Abstract
Background
Our study aimed to evaluate change in sarcopenia, its defining components over 1 year follow‐up and investigate associations with subsequent cognitive decline, incident mild cognitive impairment (MCI) and dementia among patients undergoing haemodialysis (HD).
Methods
In the multicentre, longitudinal study, 1117 HD patients aged 56.8 ± 14.3 years (654 men; and 463 women) from 17 dialysis centres in Guizhou Province, China, were recruited in 2019 and followed up for 1 year in 2020. Sarcopenia was diagnosed with Asian Working Group for Sarcopenia criteria using appendicular skeletal muscle mass index (ASMI) and handgrip strength (HGS). Body composition was measured using body composition monitor; body water, weight, and height were corrected to calculate ASMI. HGS was measured by mechanical handgrip dynamometer. Cognitive function was measured with Mini Mental State Examination. Multivariate linear, logistic regression models and subgroup analyses were employed to examine the associations of changes in sarcopenia, ASMI, and HGS with Mini Mental State Examination score change, and incident MCI, dementia.
Results
Four hundred fourteen (37.1%) patients had sarcopenia at baseline; during 1 year follow‐up, 257 (23.0%) developed MCI and 143 (12.8%) developed dementia. According to changes in sarcopenia, patients were stratified into four groups: non‐sarcopenia; non‐sarcopenia to sarcopenia; sarcopenia; and sarcopenia to non‐sarcopenia. HD patients in sarcopenia and non‐sarcopenia to sarcopenia groups had higher risk of MCI (34.8%, 32.0%, vs. 17.4%) and dementia (20.6%, 19.8%, vs. 8.7%), compared non‐sarcopenia group (P < 0.001). Multivariate linear regression analyses showed that sarcopenia [regression coefficients (β) −1.098, 95% confidence interval (CI) −1.872, −0.324, P = 0.005] and non‐sarcopenia to sarcopenia (β −1.826, −2.441, −1.212, P < 0.001) were associated with faster cognitive decline compared to non‐sarcopenia. HGS decline (β 0.046, 0.027–0.064, P < 0.001) and ASMI decline (β 0.236, 0.109–0.362, P < 0.001) were both positively associated with cognitive decline. Multivariate logistic regression analyses demonstrated that patients with sarcopenia and non‐sarcopenia to sarcopenia were both at increased risk of developing MCI [odds ratio (OR) 1.788, 95% CI 1.115–2.870, P = 0.016 and OR 1.589, 95% CI 1.087–2.324, P = 0.017, respectively], but only non‐sarcopenia to sarcopenia was at increased risk of dementia (OR 1.792, 95% CI 1.108–2.879, P = 0.017). Both greater change of ASMI and HGS had lower risk of MCI with adjusted ORs of 0.857 (0.778–0.945, P = 0.002) and 0.976 (0.963–0.989, P < 0.001). Robust associations were found among female individuals, aged >60 years, and with low educational level.
Conclusions
Longitudinal associations were observed between new‐onset, persistent sarcopenia, and cognitive impairment. Early detection and intervention should be implemented to delay the onset of sarcopenia and improve cognitive health among HD patients.
Keywords: Sarcopenia, Mild cognitive impairment, Dementia, Haemodialysis
Introduction
End‐stage kidney disease (ESKD) is the most advanced stage of chronic kidney disease (CKD) and requires renal replacement therapy. Haemodialysis (HD) has been performed in more than 80% of patients with ESKD, 1 , 2 and the number of patients undergoing HD has increased as life expectancy and the incidence of CKD such as diabetes mellitus (DM) or hypertension has increased. 2 , 3 Patients undergoing maintenance HD face considerable disease challenges, such as poor quality of physical, mental, and functional health status, high disease burden and increased mortality rates, although the technology has sustained life in most 3 million ESKD patients worldwide over the past 70 years. 4 , 5 In recent years, cognitive impairment is increasingly being recognized as one of the most prevalent complications among HD patients, with the incidence estimated to be as high as 70%, which is approximately up to three times higher than for age‐matched general population. 6 , 7 , 8 Impaired cognition has been linked to worse quality of life, decreased adherence to medications, reduced decision‐making ability, and, more importantly, greater risk for poor prognosis, including hospitalization, withdrawal from dialysis, and mortality. 9 , 10 Besides common risk factors for cognitive impairment, such as chronic inflammation, malnutrition, and anabolic hormone deficiency, sarcopenia has mainly been regarded as a risk factor for cognitive impairment in HD patients. 9 , 10 , 11
Sarcopenia is a syndrome characterized by the progressive loss skeletal muscle mass, strength, and function. 12 CKD is one of the most important aetiologies of secondary sarcopenia, 13 especially when HD is required, due to multicausal aetiology that overlap with traditional factors of sarcopenia, including advanced age, more rapid and greater muscle loss than that in the general population. 14 , 15 Hence, sarcopenia has become an emerging concern in patients undergoing long‐term HD. Sarcopenia has been proven to be significantly associated with adverse health outcomes such as metabolic dysfunction, malnutritional status, mental disorders, decreased quality of life and functionality, increased hospitalization rates, healthcare costs, morbidity, and mortality. 16 , 17
Understanding the complex interrelationships between sarcopenia and cognitive impairment is critical because of the high prevalence of these conditions in HD populations. Several previous studies have demonstrated the association between sarcopenia and cognitive impairment among general population. 12 , 18 , 19 , 20 They showed that participants with possible sarcopenia or sarcopenia at baseline were more likely to develop new‐onset cognitive impairment in longitudinal analyses. Actually, sarcopenia status may constantly change; therefore, these prognostic values for cognitive impairment might also change over time, especially for HD patients. However, few studies have investigated the association between change in sarcopenia status, including change in muscle mass and strength, and cognitive impairment. Only a recent study has identified the association between decreasing handgrip strength and decline in cognitive function among community‐dwelling adults. 21
To our data, there is scarcity of information on the relationship between sarcopenia and cognitive impairment among HD patients, in particular the dynamic change of sarcopenia status occurring over time. To fill the research gap, we aimed to investigate the longitudinal associations of changes in sarcopenia and its defining components with cognitive decline, incident mild cognitive impairment (MCI), and dementia in the Chinese HD population.
Methods
Study protocol
This was a multicentre, longitudinal study, with the baseline survey and examination conducted from May 2019 to September 2019, and the follow‐up examination from May 2020 to September 2020. The cohort consisted of patients undergoing HD treated in 17 dialysis centres in Guizhou Province, China. The study was approved by the Ethics and Research Committee of Guizhou Provincial People's Hospital (approval number: [2020]208) and adhered to the Declaration of Helsinki and subsequent amendments. The included patients were informed and provided written informed consent. Trained research doctors performed the baseline and follow‐up assessments through face‐to‐face questionnaire interviews and physical measurements.
Patient population
Patients were eligible for inclusion if aged ≥18 years old, undergoing HD for at least 3 months, two/three times per week, with each session lasting 3–4 h, ability to ambulate without an assistive device, ability of communicate with the interviewer, and who had data available on body composition, muscle strength, and cognitive function both at baseline and 1 year follow‐up period. We excluded patients if they (i) were without cognitive measurements or sarcopenia measurements whether at baseline or follow‐up and (ii) were evaluated as cognitive impairment at baseline. More details on the inclusion process of studied populations were provided in Figure 1 .
Figure 1.
Flow chat of the study. HD, haemodialysis; MCI, mild cognitive impairment.
Assessment of sarcopenia and its components
The diagnosis of sarcopenia was based on the criteria stated in the Asian Working Group for Sarcopenia (AWGS) 2019 Consensus. 22 Muscle mass was determined using appendicular skeletal muscle mass index (ASMI) and muscle strength was determined using handgrip (HGS).
Appendicular skeletal muscle mass index
Body composition, including overhydration, total body water, extracellular water, intracellular water, lean tissue index, and fat tissue index, was measured using body composition monitor (BIA, BCM, Fresenius Medical Care, Germany) at dialysis sessions held in the middle of the week. Patients rested for 10 min in a supine position, and then BIA measurements were recorded. The appendicular skeletal muscle mass (ASM) was calculated with the Ting‐Yun Lin's prediction equation: ASM (kg) = −1.838 + 0.395 × total body water (L) + 0.105 × body weight (kg) + 1.231 × male sex − 0.026 × age (years) (R2 = 0.914, standard error of estimate = 1.35 kg). The equation has been proven to have a good agreement with the ASM assessed by dual‐energy X‐ray absorptiometry in a previous study for haemodialysis patients in Taiwan. 23 According to the recommended method, the ASMI was defined as ASM (kg) divided by its corresponding squared height (m2). Low muscle mass was defined as ASMI < 7.0 kg/m2 for male and <5.7 kg/m2 for female based on the BIA.
Muscle strength
Muscle strength was determined using HGS by a mechanical handgrip dynamometer in the arm contrary to the arteriovenous fistula. Patients were examined in the sitting position, depending on their ability, and the higher of the two measurements obtained from the non‐fistula hand was used in the analysis. Low muscle strength was defined as HGS < 28 kg for male and <18 kg for female according to diagnostic criteria of sarcopenia. 22
Sarcopenia and change status
Sarcopenia was diagnosed if participants had low muscle mass plus low muscle strength. According to the changes in sarcopenia, patients were stratified into four groups: (i) non‐sarcopenia: non‐sarcopenia both in 2019 and 2020; (ii) non‐sarcopenia to sarcopenia: non‐sarcopenia in 2019 but progressed to sarcopenia in 2020; (iii) sarcopenia to non‐sarcopenia: sarcopenia in 2019 and improved to non‐sarcopenia in 2020; and (iv) sarcopenia: sarcopenia both in 2019 and 2020. The asymmetry in HGS and ASMI was calculated by subtracting the value in 2019 from the value in 2020 of HGS and ASMI, respectively. The change of the asymmetry was then divided into two groups: (i) decreased and (ii) same or increased.
Assessment of cognitive impairment
Cognitive function was assessed using the Mini Mental State Examination (MMSE) questionnaire by professional doctors. It assessed cognitive function in five components, including orientation, registration, attention and calculation, recall, and language. The scores range from 0 to 30 points, with higher scores denoting better cognitive function. A score of 30–27 points means no cognitive dysfunction. A score <27 on the MMSE can be diagnosed as MCI and <23 on the MMSE as dementia. 24 Every patient completed the MMSE scores at baseline and follow‐up.
Covariates
The covariates included in the analysis were as follows: (i) sociodemographic characteristics, regarding age, sex, and educational levels; (ii) lifestyle behaviours, including smoking, drinking, and working status; (3) disease characteristics, including primary diseases of ESKD, dialysis vintages, the presence of hypertension and diabetes mellitus (DM), mean arterial pressure; (iv) anthropometric measurements, including body weight, height, midarm circumference (MAC), triceps skinfold (SKF) thickness, midarm muscle circumference (MAMC), waist, hip, and calf circumference; (v) laboratorial measurements, including haemoglobin (g/L), serum albumin (g/L), creatinine (μmol/L), uric acid (mmol/L), high‐sensitive C‐reactive protein (hs‐CRP) (mmol/L), total cholesterol (CHOL) (mmol/L), and triglycerides (TG).
A standardized questionnaire including demographic, sociological, characteristics, and lifestyle and disease history was conducted by trained interviewers. Age was modelled as continuous variables (in years). Sex was defined as male or female. Educational levels were classified as high education (>12th grade) and low education (<12th grade). Smoking, drinking, and working status were all classified as ‘yes’ or ‘no’. Hypertension and DM were both defined as a patient‐reported history and a medical record of responding diagnosis or medication (yes, no). All anthropometric measurements were performed by two trained nephrologists to avoid inter‐observer bias. SKFs were measured using an SKF calliper on the non‐fistula arm. MAMC was derived from MAC and TSF with the equation of Heymsfield et al., MAMC (cm) = MAC (cm) − TSF (cm) × π. 25 Body mass index was calculated as weight in kilograms divided by the square of height in meters (BMI, kg/m2). Laboratorial measurements were performed before the dialysis session and were collected from the medical records.
Statistical analyses
The normal distribution was tested using the Kolmogorov–Smirnov test. Normally distributed continuous variables were described as means and SDs, and non‐normally distributed continuous variables were expressed as median and interquartile range. Categorical variables were expressed as counts (percentages). Characteristics of participants according to changes in sarcopenia were compared using the analysis of variance test, Wilcoxon rank‐sum test, χ 2 test, and Fisher's exact test for normally distributed continuous variables, non‐normally distributed continuous variables, categorical variables, and categorical variables with small expected values, respectively. Multivariate linear regression models were employed to examine the association between changes in sarcopenia, its defining components, and MMSE score change. The results were presented as regression coefficients (β) and 95% confidence intervals (95% CI). Logistic regression models were used to examine the associations between changes in sarcopenia, its defining components and incident MCI, and dementia. The results were presented as odd ratios (OR) with 95% CIs. We adjusted for variables with P < 0.05 on univariate analyses in the multivariate analyses. When estimating the effects of sarcopenia status, handgrip strength, muscle mass, and cognitive function, only one of these variables was included as an explanatory variable in the regression model. The analyses were conducted in a subgroup of paired patients and spouses using adjusted conditional logistical regression models. The value of P < 0.05 was be considered statistically significant. All analyses were performed using SPSS version 23.0 and R software version 4.1.1.
Results
Subject characteristics
A total of 1117 HD patients who met inclusion criteria and completed all follow‐up assessments were included for analysis. The detailed process of patient selection is shown in Figure 1. Among the included HD patients, 654 (58.5%) were male, and the mean age was 56.8 years. 24.9% were smokers, 6.4% were drinkers, and 6.6% were still working. The most common cause of ESKD was diabetic nephrology (23.8%), followed by hypertensive nephrology (21.5%). 76.3% of HD patients had hypertension and 29.8% had DM. The median dialysis vintage was 43.1 months, and 86.8% of patients used arteriovenous fistula as vascular access (Table 1 ).
Table 1.
Clinical characteristics of HD patients according to change in sarcopenia status (n = 1117)
| Variables | All patients (N = 1117) | Non‐sarcopenia (n = 425) | Sarcopenia to non‐sarcopenia (n = 273) | Sarcopenia (n = 141) | Non‐sarcopenia to sarcopenia (n = 278) | P‐value |
|---|---|---|---|---|---|---|
| Epidemiologic and clinical variables | ||||||
| Age, years | 56.8 ± 14.3 | 52.8 ± 13.5 | 56.1 ± 13.8 | 63.7 ± 13.2 | 60.0 ± 14.6 | <0.001 |
| Male, n (%) | 654 (58.5%) | 199 (46.8%) | 228 (83.5%) | 109 (77.3%) | 118 (42.4%) | <0.001 |
| Educational level (>12th grade), n (%) | 349 (31.2%) | 143 (33.6%) | 92 (33.7%) | 38 (27.0%) | 76 (27.3%) | 0.165 |
| HD vintages, months | 43.1 (18.8, 67.5) | 43.1 (18.9, 66.9) | 42.3 (17.8, 67.0) | 54.0 (29.4, 77.5) | 42.8 (18.8, 78.6) | 0.436 |
| Vascular access, AVF, n (%) | 969 (86.8%) | 385 (90.6%) | 243 (89.0%) | 115 (81.6%) | 226 (81.3%) | 0.001 |
| Smoking, n (%) | 278 (24.9%) | 84 (22.1%) | 89 (32.6%) | 40 (28.4%) | 55 (19.8%) | <0.001 |
| Drinking, n (%) | 72 (6.4%) | 32 (7.5%) | 21 (7.7%) | 10 (7.1%) | 9 (3.2%) | 0.095 |
| Working, n (%) | 109 (6.6%) | 29 (6.8%) | 27 (9.9%) | 9 (6.4%) | 14 (5.0%) | 0.158 |
| Primary cause of ESKD | 0.088 | |||||
| Glomerulonephritis, n (%) | 222 (19.9%) | 81 (19.1%) | 45 (16.5%) | 31 (22.0%) | 65 (23.4%) | |
| Diabetic nephrology, n (%) | 266 (23.8%) | 86 (20.2%) | 79 (28.9%) | 41 (29.1%) | 60 (21.6%) | |
| Hypertensive nephrology, n (%) | 240 (21.5%) | 101 (23.8%) | 53 (19.4%) | 25 (17.7%) | 61 (21.9%) | |
| Others n (%) | 389 (34.8%) | 157 (36.9%) | 96 (35.2%) | 44 (31.2%) | 92 (33.1%) | |
| Hypertension, n (%) | 852 (76.3%) | 320 (75.3%) | 220 (80.6%) | 107 (75.9%) | 205 (73.7%) | 0.258 |
| Diabetes mellitus, n (%) | 333 (29.8%) | 102 (24.0%) | 100 (36.6%) | 54 (38.3%) | 77 (27.7%) | <0.001 |
| MAP, mmHg | 99.1 ± 13.4 | 99.3 ± 13.7 | 98.6 ± 13.4 | 98.4 ± 12.8 | 99.5 ± 13.5 | 0.798 |
| Anthropometric measurements | ||||||
| BMI, kg/m2 | 23.1 ± 3.6 | 24.1 ± 3.8 | 21.7 ± 2.9 | 21.6 ± 2.6 | 23.7 ± 3.6 | <0.001 |
| Waist circumference, cm | 83.9 ± 10.7 | 85.8 ± 10.9 | 79.8 ± 9.4 | 81.9 ± 8.9 | 85.8 ± 11.2 | <0.001 |
| Hip circumference, cm | 90.1 ± 7.6 | 91.5 ± 7.7 | 87.0 ± 7.0 | 88.7 ± 6.4 | 91.8 ± 7.4 | <0.001 |
| MAMC, cm | 22.2 ± 3.5 | 22.6 ± 3.1 | 21.2 ± 4.9 | 21.3 ± 2.1 | 23.0 ± 2.4 | <0.001 |
| Calf‐circumference, mm | 32.4 ± 3.4 | 33.2 ± 3.5 | 30.6 ± 2.6 | 31.0 ± 2.9 | 33.7 ± 3.4 | <0.001 |
| ASMI, kg/m2 | 6.7 ± 0.8 | 6.8 ± 0.9 | 6.6 ± 0.8 | 6.5 ± 0.7 | 6.8 ± 0.9 | 0.001 |
| HGS, kg | 22.0 ± 9.0 | 23.8 ± 9.7 | 17.1 ± 5.3 | 17.3 ± 5.7 | 26.5 ± 8.8 | <0.001 |
| Body composition | ||||||
| LTI, kg/m2 | 15.2 ± 3.0 | 16.0 ± 2.8 | 13.6 ± 2.3 | 13.7 ± 2.4 | 16.6 ± 2.8 | <0.001 |
| FTI, kg/m2 | 7.5 ± 4.1 | 7.7 ± 4.3 | 7.7 ± 4.0 | 7.6 ± 3.6 | 6.9 ± 4.2 | 0.070 |
| OH, L | 0.6 (−0.4, 1.8) | 0.6 (−0.4, 1.9) | 0.5 (−0.5, 1.3) | 0.6 (−0.4, 1.9) | 0.6 (−0.4, 2.0) | 0.826 |
| TBW, L | 33.5 ± 6.2 | 35.0 ± 5.7 | 28.7 ± 3.9 | 30.6 ± 4.6 | 37.3 ± 5.8 | <0.001 |
| ECW/ICW ratio | 0.81 ± 0.14 | 0.80 ± 0.13 | 0.83 ± 0.15 | 0.83 ± 0.14 | 0.79 ± 0.13 | 0.001 |
| Laboratory data | ||||||
| Haemoglobin, g/L | 109.0 ± 21.8 | 107.5 ± 21.2 | 107.5 ± 21.8 | 111.1 ± 22.1 | 111.6 ± 22.1 | 0.033 |
| Serum albumin, g/L | 40.7 ± 5.1 | 40.8 ± 5.1 | 40.2 ± 5.2 | 40.4 ± 4.7 | 41.0 ± 5.0 | 0.238 |
| Creatinine, μmol/L | 897.6 ± 333.2 | 929.4 ± 328.2 | 825.0 ± 284.0 | 788.0 ± 325.0 | 976.0 ± 361.6 | <0.001 |
| Uric acid, μmol/L | 426.8 ± 130.5 | 436.2 ± 131.1 | 411.0 ± 130.3 | 415.4 ± 128.3 | 433.8 ± 129.6 | 0.044 |
| Hs‐CRP, mg/L | 2.9 (1.2, 7.8) | 2.9 (1.1, 6.5) | 2.6 (1.0, 7.0) | 3.9 (1.8, 9.0) | 2.7 (1.3, 9.7) | 0.108 |
| Total cholesterol, mmol/L | 3.8 (3.2, 4.4) | 3.8 (3.2, 4.4) | 4.1 (3.4, 4.8) | 3.8 (3.1, 4.4) | 3.6 (3.2, 4.3) | <0.001 |
| Triglycerides, mmol/L | 1.5 (1.0, 2.2) | 1.6 (1.1, 2.4) | 1.5 (1.0, 2.2) | 1.3 (0.9, 1.8) | 1.3 (1.0, 2.0) | 0.001 |
P < 0.05 was considered statistically significant. Values were expressed as mean ± SD, median (25th–75th percentile), or frequency (percentage) as appropriate.
ASMI, appendicular skeletal muscle mass index; AVF, arteriovenous fistula; BMI, body mass index; CRP, C reactive protein; ECW/ICW ratio, extracellular water/intracellular water ratio; ESKD, end‐stage kidney disease; FTI, fat tissue index; HD, haemodialysis; HGS, handgrip strength; LTI, lean tissue index; MAMC, aim muscular circumference; MAP, mean arterial pressure; OH, overhydration; TBW, total body water.
Based on AWGS 2019 criteria, 414 (37.1%) patients were diagnosed with sarcopenia at baseline. During 1 year follow‐up, 278 (24.9%), patients without sarcopenia developed sarcopenia, 141 (12.6%) with persistent sarcopenia status, while 425 (38.0%) with persistent non‐sarcopenia status. Table 1 shows the demographic, nutritional, clinical characteristics of all participants according to change in sarcopenia. Compared with those without sarcopenia, patients with new‐onset sarcopenia were more likely to be more advanced age, lower education, less likely to drinking, and had higher total body water and lean tissue index levels, while lower fat tissue index levels.
Table 2 shows a summary of cognitive function measured by MMSE according to change in sarcopenia. During 1 year follow‐up, 257 (23.0%) developed MCI and 143 (12.8%) developed dementia. The persistent sarcopenic and new‐onset sarcopenic HD patients showed significantly higher risk of MCI and dementia (P < 0.001) (Figure 2).
Table 2.
Cognitive impairment according to change in sarcopenia status among HD patients
| Variables | All patients (N = 1117) | Non‐sarcopenia (n = 425) | Sarcopenia to non‐sarcopenia (n = 273) | Sarcopenia (n = 141) | Non‐sarcopenia to sarcopenia (n = 278) | P‐value |
|---|---|---|---|---|---|---|
| Baseline MMSE score | 28.1 ± 1.7 | 28.1 ± 1.7 | 28.0 ± 1.7 | 27.9 ± 1.8 | 28.5 ± 1.5 | 0.001 |
| One year MMSE score | 27.8 ± 3.8 | 28.3 ± 3.3 | 28.3 ± 3.3 | 27.0 ± 3.9 | 26.9 ± 4.5 | <0.001 |
| △MMSE score | −2.0 (−3.0, 0.0) | −1.0 (−3.0, 0.0) | −1.0 (−2.0, 0.0) | −2.0 (−5.0, 0.0) | −2.0 (−5.3, −1.0) | <0.001 |
| MCI, n (%) | 257 (23.0%) | 74 (17.4%) | 45 (16.5%) | 49 (34.8%) | 89 (32.0%) | <0.001 |
| Dementia, n (%) | 143 (12.8%) | 37 (8.7%) | 22 (8.1%) | 29 (20.6%) | 55 (19.8%) | <0.001 |
P < 0.05 was considered statistically significant.
HD, haemodialysis; MCI, mild cognitive impairment; MMSE, Mini Mental State Examination.
Figure 2.
Prevalence of cognitive impairment in HD patients stratified by change in sarcopenia.
Associations between changes in sarcopenia, handgrip strength, appendicular skeletal muscle mass index, and cognitive decline
Table 3 depicts the associations between change in sarcopenia status, its defining components, and cognitive decline. Compared with those in the non‐sarcopenia group, those in the persistent sarcopenia group was associated with an additional 1.10 faster cognitive decline (P = 0.005), and those in the new‐onset sarcopenia group was associated with an additional 1.83 faster cognitive decline (P < 0.001). As the defining components of sarcopenia, HGS, and ASMI change were both positively associated with MMSE score (β = 0.046, 0.236, respectively, both P < 0.001).
Table 3.
Longitudinal associations of change in sarcopenia status, ASMI, HGS with cognitive decline among HD patients
| Variables | MMSE score | ||
|---|---|---|---|
| β * | 95% CI | P value | |
| Change in sarcopenia status | |||
| Non‐sarcopenia | Reference | ||
| Sarcopenia to non‐sarcopenia | 0.049 | −0.568, 0.667 | 0.875 |
| Sarcopenia | −1.098 | −1.872, −0.324 | 0.005 |
| Non‐sarcopenia to sarcopenia | −1.826 | −2.441, −1.212 | <0.001 |
| HGS change | 0.046 | 0.027, 0.064 | <0.001 |
| ASMI change | 0.236 | 0.109, 0.362 | <0.001 |
P < 0.05 was considered statistically significant.
β, regression coefficients; ASMI, appendicular skeletal muscle mass index; CI, confidence interval; HD, haemodialysis; HGS, handgrip strength; MMSE, Mini Mental State Examination.
Adjusted for age, sex, educational level, primary diseases, smoking, drinking, working status, hypertension, diabetes mellitus, dialysis vintage, mean arterial pressure, extracellular water/intracellular water ratio, calf circumference, and haemoglobin.
Associations between changes in sarcopenia, handgrip strength, appendicular skeletal muscle mass index, and mild cognitive impairment
Compared with those without sarcopenia, patients with persistent sarcopenia and those with non‐sarcopenia to sarcopenia were both at an increased risk of developing MCI (OR 1.788, 95% CI 1.115–2.870, P = 0.016 and OR 1.589, 95% CI 1.087–2.324, P = 0.017, respectively) after adjusting covariates.
We also analysed the associations between MCI and sarcopenia defining components, including ASMI and HGS. The results demonstrated that both greater change of ASMI and HGS had significant lower risk of MCI with multivariate‐adjusted ORs of 0.857 (95% CI 0.778–0.945, P = 0.002) and 0.976 (0.963–0.989, P < 0.001). However, only decreased HGS is associated with higher risk of MCI compared with same or increased HGS, as categorized variables (OR 1.679, 95% CI 1.222–2.036, P = 0.001). No significant differences between those with decreased ASMI and same or increased ASMI were found, as illustrated in Table 4 .
Table 4.
Associations of change in sarcopenia, ASMI, and HGS with mild cognitive impairment among HD patients
| Unadjusted model | Multivariable‐adjusted model* | |||||
|---|---|---|---|---|---|---|
| OR | 95% CI | P value | OR | 95% CI | P value | |
| Sarcopenia trajectory | ||||||
| Non‐sarcopenia | Reference | Reference | ||||
| Sarcopenia to non‐sarcopenia | 0.750 | 0.624–1.405 | 0.750 | 0.907 | 0.581–1.417 | 0.669 |
| Sarcopenia | 2.526 | 1.647–3.875 | <0.001 | 1.788 | 1.115–2.870 | 0.016 |
| Non‐sarcopenia to sarcopenia | 2.234 | 1.565–3.187 | <0.001 | 1.589 | 1.087–2.324 | 0.017 |
| ASMI change (cm) | 0.888 | 0.822–0.960 | 0.003 | 0.857 | 0.778–0.945 | 0.002 |
| Change status in ASMI | ||||||
| Same or increased | Reference | Reference | ||||
| Decreased | 1.247 | 0.942–1.651 | 0.122 | 1.085 | 0.789–1.493 | 0.615 |
| HGS change (kg) | 0.968 | 0.957–0.979 | <0.001 | 0.976 | 0.963–0.989 | <0.001 |
| Change status in HGS | ||||||
| Same or increased | Reference | Reference | ||||
| Decreased | 2.252 | 1.671–3.036 | <0.001 | 1.679 | 1.222–2.306 | 0.001 |
P < 0.05 was considered statistically significant.
ASMI, appendicular skeletal muscle mass index; CI, confidence interval; HD, haemodialysis; HGS, handgrip strength; OR, odd ratio.
Adjusted for age, sex, educational level, primary diseases, smoking, drinking, working status, hypertension, diabetes mellitus, dialysis vintage, mean arterial pressure, extracellular water/intracellular water ratio, calf circumference, and haemoglobin.
Associations between changes in sarcopenia, handgrip strength, appendicular skeletal muscle mass index, and dementia
Compared with those without sarcopenia, only patients with non‐sarcopenia to sarcopenia were at increased risk of developing dementia (OR 1.792, 95% CI 1.108–2.879, P = 0.017) after adjusting covariates. When analysing the associations of HGS, ASMI, and dementia, the trends were similar with those of MCI, which were shown in Table 5 .
Table 5.
Associations of change in sarcopenia status, ASMI, and HGS with dementia among HD patients
| Unadjusted model | Multivariable‐adjusted model* | |||||
|---|---|---|---|---|---|---|
| OR | 95% CI | P value | OR | 95% CI | P value | |
| Sarcopenia trajectory | ||||||
| Non‐sarcopenia | Reference | Reference | ||||
| Sarcopenia to non‐sarcopenia | 0.919 | 0.530–1.595 | 0.764 | 0.828 | 0.447–1.533 | 0.548 |
| Sarcopenia | 2.715 | 1.599–4.611 | <0.001 | 1.719 | 0.945–3.129 | 0.076 |
| Non‐sarcopenia to sarcopenia | 2.586 | 1.652–4.049 | <0.001 | 1.792 | 1.108–2.897 | 0.017 |
| ASMI change (cm) | 0.859 | 0.779–0.948 | 0.002 | 0.814 | 0.718–0.922 | 0.001 |
| Change status in ASMI | ||||||
| Same or increased | Reference | Reference | ||||
| Decreased | 1.401 | 0.981–2.001 | 0.064 | 1.332 | 0.874–2.030 | 0.182 |
| HGS change (kg) | 0.964 | 0.951–0.979 | <0.001 | 0.978 | 0.961–0.995 | 0.013 |
| Change status in HGS | ||||||
| Same or increased | Reference | Reference | ||||
| Decreased | 2.585 | 1.742–3.837 | <0.001 | 1.663 | 1.072–2.579 | 0.023 |
P < 0.05 was considered statistically significant.
ASMI, appendicular skeletal muscle mass index; CI, confidence interval; HD, haemodialysis; HGS, handgrip strength; OR, odd ratio.
Adjusted for age, sex, educational level, primary diseases, smoking, drinking, working status, hypertension, diabetes mellitus, dialysis vintage, mean arterial pressure, extracellular water/intracellular water ratio, calf circumference, and haemoglobin.
Subgroup analyses
In addition, we analysed the associations between change in sarcopenia and MCI, dementia in a subgroup analysis that was stratified by age, sex, and educational level. Both non‐sarcopenia to sarcopenia and persistent sarcopenia were robust associated with MCI among individuals with aged >60 years and low educational level, while only persistent sarcopenia was robust associated with MCI among female individuals. For analysis on dementia, non‐sarcopenia to sarcopenia had a stronger association with dementia among individuals with aged >60 years, female, and low educational level, and persistent sarcopenia only had a stronger association among those with low educational level (Figure 3 ).
Figure 3.
Subgroup analyses for change in sarcopenia predicting cognitive impairment in HD patients. Model was adjusted for age, sex, educational level, primary diseases, smoking, drinking, working status, hypertension, diabetes mellitus, dialysis vintage, mean arterial pressure, extracellular water/intracellular water ratio, calf circumference, and haemoglobin levels. CI, confidence intervals; OR, odds ratio.
Discussion
To the best of our knowledge, this is the first study to evaluate the longitudinal associations between change in sarcopenia and cognitive decline, incident MCI, and dementia among HD patients from multiple dialysis centres of the southwestern China. We found that compared with those of persistently non‐sarcopenia, both HD patients of initially non‐sarcopenia and then sarcopenia and persistently sarcopenia were associated with accelerated cognitive decline, a higher risk of incident cognitive impairment and dementia, especially in female, older individuals, and those with low educational level. In addition, decreased handgrip strength and muscle mass were also associated with MCI and dementia.
In our study, the prevalence of sarcopenia at baseline among HD patients was 37.1%, which was similar with those reported in previous studies. 12 , 15 , 16 , 17 A recent meta‐analysis revealed the prevalence of sarcopenia varied from 25.9% to 34.6% in dialysis patients. 17 A study based on 346 Chinese HD patients reported 32.66% had sarcopenia diagnosed with ASWG criteria. 18 A lower prevalence of sarcopenia was reported in a multicentre cross‐sectional study from East China (18.1%), 26 while in another single‐centre cross‐sectional study, 49.2% of 238 East Chinese dialysis patients were diagnosed with sarcopenia. 27 The clinical heterogeneity of prevalence mainly depended on the differences in sample size, ethnicity, diagnostic criteria, assessment procedures, and diagnostic thresholds for sarcopenia. 19 In addition, this study demonstrated that 39.5% developed sarcopenia among HD patients without sarcopenia at baseline over 1 year follow‐up.
Our finding showed that 1 year change in sarcopenia status was associated with cognitive impairment. Compared with persistent non‐sarcopenia group, persistent sarcopenia was associated with 78% higher risk of cognitive impairment and 76% higher risk of dementia, in line with the previous studies reported risks range in community dwelling population, 18 , 19 , 20 , 21 although there is few research focusing on the relationship between sarcopenia and cognitive function in HD patients. A recent meta‐analysis using nine cross‐sectional and one longitudinal study from Asia and western countries demonstrated a significant association between sarcopenia and cognitive impairment (pooled OR 2.50, 95% CI 1.26–4.95). 17 Hu et al. recently reported that individuals with sarcopenia were 1.72 times more likely to develop MCI than those without in a longitudinal analysis involving 2982 elderly adults in Chinese communities based on nationally representative data. 18 Ramoo et al. showed that adults with AWGS 2019‐based sarcopenia have 80% increased risk of cognitive impairment assessed by MMSE at 1 year follow‐up, compared with those without (OR 1.80, 95% CI 1.18–2.775) in a longitudinal study conducted by 1946 adults in Rural Malaysia. 19 Another longitudinal study among 496 Mexican adults demonstrated that sarcopenia was significantly associated with MCI (OR 1.74, 95% CI 1.02, 2.96). 20 Several cross‐sectional studies also reported the positive results, 28 , 29 while the others reported a non‐significant association. 30 The inconsistent findings could be caused by the different measuring tools of sarcopenia and cognitive function, study population, sample sizes, and study designs.
This study found that new‐onset sarcopenia was also an independent risk factor for cognitive impairment, and it exhibited an accelerated descent of cognitive score and a greater risk of dementia in the 1 year duration than new‐onset sarcopenia. These results showed that in addition to sarcopenia at a time in point, short‐time changes in sarcopenia status could be also an important basis for predicting future cognitive impairment, which is a new discovery that extends the results of previous studies. Therefore, early, successive detection of sarcopenia status and its deterioration is essential for proper identification of cognitive impairment among HD patients. Optimizing sarcopenia status may prevent cognitive impairment even over a relatively short follow up period. Moreover, these associations were more noticeable in female, older participants aged over 60 years and those with low educational level, and similar results have shown in previous study from the study, 12 , 17 suggesting that these subpopulations might be the most suitable to target for improvement of sarcopenia status where benefit may be greatest.
This present study analysed the association between changes in two sarcopenia defining components and cognitive impairment. The results showed that HGS and ASMI decline were both predictors of accelerated cognitive decline, incident MCI, and dementia with a dosage effect separately. For HGS, this is consistent with previous studies, which showed that HGS could be meaningful to monitor progression of cognitive decline. 21 , 31 However, results among previous studies regarding the association between low skeletal muscle mass and cognitive decline have been inconsistent. 32 , 33 In the current study, we found that ASMI decline was a predictor for cognitive decline, but decreased ASMI was not associated with incident MCI and dementia. Controversies among studies were mainly considered to be due to differences of body composition devices. 33 Whether ASMI and its change could be used as predictors of cognitive impairment for HD patients required more studies.
The specific mechanisms underlying the association between sarcopenia and cognitive decline remains inconclusive, but there are several plausible hypotheses. First, sarcopenia could trigger physical inactivity, even to disability, that could reduce expression of molecules related to learning and neural plasticity (brain derived neurotrophic factor and insulin growth factor 1), eventually leading to future cognitive decline. 34 Cognitive impairment alters the activity of neurotransmitters through the enhancement of central neuronal changes, resulting in the inadequate distribution of oxygen to the brain. The process leads to physical inactivity, which in turn is associated with sarcopenia. 35 Second, sarcopenia and cognitive impairment share some common risk factors, including inflammation, oxidative stress, malnutrition, and hormonal dysregulations, which has been called ‘common cause hypothesis’. 19 HD patients usually maintain low‐grade inflammatory status, which is considered to be associated with both conditions. High levels of inflammatory parameters, such as interleukin‐6, tumour necrosis factor‐α and C‐reactive protein, are associated with the loss of skeletal muscle and muscle strength and an increased risk of cognitive impairment. 36 Excessive oxidative stress induces the accumulation of molecular damage that has been associated with protein breakdown, causing mitochondrial dysfunction, apoptosis, inducing muscle atrophy, subsequently leading to sarcopenia. 37 Moreover, the products of oxidative stress are also the main risk factor for cognitive impairment. 38 A successive decline in the intake of essential foods caused by required restrictive diet, gastrointestinal symptoms, and urotoxic accumulation for HD patients could contribute to malnutrition, which mediates the relationship between sarcopenia and cognitive impairment. 39 As with hormonal dysregulations, low serum testosterone levels were associated with lower muscle mass, strength and were independent predictors of cognitive impairment. 12
Our study has several strengths. First, this is the first study to investigate the associations between changes in sarcopenia status and its defining components with cognitive decline among HD patients in the southwestern China, which provided longitudinal study‐based support in addition to sarcopenia base status and cognitive impairment. Second, our participants were a reliable group of patients undergoing HD coming from the real world, who had electronic health records from long‐run medical centres. Our interview took place in these medical centres, which guaranteed reliability and were more representative of the real world. Thirdly, our study observed robust findings concerning associations of sarcopenia change, its defining components with multiple outcomes, including cognitive decline, incident cognitive impairment, and dementia. These findings were preserved even after controlling for a considerable number of factors.
However, there are several limitations to this study. First, 1 year follow‐up duration limits a long‐term causal relationship. Second, even considering sarcopenia status changes, the casual relationship could not be confirmed in an observational design. Third, the population of our study subjects was from a southwestern province of China that may limit generalizability to other areas.
Conclusions
In summary, our results revealed that persistent sarcopenia and new‐onset sarcopenia in the short term were associated with a higher risk of cognitive decline, incident cognitive impairment, and dementia. Proper attention should be paid to addressing sarcopenia status of HD patients in clinical practice for the improvement of cognitive function. Future clinical trials targeted the association between change in sarcopenia and cognitive impairment in HD patients are still essential.
Conflict of interest
The authors have no conflicts of interest to declare.
Funding
The work was supported by the Guizhou Provincial Health Commission Project under Grant gzwjkj2018‐1‐015 and Guizhou High‐Level Innovative Talents Program under Grant QKHPTRC(2018)5636.
Acknowledgements
The study is based on data provided by 17 dialysis centres. All members of the 17 dialysis centres are appreciated.
Yang Y, Da J, Yuan J, Zha Y (2023) One‐year change in sarcopenia was associated with cognitive impairment among haemodialysis patients, Journal of Cachexia, Sarcopenia and Muscle, 14, 2264–2274, 10.1002/jcsm.13311
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