Prevalence and risk factors of malnutrition among patients receiving hemodialysis in a tertiary level hospital in Mauritius

Abstract

Objective

In this study, we aimed to determine the prevalence of malnutrition and its associated risk factors among patients undergoing hemodialysis in a tertiary hospital in Mauritius.

Methods

We enrolled 250 participants in this cross-sectional single-center study. A modified Malnutrition–Inflammation Score (MIS) questionnaire was used. We collected and analyzed data pertaining to patients’ medical and hemodialysis details.

Results

Among the 250 enrolled participants, 136 (54.4%) were male patients. Participants had been undergoing hemodialysis for a mean duration of 5.67 ± 4.66 years. Malnutrition was present in 108 (43.2%) participants, and 176 patients (70.4%) had diabetes mellitus, which was found to be a significant predictor of malnutrition. There was a significant correlation between malnutrition and the number of years a participant had been under hemodialysis, as well as female sex. A significant variation in MIS values was found among different age groups. Participants with malnutrition had lower body mass index and hyponatremia.

Conclusions

Malnutrition is an important issue, particularly among women, patients who have been on hemodialysis for an extended period, those with older age, and patients with diabetes mellitus.

Keywords

Diabetes mellitus hemodialysis malnutrition risk factor Mauritius dialysis duration

Introduction

Mauritius is ranked second in terms of both mortality owing to chronic kidney disease (CKD) and CKD prevalence, according to the 2017 Global Burden of Disease.¹ CKD is the second cause of death and disability in Mauritius. According to the 2022 Health Statistics report published by the Ministry of Health and Wellness, 1476 patients underwent hemodialysis in regional hospitals of the country during that year² (Figure 1).

Figure 1.

Total number of patients on hemodialysis during 2019–2022.

Malnutrition is a condition characterized by either inadequate or excessive nutrient intake, an imbalance of essential nutrients, or impaired nutrient absorption and utilization. Malnutrition can result from various factors, including medication use, chronic illness, age, and the lack of systematic nutritional screening strategies. Malnutrition is a common issue among individuals with renal failure and is a significant mortality risk factor for patients with CKD, particularly those undergoing hemodialysis.³ A number of studies have identified malnutrition in approximately 20% to 60% of patients receiving hemodialysis.⁴ To the best of our knowledge, no studies on this patient group have been conducted in Mauritius to date.

The causes of malnutrition in patients undergoing hemodialysis are multifactorial and include the number of years on dialysis, dialysis-related side effects, functional capacity, chronic inflammation, advanced age, inadequate dietary intake owing to diminished appetite and gastrointestinal symptoms, comorbidities like diabetes mellitus, and socioeconomic status.^5,6 The purpose of this study was to investigate the prevalence and severity of malnutrition among patients undergoing hemodialysis in a tertiary center of Mauritius using the Malnutrition–Inflammation Score (MIS). Additionally, we examined the correlation between malnutrition and risk factors such as diabetes mellitus, age, sex, and the duration of hemodialysis treatment.

Methods

The was a single-center cross-sectional study conducted from February 2023 to October 2023 at Dr AG Jeetoo Hospital, a tertiary care center.

Patients were randomly selected. Our study sample represented approximately 17% of the total number of Mauritian patients on dialysis during the study period. The minimum required sample size (n = 245) was determined using the following formula:⁷

Z_{1 - a / 2}^{2} P (1 - P) / d^{2}

where:

Z_1−a/2² is the standard normal variate at p < 0.05, or 1.96; P is the proportion of patients on dialysis with malnutrition, which was taken to be 20% in this case; and d is the absolute error, which was 0.05 in this study.

The reporting of this study adheres to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.⁸

Eligibility criteria

The inclusion criteria comprised participants aged 18 years and older who provided their written informed consent. We only recruited Mauritian participants of either sex and any race and ethnicity as well as social background.

Participants who did not give their consent to participate, those under 18 years of age, and those who were unable to stand were excluded from our study. Additionally, participants with missing data and those with other chronic conditions such as heart failure or malignancies, which could be confounding factors, were excluded. A 2016 study conducted in Korea found that being malnourished for 12 months after dialysis initiation was a significant risk factor for mortality.⁹ To reduce variability owing to the period of adaptation to the nutritional regimen established by a nutritionist, participants undergoing hemodialysis for less than 1 year were also excluded.

Research method

General characteristics such as age, weight, height, and sex were analyzed. The duration of hemodialysis in years was also assessed. Participant comorbidities were queried, in particular, the prevalence of diabetes mellitus and anemia. We calculated body mass index (BMI) for all participants.

In this study, we used a modified, interview-based MIS questionnaire from the American Journal of Kidney Disease. The MIS questionnaire comprises 10 components, categorized into four divisions: the patient’s medical history, physical examination findings, BMI, and laboratory parameters. Each component is scored on a scale from 0 to 3, with higher scores indicating greater severity. The total score ranges from 0 to 30, with higher scores reflecting more severe malnutrition. The MIS was significantly associated with future hospitalization and mortality, as well as nutritional and inflammation indicators.

Assessment of subcutaneous fat loss (observed in the under-eye, triceps, and biceps regions) and muscle wasting (observed in the shoulder, temple, quadriceps, and interosseous muscle between the thumb and index finger) was conducted post-dialysis. These findings were subsequently used in the questionnaire. Biochemical data including serum potassium and sodium were determined using conventional auto analyzers.

In our study, an MIS of ≥7 was established as the threshold for diagnosing malnutrition. This threshold was chosen based on previous similar studies, which demonstrated that a score above 7 could predict mortality using sensitivity and specificity analysis and receiver operating characteristic curves.^10–12

Ethical approval

The National Ethics Committee of the Ministry of Health and Wellness granted approval for the study on 9 February 2023 (approval number MHC/CT/NETH/2022 A V6). The present research adhered to the principles of the Declaration of Helsinki of 1975, as revised in 2013. Written informed consent was obtained from all patients prior to participation. Throughout the data collection and analysis, participants’ confidentiality was strictly maintained. All participant information was de-identified and participants had the freedom to withdraw from the study at any time.

Statistical analysis

Table 1 summarizes the variables we used in our study. For quantitative variables, the mean and standard deviation, median, minimum and maximum value were determined. For qualitative variables, we calculated the frequency and percentage.

Table 1.

Summary of variables.

Quantitative variables	Qualitative variables
MIS	Malnutrition status
Age	Sex
Duration of MHD treatment in years	Diabetes
Body mass index	Anemia
Serum potassium level
Serum sodium level

MIS, Malnutrition–Inflammation Score; MHD, maintenance hemodialysis.

In inferential analysis, non-parametric tests were applied. The chi-squared test was used to assess the relationship between malnutrition status and dichotomous variables. Spearman’s correlation was used to measure the correlation between MIS and quantitative variables. The Mann–Whitney U test was used to assess the correlation between MIS and dichotomous variables. Finally, the one-sample Wilcoxon signed-rank test was used to determine whether the median of the biochemical data differed significantly from the reference medians.

IBM SPSS software, version 27 (IBM Corp., Armonk, NY, USA), was used for the analysis. Results were considered statistically significant with a p-value <0.05.

Results

We included 250 participants in the study. The participant enrollment process is detailed in Figure 2, and general characteristics of the study population are detailed in Table 2.

Table 2.

General characteristics of participants.

Characteristics	All participants(n = 250)	Normal nutritional status(n = 142)	Malnourished(n = 108)	p value
Hemodialysis duration (years)	5.67 ± 4.66 years	3.56 ± 3.53	8.45 ± 4.52	<0.001
Demographics
Age (years)	56.0 ± 13.4 years	55.05 ± 12.68	57.30 ± 14.31	0.039
Sex
Male	136 (54.4 %)	86 (63.2 %)	50 (36.8 %)	0.017
Female	114 (45.6 %)	56 (49.1 %)	58 (50.9 %)	0.017
Anthropometrics
BMI (kg/m²)	20.45 ± 3.86	21.50 ± 3.68	19.06 ± 3.66	0.02
Medical history
Anemia
Yes	190 (76.0 %)	103 (54.2 %)	87 (45.8 %)	0.425
No	60 (24.0 %)	39 (65.0 %)	21 (35.0 %)	0.425
Diabetes				0.01
Yes	176 (70.4 %)	87 (49.4 %)	89 (50.6 %)
No	74 (29.6 %)	55 (74.3 %)	19 (25.7 %)

BMI, body mass index.

Figure 2.

Participant enrollment process.

Among the total, 136 (54.4%) participants were male patients. On average, participants had been undergoing hemodialysis treatment for 5.67 ± 4.66 years. After adding up the scores for the 10 components, the MIS value was obtained for each participant, with higher scores indicating a more severe level of malnutrition and inflammation.¹³ The mean MIS was 6.32 ± 2.84 and ranged from 2 to 17, with 108 participants (43.2%) meeting this criterion. A significant association was found between the number of years each participant had been undergoing hemodialysis and malnutrition severity (p < 0.005). Female sex was positively correlated with malnutrition (p = 0.017, odds ratio [OR] 0.561). A significant variation in the MIS was found among various age categories (p = 0.01), with a noticeable trend observed of an increasing median MIS with advanced age.

Table 2 presents a comprehensive comparison of participants undergoing hemodialysis, categorized into those with normal nutritional status (n = 142) and those who are malnourished (n = 108). The p values highlight the statistical relevance of the observed differences between these groups.

Comorbidity and the MIS

We found that 176 participants (70.4%) had diabetes, which was a significant predictor of malnutrition (p = 0.01, OR 0.388). The mean BMI was 20.45 ± 3.86 kg/m² and ranged from 15.25 kg/m² to 35.04 kg/m². The Spearman correlation test was conducted, showing a negative relationship between MIS and BMI (p = 0.02).

Logistic regression analysis indicated that both diabetes status and BMI were significant predictors of malnutrition risk. Specifically, diabetes was a significant predictor with an odds ratio (Exp(B)) of 3.24 (p < 0.05, 95% CI: 1.60–5.78), suggesting that individuals with diabetes are 3.24 times more likely to be at risk of malnutrition compared with individuals who do not have diabetes. Additionally, BMI was a significant predictor with an odds ratio (Exp(B)) of 1.21 (p < 0.05, 95% CI: 1.12–1.32), indicating that for each unit increase in BMI, the likelihood of malnutrition risk increases by approximately 1.21 times.

Biochemical profile and the MIS

Table 3 summarizes the mean and median values for serum sodium and potassium levels. The one-sample Wilcoxon signed-rank test, a non-parametric statistical test, was used to determine whether the median of our sample differed significantly from the reference median (140.00 mmol/L for sodium and 4.40 mmol/L for potassium). Compared with the reference medians, the average sodium level of participants was lower, and the median serum potassium level was higher. Serum sodium level was positively correlated with the MIS (p < 0.005). However, there was no statistically significant correlation between the MIS and serum potassium levels.

Table 3.

Biochemical data.

Variable	Mean	Observed median	Comparison to reference value	p value
Serum sodium (mmol/L)	135.43 ± 4.19	135.00	Lower	<0.001
Serum potassium (mmol/L)	5.12 ± 0.64	5.30	Higher	<0.001

Discussion

Malnutrition is one of the most well-established predictors of mortality and morbidity in patients undergoing hemodialysis.¹⁴ The nutritional status of participants is often overlooked in hemodialysis centers worldwide, even though straightforward methods of nutritional evaluation could considerably enhance patient care, as stated in the Kidney Disease: Improving Global Outcomes guidelines.^13,15

Our study found a malnutrition prevalence of 43.2%, closely mirroring the 45.4% reported in a Palestinian hospital study, potentially owing to similar dietary habits between the Palestinian and Mauritian populations.¹⁴ This prevalence was marginally lower than the 56.2% and 67% reported in Jordan and rural Egypt, respectively, possibly owing to Mauritius having better health care facilities, with patients receiving more frequent dialysis sessions per week.^16,17 It should be noted that in Mauritius, all patients are given free dialysis as well as free transport to a facility to attend their dialysis sessions, which greatly improves adherence to treatment. However, the prevalence in our study surpassed the 38% reported in a Brazilian hospital and the 22.4% in a Saudi Arabian study. This may be attributed to the lower mean age and higher BMI in those studies.^18,19

Mauritius has a high prevalence of diabetes mellitus, which is a leading cause of end-stage renal disease.^20,21 In this study, we found that 70.4% of participants undergoing hemodialysis had diabetes. Furthermore, we noted a greater susceptibility to being malnourished among participants with diabetes. This observation aligns with the findings of a 2018 Iraqi study.²² The underlying cause can be traced back to an acidic environment, which impairs the ability of insulin to bind to receptors, a condition that is prevalent among patients with diabetes.²³ Interestingly, we did not find a correlation between anemia and malnutrition. A plausible explanation for this could be that participants undergoing hemodialysis in Mauritius receive regular injections of erythropoietin-stimulating agents. This treatment could potentially confound the results or even have a protective effect; erythropoietin contributes to the maintenance, repair, and growth of skeletal muscles and protects against inflammatory responses that lead to fat degradation.²⁴

Our study identified a higher incidence of malnutrition among female participants, with 50.9% affected, consistent with studies in Iran and China.^25,26 This higher prevalence among female patients could potentially be attributed to their lower average BMI, which is a risk factor for malnutrition.

Our research demonstrated a direct relationship between age and malnutrition, with a higher incidence noted in older patients, in line with the findings of a study in Romania.²⁷ The rationale for this correlation could be that older individuals often face greater challenges with eating, have lower body fat, experience increased muscle protein catabolism, and exhibit reduced daily activity levels.¹⁶ This could be because malnutrition is largely dependent on diet, and most participants stated that their diet was largely based on a nutritional plan provided by a hospital nutritionist. However, in clinical practice, many patients have difficulty adjusting to the recommended dietary restrictions or are not given clear information regarding their diet.

Our study identified a statistically significant correlation between the MIS and hyponatremia. This may be attributed to the hypothesis that whereas malnutrition can precipitate hyponatremia, hyponatremia alone can contribute to the loss of adiposity and onset of sarcopenia.²⁸ This highlights the complex interplay between nutritional status and electrolyte balance in patient health.²⁴

Chronic hemodialysis accentuates proteolysis as a result of chronic inflammation as well as a loss of nutrients.²⁹ The longer a patient is on hemodialysis, the greater the risk of malnutrition. This is supported by the significant association found in our study between the number of years participants had been undergoing hemodialysis and malnutrition severity (p < 0.005).

Limitations in this study

Our study has several limitations. Given the cross-sectional design of our study, it was not possible to establish any causal relationships. Additionally, we only included patients from Dr. AG Jeetoo Hospital, which covers a specific geographical area. Consequently, the prevalence observed in our sample may not be representative of that in other hospitals or catchment areas. Additionally, pain experienced by some participants during physical examinations hindered our ability to assess muscle wasting and fat storage using the MIS. Furthermore, the use of self-reporting methods increases the risk of respondent error. These limitations should be considered when interpreting our results.

Conclusion

Screening the nutritional status of patients undergoing hemodialysis is a critical issue that requires the concerted efforts of a multidisciplinary team of health professionals in hemodialysis centers. Our findings revealed that a significant proportion of patients was malnourished, highlighting a major health concern. Several factors were identified as being associated with an increased risk of malnutrition, including female sex, advanced age, and the duration of hemodialysis treatment. Additionally, patients with diabetes were found to have a heightened risk of malnutrition. Our study also demonstrated a direct correlation between hyponatremia and the MIS. These results underscore the complex and multifactorial nature of malnutrition in patients undergoing hemodialysis. Our findings emphasize the need for personalized nutritional management strategies and highlight the importance of comprehensive nutritional assessment and intervention to improve the overall health outcomes of this patient population.

Supplemental Material

sj-pdf-1-imr-10.1177_03000605241300008 - Supplemental material for Prevalence and risk factors of malnutrition among patients receiving hemodialysis in a tertiary level hospital in Mauritius

Supplemental material, sj-pdf-1-imr-10.1177_03000605241300008 for Prevalence and risk factors of malnutrition among patients receiving hemodialysis in a tertiary level hospital in Mauritius by Kevin Fagoonee, Ganessen Chinien and Neelesh Munnohur in Journal of International Medical Research

Supplemental Material

sj-pdf-2-imr-10.1177_03000605241300008 - Supplemental material for Prevalence and risk factors of malnutrition among patients receiving hemodialysis in a tertiary level hospital in Mauritius

Supplemental material, sj-pdf-2-imr-10.1177_03000605241300008 for Prevalence and risk factors of malnutrition among patients receiving hemodialysis in a tertiary level hospital in Mauritius by Kevin Fagoonee, Ganessen Chinien and Neelesh Munnohur in Journal of International Medical Research

Supplemental Material

sj-pdf-3-imr-10.1177_03000605241300008 - Supplemental material for Prevalence and risk factors of malnutrition among patients receiving hemodialysis in a tertiary level hospital in Mauritius

Supplemental material, sj-pdf-3-imr-10.1177_03000605241300008 for Prevalence and risk factors of malnutrition among patients receiving hemodialysis in a tertiary level hospital in Mauritius by Kevin Fagoonee, Ganessen Chinien and Neelesh Munnohur in Journal of International Medical Research

Footnotes

Author contributions

KF: Conceptualization, methodology, project administration, supervision, validation, visualization, writing – original draft

GC: Conceptualization, methodology, project administration, supervision, validation, writing – review and editing,

NM: Conceptualization, data curation, formal analysis, investigation, visualization

Data availability statement

All published data will be made available on request.

Declaration of conflicting interest

The authors declare that there is no conflict of interest.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

ORCID iD

Kevin Fagoonee

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Supplementary Material

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