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Multimorbidity, the coexistence of multiple chronic diseases in an individual, is highly prevalent and challenging for healthcare systems. However, its risk factors remain poorly understood. To systematically review studies reporting multimorbidity risk factors. A PRISMA-compliant systematic review was conducted, searching electronic databases (MEDLINE, EMBASE, Web of Science, Scopus). Inclusion criteria were studies addressing multimorbidity transitions, trajectories, continuous disease counts, and specific patterns. Non-human studies and participants under 18 were excluded. Associations between risk factors and multimorbidity onset were reported. Of 20,806 identified studies, 68 were included, with participants aged 18–105 from 23 countries. Nine risk factor categories were identified, including demographic, socioeconomic, and behavioral factors. Older age, low education, obesity, hypertension, depression, low pysical function were generally positively associated with multimorbidity. Results for factors like smoking, alcohol consumption, and dietary patterns were inconsistent. Study quality was moderate, with 16.2% having low risk of bias. Several risk factors seem to be consistently associated with an increased risk of accumulating chronic diseases over time. However, heterogeneity in settings, exposure and outcome, and baseline health of participants hampers robust conclusions. • Multimorbidity, affects most older persons and is more prevalent in adults with low socioeconomic status • The identification of risk factors for multimorbidity may inform public health policies and prevention programs • Older age, low education, obesity, hypertension, depression, low pysical function were generally positively associated with multimorbidity. [ABSTRACT FROM AUTHOR]

Frailty is a syndrome characterized by reduced physiological reserves, increased vulnerability to stressors and adverse health outcomes. Frailty can change the prognosis and treatment approach of several chronic diseases, including heart failure (HF). The aim of this study was to conduct a systematic review and meta-analysis assessing the association of HF with frailty and pre-frailty. We employed PRISMA guidelines for reporting the results. We searched PubMed, Web of Science, and Embase from 01/01/2002 to 29/11/2019.The quality of the studies was evaluated with the Newcastle Ottawa Scale. Pooled estimates were obtained through random-effect models and Mantel-Haenszel weighting. Homogeneity (I2) and publication bias were assessed. We selected 54 studies (52 cross-sectional, one longitudinal, and one with both designs). The pooled prevalence of pre-frailty in individuals with HF was 46% (95% CI = 38–53; I2 = 93.1%) and 40% (95% CI = 31–48; I2 = 97%) for frailty. The proportion of pre-frail individuals with HF was 20% (95%CI = 15–25; I2 = 99.2%) and the proportion of frail individuals with HF was 31% (95% CI = 17–45; I2 = 98.7%). Two studies using the same frailty definition reported estimates for the association between frailty and HF (pooled OR = 3.44; 95% CI = 0.75–15.73; I2 = 95.8%). In conclusion, frailty and pre-frailty are frequent in people with HF. Persons with HF have 3.4-fold increased odds of frailty. Longitudinal studies examining bidirectional pathophysiological pathways between HF and frailty are needed to further clarify this relationship and to assess if specific treatment for HF may prevent or delay the onset of frailty and vice versa. • Frailty and pre-frailty are common among individuals affected by heart failure. • Frailty may help risk stratification in patients with heart failure. • Studies investigating their longitudinal association are lacking. [ABSTRACT FROM AUTHOR]

Abstract Background Frailty and multimorbidity are both strongly associated with poor health-related outcomes, including mortality. Being multimorbidity one of the major determinants of frailty, we aimed to explore whether, and to what extent, frailty without multimorbidity plays an independent role in shortening life. Methods We used data from the Swedish National Study on Aging and Care in Kungsholmen (SNAC-K). Among the 3363 adults aged 60+ enrolled at baseline, those without multimorbidity (i.e.: less than two chronic diseases) (N = 1115) have been characterized according to Fried's frailty phenotype (i.e. robust, prefrail, and frail). The association between frailty and mortality was estimated using piecewise proportional hazard regression models in three five-year time periods. Results Among participants without multimorbidity, 424 (38%) were prefrail and 19 (2%) were frail. During the 15-year follow-up, 263 (24%) participants died: 19%, 29%, and 63% of those who were robust, prefrail, and frail at baseline, respectively. Within the first 5 years of follow-up, prefrail and frail participants had more than doubled mortality risk in comparison to robust ones (HR for pre-frailty 2.08, 95% CI 1.15–3.76; HR for frailty 2.69, 95% CI 1.22–5.97). Beyond 5 years, a trend of increased mortality rate was still detectable for prefrail and frail subjects in comparison to robust ones. Conclusions Physical frailty and pre-frailty are associated with short-term mortality in a cohort of older adults free from multimorbidity. Frailty could be a clinical indicator of increased risk of negative health outcomes even among subjects without multiple chronic conditions. Highlights • Forty percent of subjects without multimorbidity are frail or prefrail. • Frailty and pre-frailty increase mortality risk even in absence of multimorbidity. • Screening for frailty in individuals without multimorbidity might be beneficial. • Future research should focus on causes of frailty other than chronic diseases. [ABSTRACT FROM AUTHOR]

The aim was to characterize multimorbidity patterns in a large sample of older individuals living in nursing homes (NHs) and to investigate their association with mortality, also considering the effect of functional status. Observational and retrospective study. We analyzed data on 4131 NH residents in Italy, aged 60 years and older, assessed through the interRAI long-term care facility instrument. Entry date was between 2014 and 2018, and participants were followed until 2019. Multimorbidity patterns were identified through principal component analysis; for the identified components, subjects were stratified in quintiles (Q) with respect to their loading values, with the higher quantiles indicating greater expression of the component's pattern. Their association [hazard ratio (HR) and 95% CI] with mortality was tested in Cox regression models. Analyses were stratified by disability status. Four patterns of multimorbidity were identified: (1) heart diseases ; (2) dementia and sensory impairments ; (3) heart, respiratory, and psychiatric diseases; and (4) diabetes, musculoskeletal, and vascular diseases. For the heart diseases pattern [HR Q5 vs Q1 = 1.83 (1.53–2.20)] and the dementia and sensory impairments pattern [HR Q5 vs Q1 = 1.23 (1.06–1.42)], as the specific multimorbidity expression increases, the risk of mortality increases. On stratifying by disability status, the association between the multimorbidity patterns and mortality was not always present. Different multimorbidity patterns are differentially associated with mortality in older residents of NHs, confirming that multimorbidity's prognosis is strictly dependent on the underlying disease combinations. This knowledge may be useful to implement personalized preventive and therapeutic care pathways for institutionalized older adults, which respond to individuals' health needs. [ABSTRACT FROM AUTHOR]

The aim was to evaluate patterns of multimorbidity that increase the risk of institutionalization in older persons, also exploring the potential buffering effect of formal and informal care. Prospective cohort study. The population-based Swedish National study on Aging and Care in Kungsholmen, Stockholm, Sweden. In total, 2571 community-dwelling older adults were grouped at baseline according to their underlying multimorbidity patterns, using a fuzzy c-means cluster algorithm, and followed up for 6 years to test the association between multimorbidity patterns and institutionalization. Six patterns of multimorbidity were identified: psychiatric diseases; cardiovascular diseases, anemia, and dementia; metabolic and sleep disorders; sensory impairments and cancer; musculoskeletal, respiratory, and gastrointestinal diseases; and an unspecific pattern including diseases of which none were overrepresented. In total, 110 (4.3%) participants were institutionalized during the follow-up, ranging from 1.7% in the metabolic and sleep disorders pattern to 8.4% in the cardiovascular diseases, anemia, and dementia pattern. Compared with the unspecific pattern, only the cardiovascular diseases, anemia, dementia pattern was significantly associated with institutionalization [relative risk ratio (RRR) = 2.23; 95% confidence interval (CI) 1.07‒4.65)], after adjusting for demographic characteristics and disability status at baseline. In stratified analyses, those not receiving formal care in the psychiatric diseases pattern (RRR 3.34; 95% CI 1.20‒9.32) and those not receiving formal or informal care in the 'cardiovascular diseases, anemia, dementia' pattern (RRR 2.99; 95% CI 1.20‒7.46; RRR 2.79; 95% CI 1.16‒6.71, respectively) had increased risks of institutionalization. Older persons suffering from specific multimorbidity patterns have a higher risk of institutionalization, especially if they lack formal or informal care. Interventions aimed at preventing the clustering of diseases could reduce the associated burden on residential long-term care. Formal and informal care provision may be effective strategies in reducing the risk of institutionalization. [ABSTRACT FROM AUTHOR]