrence [ie, multimorbidity]) have been shown to increase the risk of frailty., With an estimated 66% of older people having at least 2 chronic medical conditions, effective preventive strategies are paramount to reduce overall disease burden. The rising prevalence of obesity among older adults, needs greater attention because this condition, particularly abdominal obesity, may increase the risk of frailty through the association with proinflammatory processes, insulin resistance, fat infiltration of skeletal muscles, and hormonal alterations., Many other sociodemographic, physical, biological, lifestyle (eg, smoking), and psychological factors may equally contribute to the development of frailty and thus require tailored solutions in different settings.,,,

We found a higher incidence of frailty and prefrailty in LMICs than HICs in our study, which is consistent with prior observations of significantly higher prevalence of frailty and prefrailty in LMICs compared with HICs. Some studies,, found that high income and educational levels and greater access to and quality of health care confer lower frailty risk, which may partly explain the disparity in frailty incidence between LMICs and HICs, presenting opportunity to prevent or delay the onset of chronic pathologies associated with increased risk of frailty.,

Our meta-analysis suggests higher incidence of frailty and prefrailty in women than men. Previous studies have shown consistently higher prevalence rates, and frailty scores among women than men across all age groups. The sex differences may be attributable to both biological and socioeconomic factors. Nonetheless, women have been found to better tolerate frailty, as evidenced by lower mortality rates at any frailty level or age, suggesting the existence of a male-female health-survival paradox.

To date, several interventions incorporating exercise, nutrition, cognitive training, geriatric assessment, hormone therapy, and management and prehabilitation have been evaluated for their effectiveness at delaying or reversing frailty.,,,, Most of these interventions have demonstrated feasibility, with adherence rates of about 70%. However, a recent systematic review reported that, among the available primary care interventions to delay or reverse frailty, strength training and protein supplementation ranked highest in terms of relative effectiveness and ease of implementation. Conversely, mild-intensity mixed exercises, as well as educational or health promotion activities, typically were in the midzone for both relative effectiveness and ease of implementation, whereas comprehensive geriatric assessments and home visits were ranked mid to low for both relative effectiveness and ease of implementation. In general, interventions targeting behavioral change ranked low in relative effectiveness and at the midzone for ease of implementation. However, it needs emphasizing that most interventions have been tested in people who were frail or prefrail., Our meta-analysis showed that, among people who were robust, there were approximately 12 and 151 new cases of frailty and prefrailty per 1000 person-years, respectively, suggesting that interventions aimed at preventing frailty and prefrailty in robust populations could be important.

The lower pooled incidence when frailty was defined as a physical phenotype compared with when a broad phenotype was used is consistent with prior meta-analyses that have demonstrated higher frailty prevalence when using broad definitions vs the physical phenotype., Other studies have shown considerable variability in the literature regarding the use of the deficit accumulation approach (as also observed in the present study), thus contributing to wide estimates of frailty burden. Therefore, a harmonized definition of frailty may be useful.

Limitations and Future Directions

Our study had some limitations. There was substantial heterogeneity of the included studies. Nonetheless, heterogeneity is often inevitable in meta-analyses of observational studies, and it does not necessarily invalidate the findings. We decided a priori to pool incidence data across studies that met our inclusion criteria. Furthermore, potential sources of heterogeneity were investigated via subgroup and random-effects meta-regression, which showed considerable heterogeneity in incidence rates by frailty measurement method, country income level, and publication years of studies. Meta-analysis of incidence data is also complicated by variable duration of follow-up. We sought to overcome this by estimating person-years on the basis of the median follow-up duration. While this method is considered robust and is widely applied in the literature,,,, a more precise approach would have required the use of the actual data on person-years, which were unavailable in more than 90% of studies. While frailty incidence varies by age, we could not perform age-stratified analysis due to limited data, and we were unable to account for the influence of the mean age of participants in the individual studies in the regression models due to poor reporting. People who develop frailty or prefrailty may regress,; however, the present analysis does not incorporate regression rates. Finally, our abstract screening may have missed relevant studies in which frailty was not the main focus, but which contained information on the incidence of frailty (eg, frailty as a covariate).

Overall, the study results reiterate the need for regular screening programs to assess older people’s vulnerability to frailty development so that appropriate interventions can be implemented in a timely manner. For example, frailty assessment could be considered as part of routine health screening or could be instituted as a part of the core services delivered to older people within primary health care and general practice settings. Because not all older people develop frailty, future studies should examine protective factors against frailty so as to inform preventive strategies. Our data could also inform health care planning and design of preventive strategies. However, the inequality in the availability of frailty data according to geographical locations requires attention because it hampers the opportunity to reliably forecast the future trajectory of the global burden of frailty, which is needed to inform efficient planning and resource allocation, mindful of the growing aging population.

Conclusions

There is a high risk of frailty among community-dwelling older adults, and we observed that the incidence of frailty varies by sex, region, country income level, and diagnostic criteria used. It is imperative to improve understanding of the factors that confer increased risk of frailty. This will help inform the design of interventions to prevent frailty or minimize its negative consequences on health.

References 109

  1. 1.

    Sander M, Oxlund B, Jespersen A, The challenges of human population ageing. Age Ageing. 2015;44(2):-

    Not in our library10.1093/ageing/afu189

  2. 2.

    United Nations Department of Economic and Social Affairs (DESA)/Population Division World Population Prospects 2019. https://population.un.org/wpp/Download/Standard/Population/. Accessed January 26, 2019.

    Not in our library

  3. 3.

    Collard RM, Boter H, Schoevers RA, Oude Voshaar RC Prevalence of frailty in community-dwelling older persons: a systematic review. J Am Geriatr Soc. 2012;60(8):1487-1492

    Not in our library10.1111/j.1532-5415.2012.04054.x

  4. 4.

    Clegg A, Young J, Iliffe S, Rikkert MO, Rockwood K Frailty in elderly people. Lancet. 2013;381(9868):752-762

    Not in our library10.1016/s0140-6736(12)62167-9

  5. 5.

    Cheng MH, Chang SF Frailty as a risk factor for falls among community dwelling people: evidence from a meta-analysis. J Nurs Scholarsh. 2017;49(5):529-536

    Not in our library10.1111/jnu.12322

  6. 6.

    Persico I, Cesari M, Morandi A, Frailty and delirium in older adults: a systematic review and meta-analysis of the literature. J Am Geriatr Soc. 2018;66(10):2022-2030

    Not in our library10.1111/jgs.15503

  7. 7.

    Kojima G Frailty as a predictor of nursing home placement among community-dwelling older adults: a systematic review and meta-analysis. J Geriatr Phys Ther. 2018;41(1):42-48

    Not in our library10.1519/jpt.0000000000000097

  8. 8.

    Kojima G Frailty as a predictor of disabilities among community-dwelling older people: a systematic review and meta-analysis. Disabil Rehabil. 2017;39(19):1897-1908

    Not in our library10.1080/09638288.2016.1212282

  9. 9.

    Kojima G, Iliffe S, Walters K Frailty Index as a predictor of mortality: a systematic review and meta-analysis. Age Ageing. 2018;47(2):193-200

    Not in our library10.1093/ageing/afx162

  10. 10.
  11. 11.

    Kojima G Frailty as a predictor of emergency department utilization among community-dwelling older people: a systematic review and meta-analysis. J Am Med Dir Assoc. 2019;20(1):103-105

    Not in our library10.1016/j.jamda.2018.10.004

  12. 12.
  13. 13.

    Gwyther H, Shaw R, Jaime Dauden EA, Understanding frailty: a qualitative study of European healthcare policy-makers’ approaches to frailty screening and management. BMJ Open. 2018;8(1):e018653

    Not in our library10.1136/bmjopen-2017-018653

  14. 14.

    Morley JE Frailty: diagnosis and management. J Nutr Health Aging. 2011;15(8):667-670

    Not in our library10.1007/s12603-011-0338-4

  15. 15.
  16. 16.

    Ambagtsheer RC, Beilby JJ, Visvanathan R, Dent E, Yu S, Braunack-Mayer AJ Should we screen for frailty in primary care settings? a fresh perspective on the frailty evidence base: a narrative review. Prev Med. 2019;119:63-69

    Not in our library10.1016/j.ypmed.2018.12.020

  17. 17.

    Fried LP, Tangen CM, Walston J,; Cardiovascular Health Study Collaborative Research Group Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001;56(3):M146-M156

    Not in our library10.1093/gerona/56.3.m146

  18. 18.

    Rockwood K, Stadnyk K, MacKnight C, McDowell I, Hébert R, Hogan DB A brief clinical instrument to classify frailty in elderly people. Lancet. 1999;353(9148):205-206

    Not in our library10.1016/s0140-6736(98)04402-x

  19. 19.

    Dent E, Kowal P, Hoogendijk EO Frailty measurement in research and clinical practice: a review. Eur J Intern Med. 2016;31:3-10

    Not in our library10.1016/j.ejim.2016.03.007

  20. 20.

    Lang PO, Michel JP, Zekry D Frailty syndrome: a transitional state in a dynamic process. Gerontology. 2009;55(5):539-549

    Not in our library10.1159/000211949

  21. 21.

    Galluzzo L, O’Caoimh R, Rodríguez-Laso Á,; Work Package 5 of the Joint Action ADVANTAGE Incidence of frailty: a systematic review of scientific literature from a public health perspective. Ann Ist Super Sanita. 2018;54(3):239-245.

    Not in our library10.4415/ann_18_03_11

  22. 22.

    Kaeberlein M, Rabinovitch PS, Martin GM Healthy aging: the ultimate preventative medicine. Science. 2015;350(6265):1191-1193

    Not in our library10.1126/science.aad3267

  23. 23.

    Moher D, Liberati A, Tetzlaff J, Altman DG; PRISMA Group Preferred Reporting Items for Systematic Reviews and Meta-analyses: the PRISMA statement. BMJ. 2009;339:b2535

    Not in our library10.1136/bmj.b2535

  24. 24.

    Stroup DF, Berlin JA, Morton SC,; Meta-analysis of Observational Studies in Epidemiology (MOOSE) Group. Meta-analysis of Observational Studies in Epidemiology: a proposal for reporting. JAMA. 2000;283(15):2008-2012

    Not in our library10.1001/jama.283.15.2008

  25. 25.

    PROSPERO Incidence of Frailty Among Community-Dwelling Older Adults. CRD42019121302. https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=121302. Accessed January 26, 2019.

    Not in our library

  26. 26.

    Xue QL The frailty syndrome: definition and natural history. Clin Geriatr Med. 2011;27(1):1-15

    Not in our library10.1016/j.cger.2010.08.009

  27. 27.

    Ofori-Asenso R, Lee Chin K, Mazidi M, Natural regression of frailty among community-dwelling older adults: a systematic review and meta-analysis. Gerontologist. 2019;gnz064

    Not in our library10.1093/geront/gnz064

  28. 28.

    Aguayo GA, Donneau AF, Vaillant MT, Agreement between 35 published frailty scores in the general population. Am J Epidemiol. 2017;186(4):420-434

    Not in our library10.1093/aje/kwx061

  29. 29.

    Kojima G Prevalence of frailty in nursing homes: a systematic review and meta-analysis. J Am Med Dir Assoc. 2015;16(11):940-945

    Not in our library10.1016/j.jamda.2015.06.025

  30. 30.

    Munn Z, Moola S, Lisy K, Riitano D, Tufanaru C Methodological guidance for systematic reviews of observational epidemiological studies reporting prevalence and cumulative incidence data. Int J Evid Based Healthc. 2015;13(3):147-153

    Not in our library10.1097/xeb.0000000000000054

  31. 31.

    Sikkema M, de Jonge PJ, Steyerberg EW, Kuipers EJ Risk of esophageal adenocarcinoma and mortality in patients with Barrett’s esophagus: a systematic review and meta-analysis. Clin Gastroenterol Hepatol. 2010;8(3):235-244

    Not in our library10.1016/j.cgh.2009.10.010

  32. 32.

    Tansel A, Katz LH, El-Serag HB, Incidence and determinants of hepatocellular carcinoma in autoimmune hepatitis: a systematic review and meta-analysis. Clin Gastroenterol Hepatol. 2017;15(8):1207-1217.e4

    Not in our library10.1016/j.cgh.2017.02.006

  33. 33.

    Yousef F, Cardwell C, Cantwell MM, Galway K, Johnston BT, Murray L The incidence of esophageal cancer and high-grade dysplasia in Barrett’s esophagus: a systematic review and meta-analysis. Am J Epidemiol. 2008;168(3):237-249

    Not in our library10.1093/aje/kwn121

  34. 34.

    Sutton A, Abrams K, Jones D, Sheldon T, Song F Methods for Meta-analysis in Medical Research. London, United Kingdom: Wiley; 2000.

    Not in our library

  35. 35.

    Delgado-Rodríguez M, Llorca J Bias. J Epidemiol Community Health. 2004;58(8):635-641

    Not in our library10.1136/jech.2003.008466

  36. 36.

    Kojima G, Taniguchi Y, Iliffe S, Jivraj S, Walters K Transitions between frailty states among community-dwelling older people: a systematic review and meta-analysis. Ageing Res Rev. 2019;50:81-88

    Not in our library10.1016/j.arr.2019.01.010

  37. 37.

    Higgins JP, Thompson SG, Deeks JJ, Altman DG Measuring inconsistency in meta-analyses. BMJ. 2003;327(7414):557-560

    Not in our library10.1136/bmj.327.7414.557

  38. 38.

    World Bank World Bank country and lending groups. https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups. Published 2019. Accessed January 29, 2019.

    Not in our library

  39. 39.

    Egger M, Davey Smith G, Schneider M, Minder C Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315(7109):629-634

    Not in our library10.1136/bmj.315.7109.629

  40. 40.

    Barendregt JJ, Doi SA, Lee YY, Norman RE, Vos T Meta-analysis of prevalence. J Epidemiol Community Health. 2013;67(11):974-978

    Not in our library10.1136/jech-2013-203104

  41. 41.

    Ahmad NS, Hairi NN, Said MA, Prevalence, transitions and factors predicting transition between frailty states among rural community-dwelling older adults in Malaysia. PLoS One. 2018;13(11):e0206445

    Not in our library10.1371/journal.pone.0206445

  42. 42.

    Alencar MA, Dias JMD, Figueiredo LC, Dias RC Transitions in frailty status in community-dwelling older adults. Top Geriatr Rehabil. 2015;31(2):105-112

    Not in our library10.1097/tgr.0000000000000055

  43. 43.

    Ayers E, Shapiro M, Holtzer R, Barzilai N, Milman S, Verghese J Symptoms of apathy independently predict incident frailty and disability in community-dwelling older adults. J Clin Psychiatry. 2017;78(5):e529-e536

    Not in our library10.4088/jcp.15m10113

  44. 44.

    Baulderstone L, Yaxley A, Luszcz M, Miller M Diet liberalisation in older Australians decreases frailty without increasing the risk of developing chronic disease. J Frailty Aging. 2012;1(4):174-182.

    Not in our library10.14283/jfa.2012.27

  45. 45.

    Bentur N, Sternberg SA, Shuldiner J Frailty transitions in community dwelling older people. Isr Med Assoc J. 2016;18(8):449-453.

    Not in our library

  46. 46.

    Borrat-Besson C, Ryser V, Wernli B Transitions between frailty states: a European comparison In: Börsch-Supan A, Brandt M, Litwin H, Weber G, eds. Active Ageing and Solidarity Between Generations in Europe: First Results From SHARE After the Economic Crisis. Gottingen, Germany: Hubert & Co; 2013:175-185

    Not in our library10.1515/9783110295467.175

  47. 47.

    Castrejón-Pérez RC, Jiménez-Corona A, Bernabé E, Oral disease and 3-year incidence of frailty in Mexican older adults. J Gerontol A Biol Sci Med Sci. 2017;72(7):951-957.

    Not in our library10.1093/gerona/glw201

  48. 48.

    Chhetri JK, Zheng Z, Xu X, Ma C, Chan P The prevalence and incidence of frailty in pre-diabetic and diabetic community-dwelling older population: results from Beijing Longitudinal Study of Aging II (BLSA-II). BMC Geriatr. 2017;17(1):47

    Not in our library10.1186/s12877-017-0439-y

  49. 49.

    Dalrymple LS, Katz R, Rifkin DE, Kidney function and prevalent and incident frailty. Clin J Am Soc Nephrol. 2013;8(12):2091-2099

    Not in our library10.2215/cjn.02870313

  50. 50.

    Doba N, Tokuda Y, Goldstein NE, Kushiro T, Hinohara S A pilot trial to predict frailty syndrome: the Japanese Health Research Volunteer Study. Exp Gerontol. 2012;47(8):638-643

    Not in our library10.1016/j.exger.2012.05.016

  51. 51.

    Doi T, Makizako H, Tsutsumimoto K, Transitional status and modifiable risk of frailty in Japanese older adults: a prospective cohort study. Geriatr Gerontol Int. 2018;18(11):1562-1566

    Not in our library10.1111/ggi.13525

  52. 52.

    Ensrud KE, Ewing SK, Fredman L,; Study of Osteoporotic Fractures Research Group Circulating 25-hydroxyvitamin D levels and frailty status in older women. J Clin Endocrinol Metab. 2010;95(12):5266-5273

    Not in our library10.1210/jc.2010-2317

  53. 53.

    Espinoza SE, Jung I, Hazuda H Frailty transitions in the San Antonio Longitudinal Study of Aging. J Am Geriatr Soc. 2012;60(4):652-660

    Not in our library10.1111/j.1532-5415.2011.03882.x

  54. 54.

    Gale CR, Baylis D, Cooper C, Sayer AA Inflammatory markers and incident frailty in men and women: the English Longitudinal Study of Ageing. Age (Dordr). 2013;35(6):2493-2501

    Not in our library10.1007/s11357-013-9528-9

  55. 55.

    García-Esquinas E, José García-García F, León-Muñoz LM, Obesity, fat distribution, and risk of frailty in two population-based cohorts of older adults in Spain. Obesity (Silver Spring). 2015;23(4):847-855

    Not in our library10.1002/oby.21013

  56. 56.

    García-Esquinas E, Rahi B, Peres K, Consumption of fruit and vegetables and risk of frailty: a dose-response analysis of 3 prospective cohorts of community-dwelling older adults. Am J Clin Nutr. 2016;104(1):132-142

    Not in our library10.3945/ajcn.115.125781

  57. 57.

    Gill TM, Gahbauer EA, Allore HG, Han L Transitions between frailty states among community-living older persons. Arch Intern Med. 2006;166(4):418-423

    Not in our library10.1001/archinte.166.4.418

  58. 58.

    Gnjidic D, Hilmer SN, Blyth FM, High-risk prescribing and incidence of frailty among older community-dwelling men. Clin Pharmacol Ther. 2012;91(3):521-528

    Not in our library10.1038/clpt.2011.258

  59. 59.

    Gomes CDS, Guerra RO, Wu YY, Social and economic predictors of worse frailty status occurrence across selected countries in North and South America and Europe. Innov Aging. 2018;2(3):igy037

    Not in our library10.1093/geroni/igy037

  60. 60.

    Gruenewald TL, Seeman TE, Karlamangla AS, Sarkisian CA Allostatic load and frailty in older adults. J Am Geriatr Soc. 2009;57(9):1525-1531

    Not in our library10.1111/j.1532-5415.2009.02389.x

  61. 61.

    Hyde Z, Flicker L, Smith K, Prevalence and incidence of frailty in Aboriginal Australians, and associations with mortality and disability. Maturitas. 2016;87:89-94

    Not in our library10.1016/j.maturitas.2016.02.013

  62. 62.

    Iwasaki M, Yoshihara A, Sato M, Dentition status and frailty in community-dwelling older adults: a 5-year prospective cohort study. Geriatr Gerontol Int. 2018;18(2):256-262

    Not in our library10.1111/ggi.13170

  63. 63.

    Kalyani RR, Tian J, Xue QL, Hyperglycemia and incidence of frailty and lower extremity mobility limitations in older women. J Am Geriatr Soc. 2012;60(9):1701-1707

    Not in our library10.1111/j.1532-5415.2012.04099.x

  64. 64.

    Kim M, Suzuki T, Kojima N, Association between serum β2-microglobulin levels and prevalent and incident physical frailty in community-dwelling older women. J Am Geriatr Soc. 2017;65(4):e83-e88

    Not in our library10.1111/jgs.14733

  65. 65.

    Lanziotti Azevedo da Silva S, Campos Cavalcanti Maciel Á, de Sousa Máximo Pereira L, Domingues Dias JM, Guimarães de Assis M, Corrêa Dias R Transition patterns of frailty syndrome in community-dwelling elderly individuals: a longitudinal study. J Frailty Aging. 2015;4(2):50-55.

    Not in our library10.14283/jfa.2015.43

  66. 66.

    Lee JSW, Auyeung TW, Leung J, Kwok T, Woo J Transitions in frailty states among community-living older adults and their associated factors. J Am Med Dir Assoc. 2014;15(4):281-286

    Not in our library10.1016/j.jamda.2013.12.002

  67. 67.

    Liu ZY, Wei YZ, Wei LQ, Frailty transitions and types of death in Chinese older adults: a population-based cohort study. Clin Interv Aging. 2018;13:947-956

    Not in our library10.2147/cia.s157089

  68. 68.

    Lorenzo-López L, López-López R, Maseda A, Buján A, Rodríguez-Villamil JL, Millán-Calenti JC Changes in frailty status in a community-dwelling cohort of older adults: the VERISAÚDE study. Maturitas. 2019;119:54-60

    Not in our library10.1016/j.maturitas.2018.11.006

  69. 69.

    Ottenbacher KJ, Graham JE, Al Snih S, Mexican Americans and frailty: findings from the Hispanic established populations epidemiologic studies of the elderly. Am J Public Health. 2009;99(4):673-679

    Not in our library10.2105/ajph.2008.143958

  70. 70.

    Pilleron S, Ajana S, Jutand MA, Dietary patterns and 12-year risk of frailty: results from the Three-City Bordeaux Study. J Am Med Dir Assoc. 2017;18(2):169-175

    Not in our library10.1016/j.jamda.2016.09.014

  71. 71.

    Pollack LR, Litwack-Harrison S, Cawthon PM, Patterns and predictors of frailty transitions in older men: the Osteoporotic Fractures in Men Study. J Am Geriatr Soc. 2017;65(11):2473-2479

    Not in our library10.1111/jgs.15003

  72. 72.

    Potier F, Degryse JM, Bihin B, Health and frailty among older spousal caregivers: an observational cohort study in Belgium. BMC Geriatr. 2018;18(1):291

    Not in our library10.1186/s12877-018-0980-3

  73. 73.
  74. 74.

    Sandoval-Insausti H, Pérez-Tasigchana RF, López-García E, García-Esquinas E, Rodríguez-Artalejo F, Guallar-Castillón P Macronutrients intake and incident frailty in older adults: a prospective cohort study. J Gerontol A Biol Sci Med Sci. 2016;71(10):1329-1334

    Not in our library10.1093/gerona/glw033

  75. 75.

    Saum KU, Schöttker B, Meid AD, Is polypharmacy associated with frailty in older people? results from the ESTHER cohort study. J Am Geriatr Soc. 2017;65(2):e27-e32

    Not in our library10.1111/jgs.14718

  76. 76.

    Semba RD, Bartali B, Zhou J, Blaum C, Ko CW, Fried LP Low serum micronutrient concentrations predict frailty among older women living in the community. J Gerontol A Biol Sci Med Sci. 2006;61(6):594-599

    Not in our library10.1093/gerona/61.6.594

  77. 77.

    Serra-Prat M, Papiol M, Vico J, Palomera E, Arús M, Cabré M Incidence and risk factors for frailty in the community-dwelling elderly population: a two-year follow-up cohort study. J Gerontol Geriatr Res. 2017;6(6):452

    Not in our library10.4172/2167-7182.1000452

  78. 78.

    Shah M, Paulson D, Nguyen V Alcohol use and frailty risk among older adults over 12 years: the Health and Retirement Study. Clin Gerontol. 2018;41(4):315-325

    Not in our library10.1080/07317115.2017.1364681

  79. 79.

    Stephan AJ, Strobl R, Holle R, Male sex and poverty predict abrupt health decline: deficit accumulation patterns and trajectories in the KORA-Age cohort study. Prev Med. 2017;102:31-38

    Not in our library10.1016/j.ypmed.2017.06.032

  80. 80.

    Swiecicka A, Eendebak RJAH, Lunt M,; European Male Ageing Study Group Reproductive hormone levels predict changes in frailty status in community-dwelling older men: European Male Ageing Study prospective data. J Clin Endocrinol Metab. 2018;103(2):701-709

    Not in our library10.1210/jc.2017-01172

  81. 81.

    Thompson MQ, Theou O, Adams RJ, Tucker GR, Visvanathan R Frailty state transitions and associated factors in South Australian older adults. Geriatr Gerontol Int. 2018;18(11):1549-1555

    Not in our library10.1111/ggi.13522

  82. 82.

    Tom S, Wyman A, Woods N, Regional differences in incident prefrailty and frailty. J Womens Health (Larchmt). 2017;26(9):992-998

    Not in our library10.1089/jwh.2016.6041

  83. 83.

    Trevisan C, Veronese N, Maggi S, Marital status and frailty in older people: gender differences in the Progetto Veneto Anziani longitudinal study. J Womens Health (Larchmt). 2016;25(6):630-637

    Not in our library10.1089/jwh.2015.5592

  84. 84.
  85. 85.

    Woods NF, LaCroix AZ, Gray SL,; Women’s Health Initiative Frailty: emergence and consequences in women aged 65 and older in the Women’s Health Initiative Observational Study [published correction appears in J Am Geriatr Soc. 2017;65(7):1631-1632]. J Am Geriatr Soc. 2005;53(8):1321-1330.

    Not in our library10.1111/j.1532-5415.2005.53405.x

  86. 86.

    Zaslavsky O, Walker RL, Crane PK, Gray SL, Larson EB Glucose levels and risk of frailty. J Gerontol A Biol Sci Med Sci. 2016;71(9):1223-1229

    Not in our library10.1093/gerona/glw024

  87. 87.

    Doi T, Makizako H, Tsutsumimoto K, Transitional status and modifiable risk of frailty in Japanese older adults: a prospective cohort study. Geriatr Gerontol Int. 2018;18(11):1562-1566

    Not in our library10.1111/ggi.13525

  88. 88.
  89. 89.

    Vetrano DL, Palmer K, Marengoni A,; Joint Action ADVANTAGE WP4 Group Frailty and multimorbidity: a systematic review and meta-analysis. J Gerontol A Biol Sci Med Sci. 2018.

    Not in our library10.1093/gerona/gly110

  90. 90.

    Ofori-Asenso R, Chin KL, Curtis AJ, Zomer E, Zoungas S, Liew D Recent patterns of multimorbidity among older adults in high-income countries. Popul Health Manag. 2019;22(2):127-137

    Not in our library10.1089/pop.2018.0069

  91. 91.

    Peralta M, Ramos M, Lipert A, Martins J, Marques A Prevalence and trends of overweight and obesity in older adults from 10 European countries from 2005 to 2013. Scand J Public Health. 2018;46(5):522-529

    Not in our library10.1177/1403494818764810

  92. 92.

    Samper-Ternent R, Al Snih S Obesity in older adults: epidemiology and implications for disability and disease. Rev Clin Gerontol. 2012;22(1):10-34

    Not in our library10.1017/s0959259811000190

  93. 93.

    García-Esquinas E, José García-García F, León-Muñoz LM, Obesity, fat distribution, and risk of frailty in two population-based cohorts of older adults in Spain. Obesity (Silver Spring). 2015;23(4):847-855

    Not in our library10.1002/oby.21013

  94. 94.

    Stenholm S, Strandberg TE, Pitkälä K, Sainio P, Heliövaara M, Koskinen S Midlife obesity and risk of frailty in old age during a 22-year follow-up in men and women: the Mini-Finland follow-up survey. J Gerontol A Biol Sci Med Sci. 2014;69(1):73-78

    Not in our library10.1093/gerona/glt052

  95. 95.
  96. 96.

    Ng TP, Feng L, Nyunt MS, Larbi A, Yap KB Frailty in older persons: multisystem risk factors and the Frailty Risk Index (FRI). J Am Med Dir Assoc. 2014;15(9):635-642

    Not in our library10.1016/j.jamda.2014.03.008

  97. 97.

    Espinoza SE, Fried LP Risk factors for frailty in the older adult. Clin Geriatr. 2007;15(6):37-44.

    Not in our library

  98. 98.
  99. 99.

    Siriwardhana DD, Hardoon S, Rait G, Weerasinghe MC, Walters KR 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. 2018;8(3):e018195

    Not in our library10.1136/bmjopen-2017-018195

  100. 100.

    Franse CB, van Grieken A, Qin L, Melis RJF, Rietjens JAC, Raat H Socioeconomic inequalities in frailty and frailty components among community-dwelling older citizens. PLoS One. 2017;12(11):e0187946

    Not in our library10.1371/journal.pone.0187946

  101. 101.

    Epping-Jordan JE, Pruitt SD, Bengoa R, Wagner EH Improving the quality of health care for chronic conditions. Qual Saf Health Care. 2004;13(4):299-305

    Not in our library10.1136/qshc.2004.010744

  102. 102.

    Gordon EH, Peel NM, Samanta M, Theou O, Howlett SE, Hubbard RE Sex differences in frailty: a systematic review and meta-analysis. Exp Gerontol. 2017;89:30-40

    Not in our library10.1016/j.exger.2016.12.021

  103. 103.

    Puts MTE, Toubasi S, Andrew MK, Interventions to prevent or reduce the level of frailty in community-dwelling older adults: a scoping review of the literature and international policies. Age Ageing. 2017;46(3):383-392.

    Not in our library10.1093/ageing/afw247

  104. 104.

    Apóstolo J, Cooke R, Bobrowicz-Campos E, Effectiveness of interventions to prevent pre-frailty and frailty progression in older adults: a systematic review. JBI Database System Rev Implement Rep. 2018;16(1):140-232

    Not in our library10.11124/jbisrir-2017-003382

  105. 105.

    Chin A Paw MJ, van Uffelen JG, Riphagen I, van Mechelen W The functional effects of physical exercise training in frail older people: a systematic review. Sports Med. 2008;38(9):781-793

    Not in our library10.2165/00007256-200838090-00006

  106. 106.
  107. 107.

    Giné-Garriga M, Roqué-Fíguls M, Coll-Planas L, Sitjà-Rabert M, Salvà A Physical exercise interventions for improving performance-based measures of physical function in community-dwelling, frail older adults: a systematic review and meta-analysis. Arch Phys Med Rehabil. 2014;95(4):753-769.e3

    Not in our library10.1016/j.apmr.2013.11.007

  108. 108.

    Travers J, Romero-Ortuno R, Bailey J, Cooney MT Delaying and reversing frailty: a systematic review of primary care interventions. Br J Gen Pract. 2019;69(678):e61-e69

    Not in our library10.3399/bjgp18x700241

  109. 109.

    Noubiap JJ, Balti EV, Bigna JJ, Echouffo-Tcheugui JB, Kengne AP Dyslipidaemia in Africa: comment on a recent systematic review: authors’ reply. Lancet Glob Health. 2019;7(3):e308-e309

    Not in our library10.1016/s2214-109x(18)30517-5

Cited by papers we hold 8

Reads

Read by people on this page

None yet.

Checked or read by AI through naulon

None yet.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

Are you an author?

Is this your paper?

Claim it to add your note and be paid when agents cite it. Free.