BACKGROUND: Frailty has a significant impact on the overall quality of life of older cancer survivors, but the relationships among frailty symptoms are not well understood. This study aims to explore the specific associations among multidimensional symptoms of frailty among older cancer survivors by employing network analysis to provide supportive evidence for targeted interventions in the future.
METHODS: Data were obtained by cluster sampling from three large Grade-A tertiary hospitals in Shandong Province, China, and collected through face-to-face interviews by trained investigators. We included patients who were diagnosed with a solid malignant tumor at the age of 60 years or older. Frailty indicators were measured by the Groningen Frailty Indicator (GFI) and analyzed primarily through network analysis, including network estimation, centrality, and stability analysis. The relative importance of a node in a network was tested by centrality analyses, and Spearman correlations were applied to estimate the relationships between symptom pairs (symptom score) and symptom clusters (standardized symptom score) in the symptom network. In terms of centrality, the indexes of strength, closeness, and betweenness were adopted to measure the importance of nodes.
RESULTS: Five hundred and eight older cancer survivors were included, with an average age of 68.4 years (standard deviation [SD] = 5.4), and a higher proportion were male (n = 307[60.4%]). The prevalence of frailty among older cancer survivors was 58.9% (n = 299), with a mean GFI score of 4.46 (SD = 2.87). The strongest edge was between \"dressing and undressing\" and \"going to the toilet\" (r = 0.58). The nodes with the higher strength centrality were \"going to the toilet\" (rS=1.09), \"walking around outside\" (rS=0.97), and \"part of social network\" (rS=0.96); and the nodes with the higher closeness centrality were \"mark physical fitness\" (rC=0.005), \"calm and relaxed\" (rC=0.005), and \"nervous or downhearted\" (rC=0.005).
CONCLUSIONS: This study demonstrated that older cancer survivors in China have a high prevalence of frailty, with self-care and social participation-related symptoms playing a key role in the multidimensional network of frailty symptoms. Psychological symptoms can rapidly influence other symptoms within this network. Therefore, prioritizing psychological symptoms in the assessment of older adults with cancer is essential for effective frailty management.

OBJECTIVE: This study aimed to enrich the research on frailty trajectories by using FRAIL scale and frailty index (FI), and analyze the determinants of the different trajectories in older Chinese.
METHODS: 2268 older adults from the Chinese Longitudinal Healthy Longevity Survey were included. The FRAIL scale was constructed from 5 items and FI was constructed from 39 deficits. Latent Class Trajectory Model was used to depict frailty trajectories. Lasso - logistic model was applied to exploration of influencing factors.
RESULTS: Four FRAIL trajectories and three FI trajectories were identified. Women, smoking, illiteracy, more than two chronic diseases, and poor instrumental activities of daily living (all p < 0.05) were associated with frailty trajectories, regardless of the frailty instrument employed.
CONCLUSIONS: Frailty trajectories of older Chinese adults are diverse and they are influenced by different frailty measurement tools. Long-term assessment and management of frailty are recommended as routine care in community healthcare centers.

UNASSIGNED: The causality between frailty and gestational diabetes mellitus (GDM) has not yet been fully explored. A potential bidirectional causality was also needed to be confirmed.
UNASSIGNED: A bidirectional two-sample Mendelian randomization (MR) was conducted, with frailty-related data was collected from UK Biobank and TwinGen and GDM-related data was collected from the FinnGen consortium. We performed univariable and multivariable-adjusted MR with adjustments for body mass index (BMI). Several methodologies of MR were conducted to confirm the robustness of results.
UNASSIGNED: Frailty was significantly associated with elevated risks of GDM (OR, 3.563; 95% CI, 1.737 to 7.309; P< 0.001) and GDM was also significantly associated with elevated risks of frailty ( β , 0.087; 95% CI, 0.040 to 0.133; P< 0.001). There is no evidence demonstrating the existence of horizontal pleiotropy and heterogeneity. This association was robust after adjustments for BMI. The sensitivity analyses with Weighted median, Maximum likelihood, Penalised weighted median, MR Egger and MR PRESSO methods indicated consistent results.
UNASSIGNED: Our study provides evidence of the bidirectional causal association between frailty and GDM from genetic perspectives, signaling that the identification and assessment of frailty should become a standard strategy during the early stages and care of gestational diabetes.

OBJECTIVE: To investigate the independent and combined effects of physical activity (PA) and depressive symptoms on the risk of frailty in community-dwelling older adults.
BACKGROUND: Older adults face a high risk of frailty which is commonly used to predict adverse health outcomes in older patients. Engaging in PA and without depressive symptoms are crucial factors to prevent frailty. It is essential to investigate the independent and combined effects of these two variables on the risk of frailty.
METHODS: We included 3392 community-dwelling older adults. The FRAIL Scale was used to assess older adults\' frail status (robust, prefrail and frail). Multiple logistic regression was utilized to examine the independent and combined effects of PA and depressive symptoms on the risk of prefrailty and frailty. The combined effects were visualized by marginal plots.
RESULTS: The prevalence of prefrailty and frailty in older adults were 42.16% and 10.58%. Compared with the group of \"Light physical activity and With depressive symptoms\", \"Vigorous physical activity and Without depressive symptoms\" had the lowest risk of prefrailty and frailty.
CONCLUSIONS: Older adults who do not engage in PA or have depressive symptoms increased the risk of frailty, but older adults with depressive symptoms could lower the risk of frailty through PA.
CONCLUSIONS: It is effective to reduce the risk of frailty by directing older adults to do moderate physical activity, although they have depressive symptoms. The focus should also be on older adults with depressive symptoms, who have at least more than twice and fourfold risk of prefrailty and frailty compared to those without.
CONCLUSIONS: This study offers insights for future interventions aimed at preventing frailty in older adults.
UNASSIGNED: This study adhered to the STROBE checklist.
UNASSIGNED: Older adults participated in this study and completed questionnaires.

OBJECTIVE: Frailty is a common health state that is closely linked to adverse health outcomes in aging society. Although many inflammatory biomarkers have been cross-sectionally associated with frailty, knowledge on the longitudinal association is still limited. This study investigated the associations between inflammatory factors in clinical practice and frailty progression over time.
METHODS: To investigate the associations of three common inflammatory markers (hypersensitive C-reactive protein [hsCRP], white blood cell [WBC] and fibrinogen) with the progression of frailty.
METHODS: Data of 2316 participants (age 67.9 ± 6.1 years) were obtained from the English longitudinal study of aging (wave 4, 6 and 8) over an 8-year follow-up. The frailty index (FI) was calculated from 52 items. Mixed-effects models and Cox proportional hazards (Cox-PH) models were used to analyze the associations of hsCRP, WBC and fibrinogen with frailty progression. Values of inflammatory biomarkers were log-transformed. Age, sex and gross wealth were controlled.
RESULTS: Mixed-effects models showed that at a cross-sectional level, higher levels of hsCRP (β: 0.007, 95% CI 0.004-0.010), WBC (β: 0.021, 95% CI 0.010-0.032) and fibrinogen (β: 0.022, 95% CI 0.005-0.038) were associated with greater FI values while no significant time interaction was found. Cox-PH models showed that higher baseline levels of hsCRP (HR: 1.10, 95% CI 1.03-1.17) and WBC (HR: 1.23, 95% CI 1.10-1.37) were linked to a greater risk of developing frailty within 8 years.
CONCLUSIONS: We concluded that hsCRP, WBC and fibrinogen can reflect frailty status at a cross-sectional level while only hsCRP and WBC are associated with frailty progression over an 8-year period.

BACKGROUND: Little is known about the prevalence of malnutrition among patients receiving home care (HC) and ambulatory care (AC) services. Further, the risk of hospital readmission in malnourished patients transitioning from hospital to HC or AC is also not well established. This study aims to address these two gaps.
METHODS: A descriptive cohort study of newly referred HC and AC patients between January and December 2019 was conducted. Nutrition status was assessed by clinicians using the Mini Nutritional Assessment-Short Form (MNA-SF). Prevalence of malnutrition and at risk of malnutrition (ARM) was calculated, and a log-binomial regression model was used to estimate the relative risk of hospital readmission within 30 days of discharge for those who were malnourished and referred from hospital.
RESULTS: A total of 3704 MNA-SFs were returned, of which 2402 (65%) had complete data. The estimated prevalence of malnutrition and ARM among newly referred HC and AC patients was 21% (95% CI: 19%-22%) and 55% (95% CI: 53%-57%), respectively. The estimated risk of hospital readmission for malnourished patients was 2.7 times higher (95% CI: 1.9%-3.9%) and for ARM patients was 1.9 times higher (95% CI: 1.4%-2.8%) than that of patients with normal nutrition status.
CONCLUSIONS: The prevalence of malnutrition and ARM among HC and AC patients is high. Malnutrition and ARM are correlated with an increased risk of hospital readmission 30 days posthospital discharge.

The prevalence of frailty in clinical trials of lymphoma is unknown. We conducted a secondary analysis of the phase III LY.12 trial in which patients with relapsed aggressive non-Hodgkin lymphoma were randomized to different salvage regimens before autologous stem cell transplant. The primary objective was to construct a lymphoma clinical trials-specific frailty index (LyFI) using previously described methods. The secondary objective was to describe the association of frailty withover all and event-free survival (OS, EFS). The LyFI was constructed using 619 patients, and11% (N = 70) were classified as frail. Frailty was associated with EFS (HR 1.94, 95%CI 1.53-2.46) and OS (HR 2.01, 95%CI 1.57-2.58) in univariable analysis, but was only significant as a continuous (not binary) variable in multivariable analysis controlling for prognostic score, suggesting limitations of a FI in this trial population. Future work could validate the FI using clinical assessments and/or apply it to an older trial population.

BACKGROUND: Osteoporosis and frailty are two common features in the elderly population. Despite many review articles mentioning the association between osteoporosis and frailty, there is a lack of original research directly investigating their relationship. Therefore, this study was conducted to examine the correlation between osteoporosis and frailty.
METHODS: We conducted a cross-sectional study using data from the National Health and Nutrition Examination Survey (NHANES), using logistic regression analysis to assess the association of osteoporosis with the frailty index. In addition, we further explored the causal relationship between them using Mendelian randomization (MR) study.
RESULTS: In the cross-sectional study, 19,091 non-frailty participants and 5878 frailty participants were included in this study. We observed a significant positive association between osteoporosis and frailty after adjusting for demographic characteristics, body mass index (BMI), smoking, and alcohol use (OR = 1.454, 95% CI [1.142,1.851], P = 0.003). Moreover, the MR study showed a bidirectional causal relationship between osteoporosis and frailty. When osteoporosis was used as an exposure factor, the frailty pooled OR value calculated utilizing the inverse variance weighted (IVW) method was 2.81 (95% CI [1.69, 4.68], P = 6.82 × 10- 5). When frailty was used as an exposure factor, the OR value calculated using the IVW method was 1.01 (95% CI [1.00,1.01], P = 3.65 × 10- 7).
CONCLUSIONS: Osteoporosis was positively correlated with frailty, and the results remained robust after adjusting for covariates. Further, MR studies have shown a bidirectional causal relationship between osteoporosis and frailty.

Frailty has been linked to inflammation and changes in body composition, but the findings are inconsistent. To explore this, we used the Frailty Index (FI) definition to (1) investigate the association between levels of inflammatory markers (baseline) and change in FI score after 8 years of follow-up and (2) investigate the longitudinal associations between inflammatory markers, body composition, and frailty. Home-dwelling elderly (≥ 70 years) were invited to participate in the study and re-invited to a follow-up visit 8 years later. This study includes a total of 133 participants. The inflammatory markers included were high-sensitive C-reactive protein (hs-CRP), interleukin 6 (IL-6), tumor necrosis factor alpha (TNF-α), and glycoprotein acetyls (Gp-acetyls). We used the body composition markers fat mass, fat-free mass, and waist circumference. The FI score consisted of 38 variables. Additional clinical assessments such as blood pressure and body mass index (BMI), as well as information about daily medications, were collected at both visits. Linear regression model and Spearman\'s rank correlation were used to investigate associations. We showed that the FI score increased after 8 years, and participants with higher hs-CRP levels at baseline had the largest change in the FI score. Changes in fat mass were significantly correlated with changes in hs-CRP and IL-6, and changes in waist circumference were significantly correlated with changes in TNF-α. The use of drugs increased during the 8 years of follow-up, which may have attenuated the associations between inflammation and frailty. However, elevated concentrations of hs-CRP in the elderly may be associated with an increased risk of frailty in subsequent years.

This study aimed to examine joint trajectories of pain, depression and frailty and their associations with adverse outcomes. Four waves of national data from the China Health and Retirement Longitudinal Study (CHARLS 2011-2018) were used, involving 4217 participants aged ≥60 years. Joint trajectories were fit using parallel-process latent class growth analysis, and their associations with adverse outcomes were evaluated using modified Poisson regression. Four joint trajectories were identified. Compared with most favorable group, other three joint trajectory groups had higher risk of functional disability and hospitalization. Slowly progressive pain, depression and frailty and persistent combination of pain, depression and frailty were also associated with cognitive decline, while slowly reduced pain and depression but persistent frailty was associated with all-cause mortality. The findings highlight unique characteristics and health impacts of concurrent changes in pain, depression and frailty over time, implicating the integrated physical and psychological care for older adults.