Prevalence of frailty and prefrailty among community-dwelling older adults in low-income and middle-income countries: a systematic review and meta-analysis

OBJECTIVE: To systematically review the research conducted on prevalence of frailty and prefrailty among community-dwelling older adults in low-income and middle-income countries (LMICs) and to estimate the pooled prevalence of frailty and prefrailty in community-dwelling older adults in LMICs. DESIGN: Systematic review and meta-analysis. PROSPERO registration number is CRD42016036083. DATA SOURCES: MEDLINE, EMBASE, AMED, Web of Science, CINAHL and WHO Global Health Library were searched from their inception to 12 September 2017. SETTING: Low-income and middle-income countries. PARTICIPANTS: Community-dwelling older adults aged ≥60 years. RESULTS: We screened 7057 citations and 56 studies were included. Forty-seven and 42 studies were included in the frailty and prefrailty meta-analysis, respectively. The majority of studies were from upper middle-income countries. One study was available from low-income countries. The prevalence of frailty varied from 3.9% (China) to 51.4% (Cuba) and prevalence of prefrailty ranged from 13.4% (Tanzania) to 71.6% (Brazil). The pooled prevalence of frailty was 17.4% (95% CI 14.4% to 20.7%, I²=99.2%) and prefrailty was 49.3% (95% CI 46.4% to 52.2%, I²=97.5%). The wide variation in prevalence rates across studies was largely explained by differences in frailty assessment method and the geographic region. These findings are for the studies with a minimum recruitment age 60, 65 and 70 years. CONCLUSION: The prevalence of frailty and prefrailty appears higher in community-dwelling older adults in upper middle-income countries compared with high-income countries, which has important implications for healthcare planning. There is limited evidence on frailty prevalence in lower middle-income and low-income countries

Association between frailty and disability among rural community-dwelling older adults in Sri Lanka: a cross-sectional study

OBJECTIVE: We examined the association between frailty and disability in rural community-dwelling older adults in Kegalle district of Sri Lanka. DESIGN: A population-based cross-sectional study. PARTICIPANTS: A total of 746 community-dwelling adults aged ≥60 years. PRIMARY AND SECONDARY OUTCOME MEASURES: Frailty was assessed using the Fried phenotype. Disability was operationalised in terms of having one or more activity limitation/s in instrumental activities of daily living (IADL) and basic activities of daily living (BADL). RESULTS: The median age of the sample was (median 68; IQR 64-75) years and 56.7% were female. 15.2% were frail and 48.5% were prefrail. The prevalence of ≥1 IADL limitations was high, 84.4% among frail adults. 38.7% of frail adults reported ≥1 BADL limitations. Over half of frail older adults (58.3%) reported both ≥1 physical and cognitive IADL limitations. Being frail decreased the odds of having no IADL limitations, and was associated with a higher count of IADL limitations. No significant association was found between prefrailty and number of IADL limitations. CONCLUSIONS: The prevalence of ≥1 IADL limitations was high among rural community-dwelling frail older adults. Findings imply the greater support and care required for rural Sri Lankan frail older adults to live independently in the community

Prevalence of frailty in rural community-dwelling older adults in Kegalle district of Sri Lanka: a population-based cross-sectional study

OBJECTIVE: Our main objective was to describe the prevalence and associated sociodemographic factors of frailty and pre-frailty in rural community-dwelling older adults in Kegalle district of Sri Lanka. DESIGN: Community-based cross-sectional study. SETTING: The study was conducted in rural areas of Kegalle district in Sri Lanka. PARTICIPANTS: A total of 746 community-dwelling older adults aged ≥60 years were included in the study. RESULTS: The prevalence of frailty and pre-frailty in rural Kegalle district was 15.2% (95% CI 12.3% to 18.6%) and 48.5% (95% CI 43.8% to 53.2%), respectively. We found a strong association between age and both frailty and pre-frailty. There were strong associations between longest-held occupation and frailty and education level and pre-frailty. CONCLUSIONS: The prevalence of frailty in this rural Sri Lankan older population was high compared with high-income and upper middle-income countries. The profile of health and social care services in Sri Lanka needs to address frailty and its consequences

The association between frailty and quality of life among rural community-dwelling older adults in Kegalle district of Sri Lanka: a cross-sectional study

PURPOSE: The objective of this study was to estimate the cross-sectional association of frailty status with overall and domain-specific quality of life (QoL) in rural community-dwelling older adults in Kegalle district of Sri Lanka. METHODS: A population-based cross-sectional study was conducted with 746 community-dwelling older adults aged ≥ 60 years living in the rural areas of Kegalle district of Sri Lanka in 2016. A three-stage probability sampling design was used to recruit participants. Frailty and QoL were assessed using the Fried phenotype and Older People's Quality of Life Questionnaire, respectively. Multivariable linear regression was used to estimate the association of frailty with QoL after accounting for the complex sampling design. RESULTS: The median (IQR) age of the sample was 68 (64:75) years and comprised of 56.7% women. 15.2% (95% CI 12.4%, 18.7%) were frail and 48.5% (95% CI 43.9%, 53.2%) were pre-frail. The unadjusted means (SE) of the total QoL score for the robust, pre-frail and frail groups were 139.2 (0.64), 131.8 (1.04) and 119.2 (1.35), respectively. After adjusting for covariates in the final multivariable model, the estimated differences in mean QoL were lower for both frail and pre-frail groups versus robust. The estimated reduction in the total QoL score was 7.3% for those frail and 2.1% for those pre-frail. All QoL domains apart from 'social relationships and participation', 'home and neighbourhood' and 'financial circumstances' were associated with frailty. CONCLUSIONS: Frailty was associated with a small but significant lower quality of life in this rural Sri Lankan population, which appears largely explained by 'health' and 'independence, control over life and freedom' QoL domains. Interventions aiming to improve quality of life in frail older adults should consider targeting these aspects

A robust machine learning framework to identify signatures for frailty: a nested case-control study in four aging European cohorts

Phenotype-specific omic expression patterns in people with frailty could provide invaluable insight into the underlying multi-systemic pathological processes and targets for intervention. Classical approaches to frailty have not considered the potential for different frailty phenotypes. We characterized associations between frailty (with/without disability) and sets of omic factors (genomic, proteomic, and metabolomic) plus markers measured in routine geriatric care. This study was a prevalent case control using stored biospecimens (urine, whole blood, cells, plasma, and serum) from 1522 individuals (identified as robust (R), pre-frail (P), or frail (F)] from the Toledo Study of Healthy Aging (R=178/P=184/F=109), 3 City Bordeaux (111/269/100), Aging Multidisciplinary Investigation (157/79/54) and InCHIANTI (106/98/77) cohorts. The analysis included over 35,000 omic and routine laboratory variables from robust and frail or pre-frail (with/without disability) individuals using a machine learning framework. We identified three protective biomarkers, vitamin D3 (OR: 0.81 [95% CI: 0.68–0.98]), lutein zeaxanthin (OR: 0.82 [95% CI: 0.70–0.97]), and miRNA125b-5p (OR: 0.73, [95% CI: 0.56–0.97]) and one risk biomarker, cardiac troponin T (OR: 1.25 [95% CI: 1.23–1.27]). Excluding individuals with a disability, one protective biomarker was identified, miR125b-5p (OR: 0.85, [95% CI: 0.81–0.88]). Three risks of frailty biomarkers were detected: pro-BNP (OR: 1.47 [95% CI: 1.27–1.7]), cardiac troponin T (OR: 1.29 [95% CI: 1.21–1.38]), and sRAGE (OR: 1.26 [95% CI: 1.01–1.57]). Three key frailty biomarkers demonstrated a statistical association with frailty (oxidative stress, vitamin D, and cardiovascular system) with relationship patterns differing depending on the presence or absence of a disability