Prevalence of Undernutrition, Frailty and Sarcopenia in Community-Dwelling People Aged 50 Years and Above: Systematic Review and Meta-Analysis.
Nada AlmohaisenMatthew GittinsChris ToddJana SremanakovaAnne Marie SowerbuttsAmal AldossariAsrar AlmutairiDebra JonesSorrel BurdenPublished in: Nutrients (2022)
The world's population aged ≥65 is expected to rise from one in eleven in 2019 to one in six by 2050. People aged ≥65 are at a risk of undernutrition, frailty, and sarcopenia. The association between these conditions is investigated in a hospital setting. However, there is little understanding about the overlap and adverse health outcomes of these conditions in community-dwelling people. This systematic review aims to quantify the reported prevalence and incidence of undernutrition, frailty, and sarcopenia among older people aged ≥50 living in community dwellings. Searches were conducted using six databases (AMED, CENTRAL, EMBASE, Web of Science, MEDLINE, and CINAHL), and 37 studies were included. Meta-analyses produced weighted combined estimates of prevalence for each condition (Metaprop, Stata V16/MP). The combined undernutrition prevalence was 17% (95% CI 0.01, 0.46, studies n = 5; participants = 4214), frailty was 13% (95% CI 0.11, 0.17 studies n = 28; participants = 95,036), and sarcopenia was 14% (95% CI 0.09, 0.20, studies n = 9; participants = 7656). Four studies reported incidence rates, of which three included data on frailty. Nearly one in five of those aged ≥50 was considered either undernourished, frail, or sarcopenic, with a higher occurrence in women, which may reflect a longer life expectancy generally observed in females. Few studies measured incidence rates. Further work is required to understand population characteristics with these conditions and the overlap between them. PROSPERO registration No. CRD42019153806.
Keyphrases
- community dwelling
- risk factors
- systematic review
- meta analyses
- case control
- healthcare
- risk assessment
- public health
- randomized controlled trial
- type diabetes
- machine learning
- metabolic syndrome
- polycystic ovary syndrome
- adverse drug
- high resolution
- artificial intelligence
- pregnancy outcomes
- data analysis
- atomic force microscopy