Association between nutritional risk and fatigue in frailty conditions for older adult patients: a multicentre cross-sectional survey study

STRENGTHS AND LIMITATIONS OF THIS STUDY

  • This multicentre survey has revealed the risk factors related to fatigue which is a symptom of malnutrition and frailty.

  • Validated instruments were used to assess the overlap prevalence of frailty and nutritional risk in older adult patients.

  • A causal relationship between nutritional risk and fatigue could not be shown.

  • There are a few related influencing factors of frailty and nutritional risk included in this study.

  • The study only used the FRAIL scale and Nutritional Risk Screening-2002, which are screening tools but not diagnostic tools with higher accuracy to define frailty and nutritional status.

Background

Frailty is an age-related clinical syndrome characterised by the decreased physiological capacity of multiple organ systems, resulting in increased vulnerability to stressful events.1 2 Frailty is widespread in elderly inpatients, and the prevalence of frailty is expected to rise as the ageing population grows rapidly.1 3 Besides, frailty is often observed in various diseases such as cancer,4 5 cardiovascular diseases6 7 and neurodegenerative diseases.8 9 Frailty has been confirmed to increase mortality, complication rate, prolong the length of hospital stay and increase hospital costs in older adult patients.10–12

Fatigue is defined as a symptom associated with the weakening or depletion of a person’s physical and/or mental resources.13 In the Fried’s frailty phenotype model, involuntary weight loss, slowed gait, decreased grip strength, low physical activity and fatigue were the five indicators of frailty, with three or more being diagnosed as frailty syndrome.14 Fatigue plays an important role in frailty scales to cover the potential pathophysiological mechanisms related to fatigue and frailty.15 Fatigue increases the risk of adverse health outcomes in the elderly and is associated with increased mortality and the risk of daily living disorders.16

Malnutrition has a bi-directional relationship with frailty and is prevalent in frail patients; malnutrition is also considered one of the mechanisms of fatigue with changes in food intake and changes in body composition appearing to influence fatigue.17–20 Therefore, understanding the positive correlation between nutritional status and fatigue may have clinical value in suggesting that nutritional intervention can improve fatigue and even frailty. The aim of our study was to investigate the prevalence and correlation of frailty and nutritional risk in older adult patients and to analyse the risk factors associated with fatigue which is one indicator of frailty.

Methods

Patients

This multicentre cross-sectional survey study was conducted in five hospitals in the same city in China from 01 January 2021 to 01 December 2021. A total of 2016 elderly patients with complete data were included, and informed consent was obtained from all the patients.

The inclusion criteria were (1) aged 65 years or older; (2) inpatients or outpatients; (3) being conscious; (4) no emergency surgery and (5) being willing to accept the assessment and signed an informed consent. Exclusion criteria included: (1) emergency patients; (2) refusal to participate; (3) incomplete information: lack of information on nutritional risk and frailty screening indicators or clinically relevant information and (4) repeat admissions.

Patient and public involvement

Patients and/or the public were not involved in the design, conduct, reporting or dissemination plans of this research.

Data collection

In this study, the patients were surveyed by a trained physician or nurse using a mobile application that referenced the designed case report form. To begin with, the patients were confirmed whether they met the inclusion and exclusion criteria, their willingness to participate and signed informed consent. In addition, demographic information such as gender, age, smoking, alcohol consumption, diseases, medication (polypharmacy is defined as taking more than five medications), dietary status and other information were collected. Furthermore, FRAIL scale was used to investigate the frailty status, and nutritional risk screening-2002 (NRS-2002) was used to screen the nutritional risk. After confirming the completion of the survey, the investigator confirmed the submission of the report in the mobile application. Finally, the software engineers and programme managers exported the data to the background website, and the statistical analysts cleaned the data and then locked the data.

Frailty and nutritional risk screening

FRAIL scale

The FRAIL scale consists of five components: fatigue, resistance, ambulation (slow walking speed), illness and loss of weight (5% or more in the previous year), with three or more of the above five being diagnosed as frailty.21 It is a hybrid measurement consisting of components of Fried’s frailty phenotype14 and the Frailty Index22 and is the most practical tool for identifying frailty with the advantage of time and cost-effectiveness.23

Nutritional risk screening-2002

The NRS-2002 is graded and scored according to nutritional status, disease severity and age, and a score of 3 or greater is considered nutritional risk.24 It resembles as an effective and reliable tool for screening malnutrition in geriatric patients and is recognised as the preferred screening tool by some nutrition societies.25–27

Statistical analysis

Continuous variables were expressed as mean (SD), and differences were analysed by t-test. Categorical variables were expressed as frequencies (percentages), and differences were determined by the χ2 test. Spearman rank correlation was used to analyse the correlation between frailty and nutritional risk. Univariate logistic regression analysis was used to investigate the association between demographic characteristics, nutritional risk, diseases, medication and the occurrence of fatigue, and multivariate logistic regression analysis (forward: likelihood ratio) was used to analyse all related factors in all patients and inpatients to construct a fully adjusted model. SPSS V.25 was used for statistical analysis, and a p value of <0.05 was considered statistically significant.

Results

Study characteristics

A total of 2016 older adult patients were included (figure 1), including 1575 inpatients, 441 outpatients, 1083 female patients and 933 male patients, male:female = 0.86:1, median age 7211 years (table 1), 1981 Han nationality and 35 other nationalities. Concomitant diseases: 307/2016 (15.2%) patients had a malignant tumour, and 747/2016 (37.1%) patients had diabetes mellitus.

Table 1

Demographic characteristics of older adult patients

Figure 1
Figure 1

Flow chart.

Prevalence of frailty and nutritional risk

The prevalence of frailty based on the FRAIL scale in older adult patients was 15.1% (305/2016). There were 16.2% (327/2016) patients at nutritional risk screened by NRS-2002, and the overlap prevalence of frailty and nutritional risk is 7.3% (147/2016). Among hospitalised patients, 18.5% (292/1575) were frailty and 20.1% (316/1575) were at nutritional risk, and the overlap prevalence of frailty and nutritional risk is 9.0% (142/1575). Frailty and nutritional risk occur in no more than 3% of outpatients. The prevalence of frailty and nutritional risks in patients with cancer and diabetes was shown in online supplemental table 1. Frailty and nutritional risk have a low and significant correlation (rs=0.304 to 0.402, p<0.001), whether in the elderly, inpatients, outpatients and patients with cancer or diabetes (online supplemental table 1).

Supplemental material

Correlation between risk factors and fatigue in all older adult patients

The incidence of fatigue in older adult patients was 37.3% (752/2016). Univariate logistic regression analysis indicated that gender, age, marriage, education level, nutritional risk, polypharmacy, cancer and diabetes mellitus were associated with a significantly increased incidence of fatigue (figure 2). Multivariate analysis further showed that age (OR 1.015, 95% CI 1.000 to 1.029, p=0.049), marriage (OR 1.458, 95% CI 1.121 to 1.896, p=0.005), education level (OR 1.413, 95% CI 1.140 to 1.750, p=0.002), nutritional risk (OR 3.109, 95% CI 2.384 to 4.056, p<0.001), polypharmacy (OR 2.525, 95% CI 2.073 to 3.075, p<0.001), cancer (OR 2.010, 95% CI 1.532 to 2.637, p<0.001), except for gender (p=0.075), diabetes mellitus (p=0.123), smoke (p=0.964) and alcohol drink (p=0.419) are independent risk factors for fatigue (figure 3).

Figure 2
Figure 2

Univariate logistic regression analysis of risk factors associated with fatigue in older adult patients (n=2016).

Figure 3
Figure 3

Multivariate logistic regression analysis of risk factors associated with fatigue in older adult patients (n=2016). Multivariate logistic regression analysis (forward: likelihood ratio) was used to analyse all related factors, and there was no statistically significant difference in gender (p=0.075), diabetes mellitus (p=0.123), smoke (p=0.964) and alcohol drink (p=0.419) in the fully adjusted model.

Correlation between risk factors and fatigue in older adult inpatients

Univariate logistic regression analysis indicated that gender, age, marriage, education level, nutritional risk, polypharmacy, cancer and diabetes mellitus were associated with a significantly increased incidence of fatigue. Multivariate analysis further showed that in addition to gender female (p=0.063), age (p=0.927), smoke (p=0.610) and alcohol drink (p=0.152), marriage, education level, nutritional risk (OR 2.717, 95% CI 2.068 to 3.571, p<0.001), polypharmacy, cancer and diabetes mellitus are independent risk factors for fatigue (table 2).

Table 2

Univariate and multivariate logistic regression analysis of risk factors associated with fatigue in older adult inpatients (n=1575)

Discussion

Our study mainly found that frailty and nutritional risk were prevalent in older adult patients, and the prevalence of the two differed in different diseases. There is a certain overlap of frailty and nutritional risk in older adult patients, especially in older adult inpatients. Ageing, nutritional risk, polypharmacy and having a malignancy increased the occurrence of fatigue.

A broad range of sociodemographic, physical, biological, lifestyle and psychological factors have been found to be longitudinally associated with frailty.28 As malnourished patients experienced a higher risk of frailty, several studies have suggested a considerable overlap between nutritional status and frailty.29 30 On the one hand, all the frailty indicators are more or less affected by poor eating habits. Insufficient protein and energy intake and chronic undernutrition led to weight loss and sarcopenia, which may cause low muscle strength and feelings of fatigue. On the other hand, frailty itself may have a negative impact on eating and nutritional status.30 An observational study found that 65% of the frail subjects were at risk of malnutrition, and 10% were malnourished.31 Besides, another observational study strongly supported the association between malnutrition and frailty, as most malnutrition-related parameters were related to frailty, and low serum vitamin D even significantly increased the risk of death in frail populations.32 Ligthart-Melis et al’s17 meta-analysis found a high association (OR 5.77, 95% CI 3.88, 8.58, p<0.0001, I2=42.3%) and considerable overlap (49.7%) between physical (pre-) frailty and (risk of) malnutrition.

Fatigue can be described as a symptom of malnutrition and frailty.33 Fatigue is closely related to adverse outcomes, significantly increasing medical costs and reducing the quality of life.16 34 A recent systematic review classified fatigue-related factors into four aspects: biological, behavioural, psychological and social levels, and poor nutritional status was included in the behavioural levels.35 Poor nutritional status is thought to be one of the pathophysiological mechanisms of fatigue, and alterations in food intake and body composition appear to influence the feelings of fatigue, possibly through inflammation and/or mitochondrial dysfunction.19 36 Knoop et al37 showed that low muscle endurance combined with high fatigue could predict changes in activities of daily living at 1 year of follow-up, and these parameters may be well suited to assess intrinsic abilities in the concept of frailty. Wei et al38 supported a significant positive correlation between nutritional status and fatigue in postoperative patients with colorectal cancer through an observational study.

Regarding the implementation of fatigue, frailty and nutritional risk interventions, our findings support screening older adult patients for frailty and nutritional risk and clinical intervention to reverse the progression of fatigue, frailty and malnutrition. Physical frailty management guidelines recommend addressing modifiable causes of fatigue and addressing polypharmacy to develop a comprehensive frailty management plan.39 40 Fatigue management strategies include strengthening physical activity, improving sleep and nutritional support to compensate for inadequate energy and protein intake to meet an individual’s specific needs that may help combat fatigue.33 41

The strength of our study is that it focuses on both frailty and nutritional risk, two disease states associated with poor outcomes in older adult patients and explores the factors that influence fatigue, one indicator of frailty that has received less research attention. Our study has several limitations. First, this study was a cross-sectional single-city study and could not show a causal relationship between nutritional risk and fatigue; prospective multi-city cohort studies can be designed for further exploration. Second, due to the limitation of the research design, only a few related influencing factors were collected. Finally, the study only used the FRAIL scale and NRS-2002, which are screening tools but not diagnostic tools with higher accuracy to define frailty and nutritional status.

Frailty and nutritional risk are prevalent among older adult patients, and nutritional risk is associated with the occurrence of fatigue. Factors such as nutritional risk should be considered when developing interventions aimed at preventing and/or reducing the burden associated with fatigue in older adult patients.

Data availability statement

Data are available upon reasonable request.

Ethics statements

Patient consent for publication

Ethics approval

This study involves human participants and was approved by the Ethics Committee of Beijing Hospital (approval number: 2021BJYYEC-003-01). Participants gave informed consent to participate in the study before taking part.

Acknowledgments

We thank all subjects who participated in our study.

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