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Eur J Clin Nutr
Eur J Clin Nutr
European Journal of Clinical Nutrition
0954-3007
1476-5640
Nature Publishing Group UK London

38866974
1458
10.1038/s41430-024-01458-0
Case Report
Malnutrition, protein energy wasting and sarcopenia in patients attending a haemodialysis centre in sub-Saharan Africa
Crystal Findlay 1
Fulai Robert 2
Kaonga Patrick 34
http://orcid.org/0000-0002-4467-6833
Davenport Andrew a.davenport@ucl.ac.uk

5
1 https://ror.org/02jx3x895 grid.83440.3b 0000 0001 2190 1201 UCL Division of Medicine, University College London, London, UK
2 Department of Internal Medicine, University Teaching Adult Hospital, Lusaka, Zambia
3 https://ror.org/03gh19d69 grid.12984.36 0000 0000 8914 5257 Department of Epidemiology and Biostatistics, School of Public Health, University of Zambia, Lusaka, Zambia
4 https://ror.org/00za53h95 grid.21107.35 0000 0001 2171 9311 Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD USA
5 grid.83440.3b 0000000121901201 UCL Centre for Kidney & Bladder Health, Royal Free Hospital, University College London, London, UK
12 6 2024
12 6 2024
2024
78 9 818822
19 12 2023
25 5 2024
31 5 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Background

Haemodialysis (HD) patients are reported to be at greater risk of malnourishment, and at risk of increased morbidity and mortality. However, most studies report from economically advanced countries. We therefore assessed the nutritional status and diet among HD patients attending a public university hospital in a sub-Saharan African country.

Subjects

We performed nutritional assessments in HD patients attending the largest dialysis centre, in the country, collecting demographic and clinical data, dietary intake, along with anthropometric and bioimpedance body composition measurements in May 2022. Malnutrition was classified according to subjective global assessment score (SGA). Additional assessments of protein energy wasting (PEW), clinical frailty, and sarcopenia were made.

Results

All 97 HD patients were recruited, mean age 44.7 ± 12.2 years, with 55 (56.7%) males. Malnutrition was present in 43.8%, PEW 20.6%, frailty 17.6% and sarcopenia 4.1%. On multivariable logistic regression higher serum albumin (adjusted odds ratio (AOR) 0.89, 95% confidence intervals (CI) 0.85-0.95, p < 0.001), creatinine (AOR 0.99, 95%CI 0.98–0.99, p < 0.001), greater mid upper arm circumference (AOR 0.89, 95%CI 0.83–0.95, p = 0.001), body cell mass (BCM) (AOR 0.79, 95%CI 0.67–0.95, p = 0.013) and employment (AOR 0.45, 95%CI 0.23–0.87, p = 0.017), were are all protective against malnourishment. Almost 75% had reduced dietary protein intake.

Conclusions

Despite a younger, less co-morbid patient population, malnutrition is common in this resource poor setting. The staple diet is based on maize, a low protein foodstuff. Employment improved finances and potentially allows better nutrition. Further studies are required to determine whether additional dietary protein can reduce the prevalence of malnutrition in this population.

Subject terms

Acid, base, fluid, electrolyte disorders
Nutrition
Skeletal muscle
issue-copyright-statement© Springer Nature Limited 2024
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pmcIntroduction

Chronic kidney disease (CKD) is now one of the most important non-communicable diseases world-wide. Prior to starting dialysis patients may be treated with low protein diets, and even after starting dialysis patients have restricted diets designed to limit sodium, potassium and phosphate intake [1, 2]. As such dialysis patients are at increased risk of malnutrition [3].

In economically developed countries the number of patients treated by dialysis, particularly haemodialysis (HD), continues to increase annually, with the greatest exponential increase being the number of the elderly patients starting dialysis. Muscle mass naturally declines with age, but a greater loss of muscle mass than that expected for age, termed sarcopenia, is associated with increased risk of mortality both in geriatric and HD populations [4, 5]. The European Working Group for Sarcopenia in Older People (EWGSOP) and Foundations for the National Institute of Health (FNIH) have developed criteria for the assessment of sarcopenia based on non-invasive measurements of muscle mass using various techniques including anthropometry, bioimpedance, dual-energy x-ray absorptiometry, and functional assessments of muscle strength or performance [6]. World-wide, the subjective global assessment (SGA) is the tool most used by dietitians to assess the nutritional status of dialysis patients [7]. The combination of malnutrition and muscle wasting is often termed protein energy wasting (PEW) [5].

As dialysis is now offered to more older patients with advanced CKD, and those with additional co-morbidities in economically advanced countries, then more patients with degrees of frailty are now receiving dialysis [8]. Frail patients tend to be less physically active and have lower muscle mass [9, 10] and are greater risk of both sarcopenia and PEW [10]. In clinical practice frailty can be easily assessed using the 9-point Clinical Frailty Scale (CFS) [11], and frail HD patients have been reported to be at increased risk of both hospitalisation and mortality [12].

The prevalence of sarcopenia reported in dialysis patients varies between studies [11–15], but these studies have predominantly reported patients dialysing in Western Europe and North America, whereas there are very few reports from dialysis centres in developing countries [15]. As such we wished to investigate the prevalence of malnutrition, sarcopenia, and frailty in patients dialysing in a centre in sub-Saharan Africa.

Methods

Patients

A nutritional assessment of adult patients attending for HD at a university hospital in sub-Saharan Africa was undertaken during May 2022. All patients dialysed for 4 h thrice weekly, and only those established on HD for more than 3 months were included in the study.

Methods

Post-dialysis weight (kg)/height (m)2 was used to calculate body mass index (BMI). Weight was measured with a calibrated scale, and height using a stadiometer. Anthropometric measurements were obtained by the hospital nutritionist, dialysis nurse, or principal investigator. The mid-upper arm circumference (MUAC) was measured to the closest 0.1 cm in the non-fistula arm with the patient standing and arms hanging down [16]. Hand grip strength (HGS) was measured with a Takei digital dynamometer (Takei Scientific Instruments, Shinagawa-Ku, Tokyo) using a standardised protocol [17]. Normal blood pressure was considered when systolic was less than 120 mmHg and diastolic less than 80 mmHg. The majority of blood tests were measured at a private diagnostic laboratory. Dialysis adequacy was calculated using the Daugirdas equation and normalised protein nitrogen accumulation (nPNA) using: nPNA = 0.22 + (0.036 * intradialytic rise in BUN * 24)/(intradialytic interval) [18]. Malnutrition was assessed using the 7-point SGA; with values of 6–7 = very mild risk/normal nutritional status, 3–5 = mild/moderate malnutrition and 1–2 = severe malnutrition [19]. In addition, body composition was measured using the Body Composition Monitor (Fresenius AG, Bad Homberg, Germany), with measurements made 20 min after dialysis with electrodes placed on the non-fistula arm and leg [20, 21]. Demographics, and relevant co-morbidity were obtained from the hospital health care records, and patients assessed for clinical frailty using the clinical frailty score (CFS) [11].

Ethics

This observational, cross-sectional study was approved by the local university ethics committee. All patients provided written informed consent in keeping with the principles of Helsinki. Patients were told they were free to withdraw from the study or skip any questions without any consequences. Out of the 97 participants we approached, everyone agreed to take part in the study.

Statistical analysis

Data was checked for normality using the Shapiro-Wilk test, and expressed as mean and standard deviation, or median and interquartile range as appropriate. The Chi square (X2) test was used for analysis of categorical data. Bonferroni post hoc adjustments were made as appropriate. Cohen’s kappa statistic was used to compare the different scoring tools for assessing malnourishment, frailty, and sarcopenia. As only 2 patients had SGA scores of 2 or less, we combined severely and moderately malnourished patients to develop a multivariable binary logistic regression model to determine factors associated with malnutrition. Variables with a univariate p < 0.05 were included into a step backward regression model, which was checked for collinearity and variance inflation factor (VIF). All analyses were made using SPSS version 24 (IBM SPSS Corp., Armonk, New York, USA). Statistical significance was taken with a p < 0.05.

Results

We assessed the nutrition status of all 97 eligible patients 44.7 ± 12.2 years, 55 (56.7%) male. The majority (81.4%) were from within the capital city; 63.8% were married, 59.6% unemployed, 50.5% tertiary education, 75% had hypertension and 37.6% were human immunodeficiency virus (HIV) positive. Approximately three-quarters (74.1%) of participants had inadequate protein intake (nPNA <0.8 g/kg/day).

Thirty-nine patients (43.8%) were malnourished using the SGA assessment and they had significantly lower MUAC, HGS, body cell mass (BCM), lean tissue index (LTI), serum albumin, and creatinine compared (Table 1). Malnourished patients were shorter, but this difference did not remain statistically different after Bonferroni adjustment.Table 1 Baseline and clinical characteristics of study participants.

Characteristic	Not malnourished	Malnourished	P value	
number	50	39		
Age in years, mean (SD)	44.7 (11.8)	43.5 (13.1)	0.635	
Sex (n, %)	
 Male	33 (66.0)	18 (46.2)	0.060	
 Female	17 (34.0)	21 (53.8)	
Residence (n, %)	
 Lusaka	40 (80.0)	33 (84.6)	0.574	
 Outside Lusaka	10 (20.0)	6 (15.4)	
Marital status (n, %)	
 Married	30 (62.5)	25 (64.1)	0.877	
 Not married	18 (37.5)	14 (35.9)	
Employment status (n, %)	
 Employed	25 (50.0)	10 (27.0)	0.031	
 Not employed	25 (50.0)	27 (73.0)	
Education level (n, %)	
 No education/primary	18 (20.2)	9 (23.1)	0.509	
 Secondary	13 (26.0)	13 (33.3)	
 Tertiary	28 (56.0)	17 (43.6)	
Blood Pressure (n, %)	
 Normal	8 (18.2)	11 (30.6)	0.196	
 High	36 (81.8)	25 (69.4)	
HIV status (n, %)	
 Negative	32 (68.1)	25 (61.5)	0.526	
 Positive	15 (31.9)	15 (38.5)	
Protein Intake (nPNA)	
 Adequate	11 (22.0)	11 (29.7)	0.477	
 Inadequate	37 (77.1)	26 (70.3)	
Height (cm)	166.4 (9.0)	162.3 (8.3)	0.029	
BMI kg/m2	22.9 (20.7–24.7)	23.0 (20.1–25.0)	0.697	
MUAC post-dialysis	24.9 (23.0–26.8)	22.5 (19.6–25.0)	0.006	
Hand Grip strength kg	22.3 (19.9–30.0)	17.4 (12.3–21.9)	<0.001	
LTMI in kg/m2	12.1 (10.7–13.4)	10.6 (9.0–12.7)	0.036	
BCM kg/m2	18.0 (5.3)	15.4 (6.1)	0.031	
TBW in L	30.6 (27.3–35.4)	29.8 (23.9–31.9)	0.141	
Overhydration in L	2.0 (0.2–3.6)	2.3 (0.6–4.7)	0.179	
ECW/ICW	0.9 (0.8–1.1)	1.0 (0.9–1.2)	0.125	
ECW in L	15.4 (3.0)	14.9 (3.1)	0.471	
FTMI kg/m2	9.7 (7.0–13.9)	10.5 (7.7–15.0)	0.482	
Haemoglobin g/dL	8.9 (8.0–10.9)	8.4 (7.1–10.6)	0.295	
Albumin g/L	38.2 (4.0)	34.4 (5.4)	<0.001	
Total serum protein g/L	69.3 (8.9)	67.2 (8.9)	0.294	
Serum creatinine µmol/L	961.2 (752.9–1112.0)	809.1 (757.6–1097.2)	0.040	
Serum urea mmol/L	7.3 (5.9–9.0)	6.3 (4.6–10.5)	0.461	
Dialysis vintage months	34.0 (17.0–48.0)	21.0 (68.0–46.5)	0.050	
Kt/Vurea	1.18 (0.89–1.42)	1.37 (1.10–1.77)	0.054	
Normal nutritional assessment SGA ≥ 6, malnourished SGA ≤ 5, blood pressure, human immunodeficiency virus (HIV), body mass index (BMI), mid upper arm circumference (MUAC), lean tissue mass index (LTI), body cell mass (BCM), total body water (TBW) fat tissue mass index (FTI), normalised nitrogen protein accumulation (nPNA), dialysis adequacy (Kt/Vurea). Data expressed as mean ± SD or median (IQR). P values comparing those with normal nutritional assessment and those malnourished.

SD standard deviation, HIV human immunodeficiency virus, BMI body mass index, MUAC mid upper arm circumference, IQR interquartile range, LTI lean tissue index, BCM body composition monitoring, FTI fat tissue index, Kt/V represents the dose of haemodialyses, an abbreviation of (KureaTd)/Vurea. Kurea (mL/min).

Using the CFS [11], then 19 (19.6%) were classified as frail, and 20 (20.4%) had PEW according to the International Society for Renal Nutrition and Metabolism (ISRNM) criteria for PEW [15], and 4(4.1%) met the EWGSOP definition of sarcopenia (Fig. 1). All 97 patients were assessed for frailty and had HGS and bioimpedance measured to screen for frailty, MUAC measurements were made in 89 (92%) patients for the 7-point SGA, and relevant blood biochemistry tests were available for 82 (85%) patients as part of the screen for PEW.Fig. 1 Prevalence of malnutrition based on four nutritional screening tools.

Kappa analysis was used to assess the agreement among nutritional assessment tools used. The kappa statistic can take values from −1 to 1. The agreement between SGA and sarcopenia were 0.09 suggesting agreement equivalent to chance; SGA and frailty was 0.22 suggesting fair agreement; SGA and PEW were 0.15 which is considered as slight agreement: sarcopenia and frailty were 0.21; sarcopenia and PEW were -0.02, while frailty and PEW were 0.06 (Table 2).Table 2 Agreement among different malnutrition assessment tools: analysis by Cohen’s kappa statistic. Subjective global assessment (SGA), protein energy wasting (PEW).

Tool	SGA	Sarcopenia	Frailty	PEW	
SGA	1	0.09	0.22	0.15	
Sarcopenia	0.09	1	0.21	−0.02	
Frailty	0.22	0.21	1	0.06	
PEW	0.15	−0.02	0.06	1	

On multivariable logistic regression analysis, malnourishment was associated with a lower serum albumin, creatinine, body cell mass, and MUAC (Table 3). Patients who were in employment were 55% less likely to be malnourished (AOR = 0.45; 95% CI: 0.23–0.87). On average, one unit increase in creatinine was associated with a 1% decrease in the odds of being malnourished (AOR = 0.99; 95% CI: 0.98–0.99).Table 3 Factors associated with malnutrition.

Characteristic	AOR	95% CI	P value	
Employment status				
Unemployed	Ref.			
Employed	0.45	0.23–0.87	0.017	
albumin g/L	0.89	0.85–0.95	<0.001	
creatinine umol/L	0.99	0.98–0.99	<0.001	
MUAC cm	0.89	0.83–0.95	0.001	
LTMI kg/m2	1.11	0.98–1.25	0.092	
BCM kg	0.79	0.67–0.95	0.013	
Step backward multivariable logistic regression model, which was checked for collinearity and variance inflation factor. Adjusted odds ratio (AOR), 95% confidence intervals (95% CI), mid upper arm circumference (MUAC), lean tissue mass index (LTMI), body cell mass (BCM). Factors with an AOR of <1.0 are associated with no malnutrition.r2 = 0.23.

AOR adjusted odds ratio, CI confidence interval, LTMI lean tissue mass index, BCM body cell mass.

Discussion

Most studies reporting on nutritional assessments in dialysis patients come from economically developed countries [15]. We therefore report on adult patients dialysing at the largest tertiary hospital in the country and the only public hospital with a specialised renal unit in the country. Almost 75% of patients had reduced dietary protein intake, when compared to that advised by clinical guideline committees [3, 19]. The prevalence of malnutrition was 43.8% using the 7-point SGA assessment [19], and malnutrition was independently associated with lower serum albumin, creatinine, MUAC, BCM and unemployment. The prevalence of PEW and sarcopenia were lower, being 20.4% and 4.1%, respectively and 19.6% classified as frail using the CFS [11, 15, 22]. The 7-point SGA includes assessment of weight change, dietary intake, gastrointestinal symptoms, functional ability, co-existing co-morbidity, and physical examination. Whereas there was fair agreement between SGA and frailty, there was only slight agreement with PEW and no agreement with sarcopenia. As our patient cohort was younger and had fewer co-morbidities than those typically dialysing in economically advanced countries, this may have impacted on SGA scores. In addition, we used the cut-offs from European and North American clinical guidelines to screen for sarcopenia, and these may not be appropriate in a sub-Saharan African population, and may account for the poor association between SGA and sarcopenia.

Compared to other studies, the reported prevalence of malnutrition in our study was lower than that reported in other studies [15]. One study from Egypt reported a much higher prevalence of 85% [23], and one from Nigeria 55% [24]. The difference in prevalence between these studies published almost 10 years ago, could reflect differences in terms of access to dialysis, as patients may have to pay in full or part for dialysis treatments in developing countries, so having less than thrice weekly sessions and re-using low-flux dialyzers, along with differences in comorbidities, dialysis vintage, let alone dietary habits [25], whereas all the patients we report were in receipt of what would now be considered standard of care with thrice weekly 4-hour dialysis sessions.

Failure to achieve adequate clearance of uraemic toxins has been reported to increase the risk of PEW [26]. All our patients dialysed for 4 h thrice weekly, even so only 55% achieved a sessional KT/Vurea target of ≥1.4, and there was no associated between sessional Kt/Vurea and SGA scores, which supports a previous report from Iran which also reported no association between dialysis session urea clearance and nutritional status [27].

Serum albumin can be lowered by inflammation, PEW and so not just a marker of malnutrition, and the mean serum albumin was below the ISRNM advisory target level of 38 g/L in our patient cohort [28]. However, whether our patients were classified as malnourished by SGA criteria, or those with PEW, then all had a low serum albumin [15, 19]. Those classified as frail had a mean lower albumin than those who were not frail though the result was not significant [11]. The number of patients who were classified as sarcopenic was low (n = 4), therefore, due to this no further analysis was done.

Similarly, serum creatinine was lower in our patients who were malnourished, which is in keeping with reports from Turkey [29], demonstrating the association between lower serum creatinine in dialysis patients and reduced muscle mass and malnutrition. For both frailty and PEW, patients who were malnourished had lower values compared to those who were not malnourished. For frailty, the result was not statistically significant, but for PEW, there were significant differences.

However, another observational study from Iran found no association between serum creatinine and malnutrition [30]. Although this study did show a significant difference in the prevalence of malnutrition between male and female patients, with greater moderate malnutrition observed with male patients, which have biased the study results. Creatinine is generated from muscle creatine, so more physically active patients will generate more creatinine. In our study patients who were employed were less likely to be malnourished, and this is in keeping with other reports of physical activity linked to employment, and reduced prevalence of PEW, sarcopenia, and frailty [9]. Our malnourished patients had lower body cell mass and more importantly lower lean tissue when indexed for height, in keeping with less muscle mass. Similarly, the MUAC was lower in our malnourished patients, and as there was no difference in fat mass indexed for height, this would again suggest lower upper arm muscle mass in the malnourished patients.

Creatinine is also affected by diet, in particular dietary meat protein intake. We found that the median nPNA value was well below the 2020 Kidney Disease Outcomes Quality Initiative (KDOQI) Clinical Practice Guideline for Nutrition recommended dietary protein intake 1.0–1.2 g/kg/day [3], and almost three-quarters (74%) of the patients had low protein intake (nPNA < 0.8 g/kg/day) which could be affected by diet patterns. The primary staple food is a starch-based food (maize) and as most individuals, especially those from poorer households predominantly only eat maize with only very little meat, this could explain the lower nPNA reported in our study [31]. Although there was no significant difference in the dietary protein intake in those who were malnourished and not malnourished, this may have been confounded by all patients being given a meal when they attended for their dialysis session. As such most dietary restrictions and recommendations for dialysis patients developed for economically advanced countries [1, 3], may be inappropriate for patients living in sub-Saharan Africa. Therefore, it is important that dietary recommendations should be appropriate for the dialysis population, considering geopolitical, religious, and other factors, including ethnicity. Whereas in economically developed countries emphasis on protein and phosphate restriction may be appropriate [3, 4], in resource-limited settings in developing countries more attention is required to provide dietary advice to ensure adequate nutrition. Our unemployed patients were more likely to be malnourished, and economic factors, such as the lack of financial resource to purchase essential foods may have played a role in the development of malnutrition. In our study, a higher proportion of individuals who were unemployed had low nPNA, though when compared to those who were employed, the result was not statistically significant.

We have reported the first study to assess nutritional status and diet among CKD patients in the country. As with any observational study, there are a number of limitations to consider. Firstly this was a cross sectional study so we cannot comment on whether patients nutritional status changed over time. Secondly it was conducted at the only public run haemodialysis centre, and there are now private dialysis centres opening. Thirdly the staple diet is maize, and although maize is widely eaten in many African countries, other countries may have different dietary patterns. As with any observational study our findings should be interpreted with caution, as we can only report factors associated with malnourishment, but not apportion causality.

Conclusion

There are differences in the population demographics of haemodialysis patients in economically advanced and those from developing countries. Despite a much younger patient cohort, with fewer co-morbidities, we found that malnutrition is common among CKD patients at the largest renal unit in the country, and higher serum albumin, creatinine, MUAC, body cell mass, and being employed were all protective against malnutrition.

Acknowledgements

We wish to thank the patients and staff of the dialysis unit at the University Hospital of Lusaka.

Author contributions

CF obtained ethical approval, collected and analysed primary data, and wrote first draft. RF helped with local ethical approval and clinical resources. PK helped with local ethical approval and clinical resources. AD provided equipment, obtained UK approvals, and edited early drafts. All authors read and approved final version.

Data availability

Primary data is held on a UCL server and in a MSc thesis held by UCL Library and data may be available on reasonable request, with all data de-identified in keeping with UK NHS practices.

Competing interests

The authors declare no competing interests.

Ethical approval

Approved by the University Hospital, Lusaka ethics committee.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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References

1. Ashby D Borman N Burton J Corbett R Davenport A Farrington K Renal association clinical practice guideline on haemodialysis BMC Nephrol. 2019 20 379 10.1186/s12882-019-1527-3 31623578
Ashby D, Borman N, Burton J, Corbett R, Davenport A, Farrington K, et al. Renal association clinical practice guideline on haemodialysis. BMC Nephrol. 2019;20:379.31623578 10.1186/s12882-019-1527-3
2. Morey B Walker R Davenport A More dietetic time, better outcome? A randomized prospective study investigating the effect of more dietetic time on phosphate control in end-stage kidney failure haemodialysis patients Nephron Clin Pract. 2008 109 c173 80 10.1159/000145462 18663331
Morey B, Walker R, Davenport A. More dietetic time, better outcome? A randomized prospective study investigating the effect of more dietetic time on phosphate control in end-stage kidney failure haemodialysis patients. Nephron Clin Pract. 2008;109:c173–80.18663331 10.1159/000145462
3. Ikizler TA Burrowes JD Byham-Gray LD Campbell KL Carrero JJ Chan W KDOQI clinical practice guideline for nutrition in CKD: 2020 Update Am J Kidney Dis. 2020 76 S1 107 10.1053/j.ajkd.2020.05.006 32829751
Ikizler TA, Burrowes JD, Byham-Gray LD, Campbell KL, Carrero JJ, Chan W, et al. KDOQI clinical practice guideline for nutrition in CKD: 2020 Update. Am J Kidney Dis. 2020;76:S1–107.32829751 10.1053/j.ajkd.2020.05.006
4. Cruz-Jentoft AJ Sayer AA Sarcopenia Lancet 2019 393 2636 46 10.1016/S0140-6736(19)31138-9 31171417
Cruz-Jentoft AJ, Sayer AA. Sarcopenia. Lancet 2019;393:2636–46.31171417 10.1016/S0140-6736(19)31138-9
5. Hanna RM Ghobry L Wassef O Rhee CM Kalantar-Zadeh K A practical approach to nutrition, protein-energy wasting, sarcopenia, and cachexia in patients with chronic kidney disease Blood Purif. 2020 49 202 11 10.1159/000504240 31851983
Hanna RM, Ghobry L, Wassef O, Rhee CM, Kalantar-Zadeh K. A practical approach to nutrition, protein-energy wasting, sarcopenia, and cachexia in patients with chronic kidney disease. Blood Purif. 2020;49:202–11.31851983 10.1159/000504240
6. Slee A McKeaveney C Adamson G Davenport A Farrington K Fouque D Estimating the prevalence of muscle wasting, weakness, and sarcopenia in hemodialysis patients J Ren Nutr. 2020 30 313 21 10.1053/j.jrn.2019.09.004 31734056
Slee A, McKeaveney C, Adamson G, Davenport A, Farrington K, Fouque D, et al. Estimating the prevalence of muscle wasting, weakness, and sarcopenia in hemodialysis patients. J Ren Nutr. 2020;30:313–21.31734056 10.1053/j.jrn.2019.09.004
7. Avesani CM Sabatino A Guerra A Rodrigues J Carrero JJ Rossi GM A comparative analysis of nutritional assessment using global leadership initiative on malnutrition versus subjective global assessment and malnutrition inflammation score in maintenance hemodialysis patients J Ren Nutr. 2022 32 476 82 10.1053/j.jrn.2021.06.008 34330567
Avesani CM, Sabatino A, Guerra A, Rodrigues J, Carrero JJ, Rossi GM, et al. A comparative analysis of nutritional assessment using global leadership initiative on malnutrition versus subjective global assessment and malnutrition inflammation score in maintenance hemodialysis patients. J Ren Nutr. 2022;32:476–82.34330567 10.1053/j.jrn.2021.06.008
8. Davenport A Frailty, appendicular lean mass, osteoporosis and osteosarcopenia in peritoneal dialysis patients J Nephrol. 2022 35 2333 40 10.1007/s40620-022-01390-1 35816240
Davenport A. Frailty, appendicular lean mass, osteoporosis and osteosarcopenia in peritoneal dialysis patients. J Nephrol. 2022;35:2333–40.35816240 10.1007/s40620-022-01390-1
9. Hendra H Sridharan S Farrington K Davenport A Characteristics of frailty in haemodialysis patients Gerontol Geriatr Med. 2022 8 23337214221098889 10.1177/23337214221098889 35548325
Hendra H, Sridharan S, Farrington K, Davenport A. Characteristics of frailty in haemodialysis patients. Gerontol Geriatr Med. 2022;8:23337214221098889 10.1177/23337214221098889.35548325 10.1177/23337214221098889
10. Davenport A Comparison of frailty, sarcopenia and protein energy wasting in a contemporary peritoneal dialysis cohort Perit Dial Int. 2022 42 571 7 10.1177/08968608221077462 35289199
Davenport A. Comparison of frailty, sarcopenia and protein energy wasting in a contemporary peritoneal dialysis cohort. Perit Dial Int. 2022;42:571–7.35289199 10.1177/08968608221077462
11. Rockwood K Song X MacKnight C Bergman H Hogan DB McDowell I A global clinical measure of fitness and frailty in elderly people Can Med Assoc J 2005 173 489 95 10.1503/cmaj.050051 16129869
Rockwood K, Song X, MacKnight C, Bergman H, Hogan DB, McDowell I, et al. A global clinical measure of fitness and frailty in elderly people. Can Med Assoc J. 2005;173:489–95.16129869 10.1503/cmaj.050051
12. McAdams-DeMarco MA Law A Salter ML Boyarsky B Gimenez L Frailty as a novel predictor of mortality and hospitalization in individuals of all ages undergoing hemodialysis J Am Geriatr Soc. 2013 61 896 901 10.1111/jgs.12266 23711111
McAdams-DeMarco MA, Law A, Salter ML, Boyarsky B, Gimenez L, et al. Frailty as a novel predictor of mortality and hospitalization in individuals of all ages undergoing hemodialysis. J Am Geriatr Soc. 2013;61:896–901.23711111 10.1111/jgs.12266
13. Tangvoraphonkchai K Hung R Sadeghi-Alavijeh O Davenport A Differences in prevalence of muscle weakness (Sarcopenia) in haemodialysis patients determined by hand grip strength due to variation in guideline definitions of sarcopenia Nutr Clin Pract. 2018 33 255 60 10.1002/ncp.10003 29377324
Tangvoraphonkchai K, Hung R, Sadeghi-Alavijeh O, Davenport A. Differences in prevalence of muscle weakness (Sarcopenia) in haemodialysis patients determined by hand grip strength due to variation in guideline definitions of sarcopenia. Nutr Clin Pract. 2018;33:255–60.29377324 10.1002/ncp.10003
14. Abro A Delicata LA Vongsanim S Davenport A Differences in the prevalence of sarcopenia in peritoneal dialysis patients using hand grip strength and appendicular lean mass: depends upon guideline definitions Eur J Clin Nutr. 2018 72 993 9 10.1038/s41430-018-0238-3 29921962
Abro A, Delicata LA, Vongsanim S, Davenport A. Differences in the prevalence of sarcopenia in peritoneal dialysis patients using hand grip strength and appendicular lean mass: depends upon guideline definitions. Eur J Clin Nutr. 2018;72:993–9.29921962 10.1038/s41430-018-0238-3
15. Carrero JJ Thomas F Nagy K Arogundade F Avesani CM Chan M Global prevalence of protein-energy wasting in kidney disease: a meta-analysis of contemporary observational studies from the international society of renal nutrition and metabolism J Ren Nutr. 2018 28 380 92 10.1053/j.jrn.2018.08.006 30348259
Carrero JJ, Thomas F, Nagy K, Arogundade F, Avesani CM, Chan M, et al. Global prevalence of protein-energy wasting in kidney disease: a meta-analysis of contemporary observational studies from the international society of renal nutrition and metabolism. J Ren Nutr. 2018;28:380–92.30348259 10.1053/j.jrn.2018.08.006
16. Al-Joudi E Slee A Davenport A The effect of an arteriovenous fistula and haemodialysis on anthropometric measurements of the upper arm Eur J Clin Nutr. 2020 74 1240 2 10.1038/s41430-019-0548-0 31896824
Al-Joudi E, Slee A, Davenport A. The effect of an arteriovenous fistula and haemodialysis on anthropometric measurements of the upper arm. Eur J Clin Nutr. 2020;74:1240–2.31896824 10.1038/s41430-019-0548-0
17. https://www.uhs.nhs.uk/Media/Southampton-Clinical-Research/Procedures/BRCProcedures/Procedure-for-measuring-gripstrength-using-the-JAMAR-dynamometer.pdf assessed 24 Feb 2023.
18. Daugirdas JT Second generation logarithmic estimates of single-pool variable volume Kt/V: an analysis of error J Am Soc Nephrol. 1993 4 1205 13 10.1681/ASN.V451205 8305648
Daugirdas JT. Second generation logarithmic estimates of single-pool variable volume Kt/V: an analysis of error. J Am Soc Nephrol. 1993;4:1205–13.8305648 10.1681/ASN.V451205
19. Duerksen DR Laporte M Jeejeebhoy K Evaluation of nutrition status using the subjective global assessment: malnutrition, cachexia, and sarcopenia Nutr Clin Pract. 2021 36 942 56 10.1002/ncp.10613 33373482
Duerksen DR, Laporte M, Jeejeebhoy K. Evaluation of nutrition status using the subjective global assessment: malnutrition, cachexia, and sarcopenia. Nutr Clin Pract. 2021;36:942–56.33373482 10.1002/ncp.10613
20. Tangvoraphonkchai K Davenport A Do bioimpedance measurements of over-hydration accurately reflect post-haemodialysis weight changes? Nephron 2016 133 247 52 10.1159/000447702 27505163
Tangvoraphonkchai K, Davenport A. Do bioimpedance measurements of over-hydration accurately reflect post-haemodialysis weight changes? Nephron. 2016;133:247–52.27505163 10.1159/000447702
21. El-Kateb S Davenport A Changes in intracellular water following hemodialysis treatment lead to changes in estimates of lean tissue using bioimpedance spectroscopy Nutr Clin Pract. 2016 31 375 7 10.1177/0884533615621549 26684440
El-Kateb S, Davenport A. Changes in intracellular water following hemodialysis treatment lead to changes in estimates of lean tissue using bioimpedance spectroscopy. Nutr Clin Pract. 2016;31:375–7.26684440 10.1177/0884533615621549
22. Cruz-Jentoft AJ Bahat G Bauer J Boirie Y Bruyère O Cederholm T Writing Group for the European Working Group on Sarcopenia in Older People 2 (EWGSOP2), and the Extended Group for EWGSOP2. Sarcopenia: revised European consensus on definition and diagnosis Age Ageing. 2019 48 16 31 10.1093/ageing/afy169 30312372
Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyère O, Cederholm T, et al. Writing Group for the European Working Group on Sarcopenia in Older People 2 (EWGSOP2), and the Extended Group for EWGSOP2. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019;48:16–31.30312372 10.1093/ageing/afy169
23. Abozead SE Ahmed AM Mahmoud MA Nutritional status and malnutrition prevalence among maintenance hemodialysis patients IOSR-JNHS 2015 4 51 58
Abozead SE, Ahmed AM, Mahmoud MA. Nutritional status and malnutrition prevalence among maintenance hemodialysis patients. IOSR-JNHS. 2015;4:51–58.
24. Liman H Anteyi E Oviasu E Prevalence of malnutrition in chronic kidney disease: a study of patients in a tertiary Hospital in Nigeria Sahel Med J 2015 18 8 10.4103/1118-8561.149496
Liman H, Anteyi E, Oviasu E. Prevalence of malnutrition in chronic kidney disease: a study of patients in a tertiary Hospital in Nigeria. Sahel Med J. 2015;18:8 10.4103/1118-8561.149496.10.4103/1118-8561.149496
25. Tayyem RF Mrayyan MT Heath DD Bawadi HA Assessment of nutritional status among ESRD patients in Jordanian hospitals J Ren Nutr. 2008 18 281 7 10.1053/j.jrn.2007.12.001 18410884
Tayyem RF, Mrayyan MT, Heath DD, Bawadi HA. Assessment of nutritional status among ESRD patients in Jordanian hospitals. J Ren Nutr. 2008;18:281–7.18410884 10.1053/j.jrn.2007.12.001
26. Carrero JJ Stenvinkel P Cuppari L Ikizler TA Kalantar-Zadeh K Kaysen G Etiology of the protein-energy wasting syndrome in chronic kidney disease: a consensus statement from the International Society of Renal Nutrition and Metabolism (ISRNM) J Ren Nutr. 2013 23 77 90 10.1053/j.jrn.2013.01.001 23428357
Carrero JJ, Stenvinkel P, Cuppari L, Ikizler TA, Kalantar-Zadeh K, Kaysen G, et al. Etiology of the protein-energy wasting syndrome in chronic kidney disease: a consensus statement from the International Society of Renal Nutrition and Metabolism (ISRNM). J Ren Nutr. 2013;23:77–90.23428357 10.1053/j.jrn.2013.01.001
27. Afshar R Sanavi S Izadi-Khah A Assessment of nutritional status in patients undergoing maintenance hemodialysis: a single-center study from Iran Saudi J Kidney Dis Transpl. 2007 18 397 404 17679753
Afshar R, Sanavi S, Izadi-Khah A. Assessment of nutritional status in patients undergoing maintenance hemodialysis: a single-center study from Iran. Saudi J Kidney Dis Transpl. 2007;18:397–404.17679753
28. Fouque D Kalantar-Zadeh K Kopple J Cano N Chauveau P Cuppari L A proposed nomenclature and diagnostic criteria for protein-energy wasting in acute and chronic kidney disease Kidney Int. 2008 73 391 8 10.1038/sj.ki.5002585 18094682
Fouque D, Kalantar-Zadeh K, Kopple J, Cano N, Chauveau P, Cuppari L, et al. A proposed nomenclature and diagnostic criteria for protein-energy wasting in acute and chronic kidney disease. Kidney Int. 2008;73:391–8.18094682 10.1038/sj.ki.5002585
29. Yildiz A Tufan F Lower creatinine as a marker of malnutrition and lower muscle mass in hemodialysis patients Clin Inter Aging. 2015 10 1593 10.2147/CIA.S94731
Yildiz A, Tufan F. Lower creatinine as a marker of malnutrition and lower muscle mass in hemodialysis patients. Clin Inter Aging. 2015;10:1593.10.2147/CIA.S94731
30. Espahbodi F Khoddad T Esmaeili L Evaluation of malnutrition and its association with biochemical parameters in patients with end stage renal disease undergoing hemodialysis using subjective global assessment Nephrourol Mon 2014 6 e16385 10.5812/numonthly.16385 25032136
Espahbodi F, Khoddad T, Esmaeili L. Evaluation of malnutrition and its association with biochemical parameters in patients with end stage renal disease undergoing hemodialysis using subjective global assessment. Nephrourol Mon. 2014;6:e16385.25032136 10.5812/numonthly.16385
31. Harris J Advocacy coalitions and the transfer of nutrition policy to Zambia Health Policy Plan. 2019 34 207 15 10.1093/heapol/czz024 31006019
Harris J. Advocacy coalitions and the transfer of nutrition policy to Zambia. Health Policy Plan. 2019;34:207–15.31006019 10.1093/heapol/czz024
