Assessment of the relationship between frailty syndrome and the nutritional status of older patients

The association between frailty and body composition among the elderly: Birjand Longitudinal Aging Study (BLAS)

Background

This study aims to assess the possible relationship between frailty and anthropometric indices in older adults using data from the first phase of the Birjand Longitudinal Aging Study (BLAS).

Methods

In this cross-sectional study, we assessed the association between frailty (Frailty index (FI) and Fried frailty phenotype) and body composition indices in 1364 participants aged ≥ 60 years (September 2018 to April 2019). Analysis was conducted using one-way ANOVA and ordinal logistic regression.

Results

Participants were categorized as frail (n = 164), non-frail (n = 415), and pre-frail (n = 785) based on FI. A significant positive association was observed between the frailty and body mass index (BMI) (OR: 1.04, 95% CI:1.01- 1.07), waist circumference (WC) (OR: 1.02, 95% CI: 1.01- 1.03), waist-to-hip ratio (WHR) (OR: 2.36, 95% CI 1.05- 5.27) and waist-to-height ratio (WHtR) (OR: 1.27, 95%CI: 1.09- 1.47). Body shape index, body roundness index, and body adiposity index showed no significant association with frailty. Moreover, a BMI greater than 29 kg/m2 increased the odds of frailty and prefrailty by 79% (OR = 1.79, 95%CI = 1.30- 2.46, P < 0.001).

Conclusion

Results of this study showed that the risk of frailty increases as BMI and abdominal obesity indices increase. Therefore, BMI and abdominal obesity indices (WC, WHR, and WHtR) could serve as suitable tools for evaluating frailty in the elderly. However, additional studies are needed to evaluate the utility of the newly developed anthropometric indices in older adults.

Exploring the interplay of frailty, physical function, physical activity, nutritional status, and their association with quality of life and depressive symptoms in older adults with the frailty phenotype

OBJECTIVE

This study aimed to explore the interplay between frailty, physical function, physical activity, nutritional status, and their impact on the quality of life and depressive status in older adults with frailty.

METHODS

A cross-sectional study involving 235 pre-frail/frail older adults residing in Spanish communities was conducted. Frailty was assessed using Fried's criteria, physical function was evaluated using the Short Physical Performance Battery, and physical activity levels were measured via wrist-worn accelerometers. Nutritional status was determined using the Mini-Nutritional Assessment alongside anthropometric measurements. Quality of life was gauged using the EuroQoL 5-Dimension 5-Level, while depressive status was assessed using the Yesavage 15-item Geriatric Depression Scale. Multivariate linear regression and logistic regression analyses were employed to elucidate the associations of these factors with quality of life and depression.

RESULTS

Our findings revealed significant correlations between various factors and quality of life. Notably, reported fatigue (β = -0.276, p = 0.002), performance in the 4-m gait test (β = -0.242, p = 0.001), the score on the short version of the Mini-Nutritional Assessment (β = 0.312, p = 0.002), and engagement in light physical activity (β = 0.180, p = 0.023) were all found to be associated with quality of life. In terms of depressive symptoms, the Mini-Nutritional Assessment score emerged as a protective factor (Odds ratio, OR: 0.812, p < 0.001), as did participation in moderate physical activity (OR: 0.988, p = 0.028). Conversely, fatigue (OR: 3.277, p = 0.003) and a slow gait speed (OR: 1.136, p = 0.045) were identified as risk factors for depressive symptoms.

CONCLUSIONS

This study underscores the detrimental association of fatigue and slow gait speed on both quality of life and depressive status among older adults with frailty. In contrast, engaging in physical activity and addressing malnutrition risk emerge as critical protective factors for enhancing quality of life and ameliorating depressive symptoms in this population.

CLINICAL TRIAL REGISTRATION

This is a study that uses cross-sectional data from a trial registered at ClinicalTrials.gov (Identifier: NCT05610605).

The SHARE Frailty Instrument for Primary Care was Associated with Sarcopenia, as Measured by Bioelectrical Impedance, in Falls Clinic Attendees

Objective

This study aimed to assess the association between measures of frailty phenotype (FP) and malnutrition, and sarcopenia measured by bioelectrical impedance analysis (BIA), in individuals aged 50 and above attending an outpatient falls clinic.

Methods

The Survey of Health, Ageing and Retirement in Europe Frailty Instrument (SHARE-FI) gauged FP status, while nutritional assessment relied on the Mini Nutritional Assessment-Short Form (MNA®-SF). Body composition, specifically appendicular skeletal muscle mass (ASMM), was determined through TANITA® DC-430MA BIA. Multivariable binary logistic regression models were used to predict pre-frailty or frailty based on SHARE-FI and at-risk of malnutrition or malnutrition based on MNA®-SF.

Results

Out of the 123 participants (68 women, 55 men), 56.1% were classified as robust, 27.6% as living with pre-frailty, and 16.3% as living with frailty according to SHARE-FI. MNA®-SF results were available for 116 patients, with 54.3% categorised as normal, 39.7% at risk of malnutrition, and 6.0% as malnourished. Among the 118 patients who underwent BIA, ASMM was independently associated with pre-frail/frail status, but there was no significant association between abnormal MNA®-SF and sarcopenia.

Conclusion

SHARE-FI, a modified FP tool, demonstrated an independent association with sarcopenia as measured by BIA.

A Narrative Review of the Utilisation of the SHARE Frailty Instruments (SHARE-FI and SHARE-FI75+) in the Literature

This narrative literature review aimed to examine the utilisation of the Survey of Health, Ageing and Retirement in Europe (SHARE) frailty instruments: SHARE-FI and SHARE-FI75+. We used the Google Scholar "cited by" function (accessed on February 20th, 2023) to identify all citations of the original SHARE-FI and SHARE-FI75+ studies. Included articles were categorised into four themes: epidemiological studies (prevalence and associated factors); associations with geriatric syndromes, diseases and health outcomes; randomised clinical trials (RCTs); and expert consensus and practice guidelines. Of 529 articles screened (446 citing SHARE-FI and 83 citing SHARE-FI75+), 64 (12.1%) were included. Sixteen (25.0%) were epidemiological; 35 (54.7%) described associations; 10 (15.6%) were RCTs; and 3 (4.7%) were expert consensus or practice guidelines. Frailty was associated with older age; female sex; higher morbidity; lower education; social isolation; worse nutrition and mobility; rheumatological, cardiovascular, and endocrine diseases; and greater healthcare utilisation and mortality. SHARE-FI was used in RCTs as entry criterion, controlling variable, and intervention outcome. SHARE-FI and SHARE-FI75+ have been recommended to aid the management of atrial fibrillation anticoagulation and hypertension, respectively. SHARE-FI and SHARE-FI75+, two open access phenotypical frailty measurement tools, have been utilised for a range of purposes, and mostly in epidemiological/associational studies.

A positive association between hunger in childhood and frailty in old age: Findings from the Chinese longitudinal healthy longevity survey

Background

Childhood hunger not only directly affects the physical and mental health of children and adolescents but also has a long-term negative effect on later health outcomes. In this cross-sectional study, we used a nationally representative Chinese sample to examine the relationship between hunger in childhood and frailty in older adults.

Materials and methods

The data were obtained from the 2018 Chinese Longitudinal Healthy Longevity Survey. The frailty index with 44 health deficits was used to identify frailty. Childhood hunger was measured by the question “Did you often go to bed hungry as a child?” Insurance status was categorized as New Rural Cooperative Medical Scheme (NRCMS), Urban Basic Medical Insurance Scheme (UBMIS), others, and no insurance. Multivariate logistic regression analysis was performed to estimate the adjusted relationship between childhood hunger and frailty.

Results

A total of 7,342 older people aged 65 years and older were analyzed in this study. Older people who experienced childhood hunger were more likely to have frailty than those who did not (OR = 1.13, 95% CI: 1.02–1.26), after adjustment for sociodemographic characteristics, family/social support, socioeconomic status, insurance status, and health behaviors. The association of childhood hunger with frailty was found in the 65–79 years group (OR = 1.21, 95% CI: 1.03–1.43), women (OR = 1.25, 95% CI: 1.08–1.45), individuals with rural residence (OR = 1.16, 95% CI: 1.03–1.31), agricultural work (OR = 1.16, 95% CI: 1.00–1.34), financial dependence (OR = 1.18, 95% CI: 1.02–1.37), and those participating in NRCMS (OR = 1.35, 95% CI: 1.16–1.56). Participants with hunger in childhood who were 80 years or older (OR = 0.80, 95% CI: 0.65–0.98) had lower odds of frailty. NRCMS (OR = 1.42, 95% CI: 1.02–1.98) showed increased odds of childhood hunger-related frailty.

Conclusion

Exposure to hunger during childhood is linked to frailty among older adults, and age, financial support, and insurance status may mediate this relationship. Targeted interventions and policies to address frailty in older adults should be implemented.

Association Between Geriatric Nutritional Risk Index and Frailty in Older Hospitalized Patients

Objective

Previous studies have explored the association between malnutrition and frailty, but no study has investigated whether the Geriatric Nutritional Risk Index (GNRI), a simple and objective nutritional risk screening tool, is associated with the frailty of older adults. The study aimed to examine the relationship between nutrition-related risk, as assessed by the GNRI, and frailty among older hospitalized patients.

Methods

A cross-sectional study was conducted in the West China Hospital of Sichuan University with 740 patients aged ≥70 years between March 2016 and Jan 2017. Nutritional and frailty status was evaluated with the GNRI and FRAIL scale, respectively. The adjusted and unadjusted ordinal logistic regression analyses were used to examine the relationship between nutritional risk and frailty. The ability of GNRI in detecting frailty was assessed by receiver operating characteristic (ROC) curve analysis.

Results

The prevalence of low, moderate, and severe nutritional risk among frail patients were 30.1%, 27.6%, and 12.5%, respectively. Ordinal logistic regression analysis showed that malnutrition assessed by the GNRI had a significant association with frailty after adjustment of age, sex, polypharmacy, comorbidity, vision impairment, hearing impairment, cognitive impairment, and depression. In the ROC analysis, the area under the curve for GNRI identifying frailty was 0.698 (95% CI: 0.66-0.74; P<0.001), and the optimal cut-point value was 97.16 (sensitivity: 64.3%; specificity: 66.9%).

Conclusion

Nutrition-related risk screened by the GNRI was independently associated with frailty. The GNRI could be used as a simple tool in detecting nutritional risk and frailty status of older patients.

Frailty in elderly inpatients with cardiovascular disease: an exploration of associated factors

AIMS

Older patients with cardiovascular diseases (CVDs) are more likely to develop frailty. Few studies have investigated frailty status, and its multiple associated factors, in this population. The aim of the present study was to explore frailty status, and its multidimensional associated factors, in elderly inpatients with CVDs.

METHODS AND RESULTS

In this cross-sectional study, 1021 inpatients with CVDs aged ≥60 years old were recruited through convenience sampling from multiple hospitals in Suzhou, China. The FRAIL scale was used to assess frailty. A self-designed questionnaire gathered sociodemographic, clinical, and health-related information related to the physiological, psychological, and social dimensions of frailty. Among the 629 elderly inpatients with CVDs (73.64 ± 7.93 years old) who met inclusion criteria and completed the assessments, 176 (28.0%) were classified as frail. Univariate analyses demonstrated that the proportion of frailty was significantly associated with multiple factors. Logistic regression analysis indicated that, compared to their counterparts, the risk of frailty was higher in participants with cardiac function classes II, III, and IV [odds ratio (OR) = 1.866, 3.393, and 6.351, respectively]; average and bad mastication function (OR = 2.534 and 2.945, respectively); and often or always using walking aids (OR = 2.713). Conversely, the risk of frailty was lower in participants with good nutritional status (OR = 0.879) and regular exercise habits (OR = 0.573), as compared with their counterparts.

CONCLUSION

Frailty in elderly inpatients with CVDs is common and associated with multiple physiological factors including cardiac function, mastication function, nutritional status, use of walking aids, and regular exercise habits.

Prevalence of frailty and associated socio-demographic factors among community-dwelling older people in southwestern Iran: a cross-sectional study

OBJECTIVES

This community-based cross-sectional study aimed to identify the frailty prevalence and associated socio-demographic factors among older adults in five cities of the south west of Iran.

METHODS

We selected a random sample of adults aged 60 years and above from five Southwest cities in Iran. Data for this study were retrospectively collected from 540 community-dwelling older adults. To measure frailty, we utilized the frailty index of cumulative deficit (FICD). Data were collected from medical records and socio-demographic factors, including gender, age, marital status, education level, lifestyle, income, and job status. The chi-square test and Spearman's correlation coefficient test were used to assess the relationship between the demographic variables and frailty status (SPSS version 22). Also, multiple binary logistic regression models were used to estimate the effects of demographic characteristics on the frailty recurrence.

RESULTS

The overall frailty prevalence was as follows: 77 (14.3%) frail, 139 (25.7%) pre-frail, and 324 (60%) not frail. The findings showed that all variables except education level and marital status are significantly associated with frailty status (P < 0.05). Multiple ridge logistic regression model indicated that age, gender, marital status, job status have significant, and education level, living arrangement, and economic status have no considerable effect on the frailty.

CONCLUSIONS

This study has shown that age and gender significantly contributed to the frailty process in older adults. The research also has shown the syndrome's occurrence affected by the aging process, and it supports the biological characteristics of frailty.

Frailty prevalence and related factors in older adults from southern Brazil: A cross-sectional observational study

OBJECTIVES

To determine the prevalence of frailty and the association of sociodemographic characteristics, clinical aspects, and functional capacity with the frailty status of community-dwelling older adults from Curitiba, Southern Brazil.

METHODS

This cross-sectional observational study included 1,716 participants aged ≥60 years. Frailty was assessed using the Fried phenotype indicators of weakness, exhaustion, low activity, slowness, and weight loss. Sociodemographic characteristics, clinical aspects, and functional capacity and functionality were evaluated and compared between the sexes and the different frailty statuses (non-frail, prefrail, and frail). Multinomial logistic regression models were used to identify associations (p<0.05).

RESULTS

A high prevalence of frailty (15.8%) and prefrailty (65.3%) were observed, and both were higher in female than in male individuals. The most predominant frailty criterion was weakness, followed by exhaustion. Compared with the non-frail elderly, the prefrail and frail elderly were older in age and presented more health problems, greater dependency for basic and instrumental activities of daily living, and reduced lower extremity strength performance and functional mobility. The highest proportion of illiterate individuals, individuals with 1-4 years of education, widowed individuals, polypharmacy, and possible cognition problems and diseases were seen in the frail elderly group. Moreover, the risk of being prefrail and frail was higher in those who were older and had more health problems, higher body mass index, and reduced lower extremity strength performance. Greater calf circumference and independence in activities of daily living were protective factors for prefrailty and frailty. Furthermore, lower functional mobility increased the chances of being frail.

CONCLUSIONS

The prevalence of frailty was more pronounced in female than in male individuals, mainly because of a decline in force. Prefrailty was 4 times more prevalent than frailty, and the presence of health problems and reduced functional capacity increased the chances of being prefrail and frail.