1Institute of Food Science and Nutrition, University of Sargodha, Sargodha-Pakistan;
2Superior University, Lahore, Faisalabad Campus-Pakistan;
3Department of Food Science, Government College University Faisalabad, Pakistan;
4College of Food Science and Technology, Guangdong Provincial Key Laboratory of Aquatic Product Processing and Safety, Guangdong Ocean University, Zhanjiang, China;
5Department of Allied Health Science, University of Sargodha, Pakistan;
6Department of Food Science and Technology, Muhammad Nawaz Sharif University of Agriculture Multan, Pakistan;
7Punjab Food Authority, Lahore, Pakistan;
8National Institute of Food Science and Technology, University of Agriculture Faisalabad, Pakistan;
9Zoology Department, College of Science, King Saud University, Riyadh, Kingdom of Saudi Arabia;
10Punjab Food Authority, Faisalabad, Pakistan
Hemodialysis is a process in which the blood is resected using a dialysis apparatus and a specific strainer known as dialyzer. Poor nutritional status is common among hemodialysis patients, but only a few studies are found on how hemodialysis is affected by other factors in the local environment. The aim of this study was to find out hemo-dialysis patients’ nutritional status and the factors that influence it. A total of 100 hemodialysis individuals (50 patients and 50 volunteers) was enrolled in this study. Anthropometry and biochemical assays, as well as nutrition assessments, were used as additional evaluation methods. According to multiple linear regression analysis, malnutrition is linked to older age, poor and lean body mass, and higher body mass index. Factors, such as interdialytic weight gain, insufficient calorie and protein consumption, and existence of morbidities, are considered along with inflammation. This study was performed at various hospitals of Sargodha district in Pakistan. Various variables of hemodialysis patients’ poor nutritional status are changeable, and these must be considered when developing and implementing effective intervention programs for this vulnerable group. Nutritional health status of hemodialysis patients was evaluated using Food Frequency Questionnaire (FFQ), concerning multiple factors, such as demographics, anthropometrics, body composition, vital signs, clinical manifestations, dietary intake, edema on the feet, triceps skin fold thickness, mild arm circumference, hand grip strength, and micronutrients. FFQs showed the overall effect of hemodialysis. Further statistical calculations and studies were conducted using SPSS, Minitab 8.1 for descriptive analysis tests for demographic features, and analysis of variance ANOVA.
Key words: Hemodialysis, nutrition, chronic kidney disease, lifestyle
*Corresponding Author: Muhammad Yousaf Quddoos, Institute of Food Science and Nutrition, University of Sargodha, Sargodha-Pakistan. Email: [email protected]
Suliman Yousef Alomar, Zoology Department, College of Science, King Saud University, Riyadh, Kingdom of Saudi Arabia. Email: [email protected]
Received: 29 August 2023; Accepted: 27 November 2023: Published: 30 January 2024
© 2024 Codon Publications
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0). License (http://creativecommons.org/licenses/by-nc-sa/4.0/)
The kidneys, which are placed in the posterior wall of the body, perform a variety of functions in the body. Waste removal, chemical balance (such as electrolyte and acid–base equilibrium, and calcium–phosphate metabolism), and blood pressure (BP) regulator are the examples of such processes (Sahathevan et al., 2020). Filtration, absorption, and secretion are the three primary functions of the kidneys, which have an intricate architecture comprising several tissue layers, permeable membranes, and arteries. Blood flow via the kidneys and waste product elimination through urine are the fundamental mechanisms that allow the aforementioned activities to take place. The failure to generate urine is indicative of a kidney condition in which waste items cannot be removed and are instead reintroduced into blood circulation. By interfering with elements, such as electrolyte balance, the overlapping influence would be detrimental to homeostasis (Fiaccadori et al., 2021)
Hemodialysis process requires dialyzer, also known as dialysis machine, which acts as an artificial kidney to remove salts, fluids, and metabolic waste from the blood (Wardani et al., 2019). Hemodialysis is the process of removing harmful fluids from the body of patients with renal failure. It is a process in which blood is cleansed through a dialysis machine comprising a specialized filter, called an artificial kidney or a dialyzer (Lim et al., 2019). When kidney function drops below 10–15%, they lose their capacity to filter blood and generate urine. This condition is known as hyperuricemia. Purines are created by the breakdown of proteins, which lead to gout, renal failure, and various other illnesses. The consequence is the buildup of poisons and extra fluid in the body. Hemodialysis is a process that removes waste, eradicates excess body fluid, and reestablishes electrolyte balance (Na, K, HCO3-, Cl, Ca, Mg, and P) (Stevenson et al., 2018). Patients may develop anemia, pulmonary edema, and hyperkalemia because of uric acid accumulation, salt increase, and magnesium deficit, respectively. Proper diet of hemodialysis patients plays an important role in minimizing problems (Dai et al., 2017). This process is indicated to the patients having stage IV or V of chronic kidney disease (CKD). To avoid cardiovascular disease and electrolytic imbalance, the protein and calorie intake of such patients is lowered substantially, but intake of a suitable diet may limit the loss of various vital nutrients. Production of uric acid or oxalate crystals in the body promotes the onset of renal impairment (Rachida et al., 2020).
Various techniques, such as anthropometric measurements, subjective goal assessment (SGA), and other laboratory tests, are utilized to determine the nutritional position of malnutrition in CKD patients. Hemodialysis patients must undergo a dietary review on regular basis (Wolfson and Strong, 1996). Patients receiving dialysis treatment are more prone to malnutrition; consequently, they require a stringent compliance diet that is packed with nutrients. Numerous characteristics, such as protein- energy intake, catabolism, anorexia, and several dietary alterations, impact malnutrition in hemodialysis patients. There are two distinct types of dietary risks in hemodialysis patients (Agboton et al., 2017). The first is the uremic syndrome and the second is the sudden decline in serum albumin concentration. This happens due to precipitous decline in energy levels and protein catabolism (Žulič and Marentič, 2016).
To evaluate the nutritional status of hemodialytic patients and correlate the variables with their health status.
The research methodology was the procedure landscape of this study, which was performed to study different variables to achieve required objectives. This study was carried out according to the procedural parameters mentioned below:
Patients having end-stage CKD along with non-CKD volunteers were the target population (Moussa et al., 2016).
This was a cross-sectional study carried out at different hospitals of Sargodha district in Pakistan (Moussa et al., 2016).
Body composition machine (Model BF 105; Beurer Co., Germany), digital thermometer (Model FT 85; Beurer), sphygmomanometer (Model BM 51, Beurer), oximeter (Model PO 30, Beurer), and stadiometer (Stand HF-5664 Analog) were used for research work, and data were collected regarding clinical manifestations of patients, demographics, family and medical history, food frequency questionnaire (FFQ), and anthropometrics (Kramer et al., 2018).
The study locale, experts, target population, and researchers were available (Visiedo et al., 2022).
Males and nonpregnant females (with or without kidney infection) of any age were included, while pregnant females or patients with multiple diseases were excluded from the study (Quddoos et al., 2022).
The sample size for the study was calculated by using the following formula (Magnani, 1997):
Volunteers getting hemodialysis along with non-CKD persons of the same family were randomly selected from different hospitals of Sargodha district, Pakistan, by following the procedure mentioned by Mahmood and Butt (2011).
Demographic parameters, such as name, age, education, gender, physical activity, socioeconomic status, lifestyle, income, and ethnicity, were recorded through interviews (Žulič and Marentič, 2016). Height (cm) and weight (kg) were measured by a stadiometer. Body composition, that is, weight (kg), bone mass (%), body fat (%), muscle mass (%), body water (%), basal metabolic rate (BMR), and active metabolic rate (AMR), was measured by using bio-electrical impedance-based scale BF-105 (Beurer; Rizvi et al., 2020).
Blood pressure, oxygen saturation, pulse rate, and body temperature of volunteers were recorded (Gibson, 1990). Clinical manifestations of pulmonary tuberculosis (TB), such as chest pain, coughing up blood, loss of appetite, unexpected weight loss, etc., were investigated (Stevenson et al., 2018).
A complete medical history of patients, such as allergy, surgical procedures, and other associated diseases, was collected (Stevenson et al., 2018). Volunteers were asked about family medical history such as TB, diabetes, hyper-tension, asthma, and hepatitis (Gibson, 1990).
General biomarkers, such as hemoglobin (Hb), complete blood count (CBC), indicative biomarkers for functioning of the kidneys (uric acid test), and urine investigations, were performed (Campbell et al., 2018).
Dietary intake (number of servings) history of volunteers was conducted through Food Guide Pyramid-based FFQ (Kramer et al., 2018).
Data were analyzed statistically by using appropriate statistical tools. Correlations were analyzed using Chi-square and the Pearson’s coefficient, and t-test was used to compare the results; p = 0.05 was considered statistically significant (Steel et al., 1997)
The study aimed to examine the hemodialysis patients in terms of their nutritional status. This study was conducted at Mubarak Hospital of Sargodha district. He is the best nephrologist in Sargodha and has treated thousands of CKD patients. Of the sample of 100 patients, 50 were from the experimental group and the rest were from the control group. Because hemodialysis patients were not able to fill the questionnaire, their family members did the same. We had patients’ demographic status and rest of the questionnaire was about nutritional components.
Patients must be aged at least 18 years, routinely undergoing hemodialysis for 4 h thrice a week for at least 3 months before enrolling in the study, and be free of any acute illness or mental disorder. Before the collection of any data, consent was obtained from the dialysis institution/Hospital, the agreement of all dialysis institutions was obtained. Anonymity was ensured prior to having patients’ written informed consent. 100 out of the 50 eligible patients who were contacted agreed to take part in the experiment, with a response rate of 50 %. Sociodemographic data, medical history of any present illness, a subjective assessment of patient’s nutritional status based on their history and physical examination, an objective assessment based on anthropometric measurements (height, weight, etc.), and biochemical parameters were collected from the questionnaires (Visiedo et al., 2022).
The SGA included a range of subjects, including anorexia, nausea, vomiting, diarrhea, functional capacity, dialysis history, and loss of subcutaneous fat in the mid-arm muscular region, arm muscle area along the body’s lateral side, and shoulder and quadricep muscles. A score of 7 indicated sufficient nutrition whereas a score of 32 indicated severe malnutrition (El-dien et al., 2019). Malnutrition was found to be mild in patients aged 9–13 years, moderate in patients aged 14–26 years, and severe in those aged 26–40 years. The information was collected by a trained medical officer under the direct supervision of nephrology and clinical nutrition specialists. All patients who imparted written permission were presented with a questionnaire to measure malnutrition by an interviewer.
Ten questions were asked for nutritional assessment and the rest of the questionnaire contained body composition.
Medical nutrition assessment questions included the following:
Consumed calories during the last 3 months
Weight reduction within the previous 3 months
Mobility (bed-bound or chair-bound, capable of getting out of bed/chair
Acute illness or psychological strain in the preceding 3 months
Neuropsychiatric illnesses
Body mass index (BMI) (<19, 19–21, 21–<23, or >)
Loss of appetite or an increase in appetite
Change in physical appearance or body swelling
Increased purine degradation or catabolism
Water retention or edema due to infection
Six components of the 7-point SGA scale: change in weight, nutritional intake, gastrointestinal symptoms, functional ability, co-morbidities, and physical examination; 1–7 points were assigned to calculate the overall SGA score. Lower the overall SGA score, more severe the SGA and prevalence of malnutrition. Individual patients were used for baseline analysis. An SGA score of 5 showed “not malnourished” status, and an SGA score of 6–7 showed “well-nourished” status. Information provided by the patients was examined, and those who completed 12 months of follow-up were classified according to the following criteria:
Two categories according to their nutritional quality during a course of 1 year:
Remained or became well-nourished—those who remained well nourished during the complete year or who were well nourished at either the beginning or end of the year.
Remained malnourished, or acquired malnourishment.
Patients aged 18–85 years were included in the study. Patients must be conscious and attentive, were having hemodialysis for at least 6 months for a minimum of 3 h, at least twice a week (Stevenson et al., 2018). Patients with the following conditions were excluded from the study:
Lacked mental or physical ability to communicate with questioner
Having multiple syndromes
Patients who were unable to speak
Patients at the end stage of CKD
Device was utilized for collection of three type data: The first section covered socioeconomic and demographic characteristics (i.e., age, gender, domicile, work, dialysis center visited, education, smoking, marital status, and salary per month). The second section recorded clinical state of the patients (number of dialysis in a year, frequency of dialysis per week, BMI, regular medications used, and chronic illnesses) (Bogacka et al., 2018).
The clinical tests of hemodialysis patients were conducted and include all anthropometric analyses or SGA. These tests included body composition, body mass, pulse rate, BP, BMI, BMR, AMR, blood oxygen saturation, etc.
Table 1 shows high systolic BP of the patients undergoing hemodialysis. This could lead to acute conditions in patients, like brain hemorrhage, bleeding from the nose, etc.
Table 1. Analysis of variance for systolic BP.
Source | DF | Ad MS | F-value | p-value |
---|---|---|---|---|
BP | 24 | 4.544 | 1.05 | 0.449 |
Error | 25 | 4.317 | ||
Total | 49 |
DF: Degree of freedom
Ad MS: Adjusted Mean square
F-Value: Frequently Value (variance of the group)
P-Value: Probability value
Some studies suggested that a pre-dialysis BP must be less than 140/90 mmHg with a post-dialysis BP of 130/80 mmHg (Stern et al., 2014)
The significant change in systolic BP post-hemodialysis is observed in Table 2. It shows significantly less systolic BP, compared to pre-dialysis systolic BP.
Table 2. Analysis of variance for systolic II BP.
Source | DF | Ad SS | Ad MS | F-value | p-value |
---|---|---|---|---|---|
Systolic II | 4 | 216.3 | 54.07 | 1.68 | 0.172 |
Error | 45 | 1449.7 | 32.22 | ||
Total | 49 | 1666.0 |
DF: Degree of freedom
Ad MS: Adjusted Mean square
F-Value: Frequently Value (variance of the group)
P-Value: Probability value
Many dialysis patients were found to be hypertensive. Hypotension is the most common complication observed in dialysis patients and recorded in 15–50% of the cases. The other complications include muscle cramps, itching, fever, chills, pyrogen reactions, disequilibrium syndrome, nausea and vomiting, headache, and hypertension (Cases and Coll, 2002).
Significant values were discovered for diastolic BP taken before and after hemodialysis (Table 3). Diastolic BP was high in patient having dialysis.
Table 3. Analysis of variance for diastolic BP.
Source | DF | Ad SS | Ad MS | F-value | p-value |
---|---|---|---|---|---|
Diastolic I | 7 | 93.24 | 13.32 | 0.62 | 0.740 |
Error | 42 | 908.38 | 21.63 | ||
Total | 49 | 1001.62 |
DF: Degree of freedom
Ad MS: Adjusted Mean square
F-Value: Frequently Value (variance of the group)
P-Value: Probability value
Both higher and lower BP values were found to be detrimental in patients having dialysis, and therefore recommendations to achieve a target BP were set forth. However, there are no strict guidelines and they vary from patient to patient. In a US study comprising 2535 hemodialysis patients, 86% were found to be suffering from hypertension. Even in the patients taking antihypertensives, 58% had poorly controlled BP and 12% had refractory hypertension (Stern et al., 2014).
Another anthropometric measurement is temperature (Table 4). Temperature values taken before hemodialysis were significantly high in patients having dialysis, as observed in Table 4.
Table 4. Analysis of variance for temperature.
Source | DF | Ad SS | Ad MS | F-value | p-value |
---|---|---|---|---|---|
F/C1 | 4 | 5.621 | 1.405 | 0.61 | 0.655 |
Error | 45 | 102.959 | 2.288 | ||
Total | 49 | 108.580 |
DF: Degree of freedom
Ad MS: Adjusted Mean square
F-Value: Frequently Value (variance of the group)
P-Value: Probability value
Blood oxygen saturation values (Table 5) were observed through an oximeter for both groups of patients on dialysis. A significant oxygen saturation level (p = 0.2) was observed in both groups of patients, which showed that both groups had abnormal oxygen levels, and a significant difference in oxygen levels was discovered between the groups.
Table 5. Analysis of variance for oxygen saturation.
Source | DF | Ad SS | Ad MS | F-value | p-value |
---|---|---|---|---|---|
O2saturation1 | 10 | 4217 | 421.7 | 1.36 | 0.235 |
Error | 39 | 12102 | 310.3 | ||
Total | 49 | 16319 |
DF: Degree of freedom
Ad MS: Adjusted Mean square
F-Value: Frequently Value (variance of the group)
P-Value: Probability value
A significant value (p = 0.99) of blood sugar was observed in control and experimental groups (Table 6). Abnormal sugar levels were observed in both groups, and high blood sugar level could affect the kidney.
Table 6. Analysis of variance for blood sugar.
Source | DF | Ad SS | Ad MS | F-value | p-value |
---|---|---|---|---|---|
Blood sugar | 24 | 2626 | 109.4 | 0.34 | 0.995 |
Error | 25 | 8075 | 323.0 | ||
Total | 49 | 10700 |
DF: Degree of freedom
Ad MS: Adjusted Mean square
F-Value: Frequently Value (variance of the group)
P-Value: Probability value
Type 2 diabetes mellitus is one of the leading causes of CKD as well as end-stage renal disease (ESRD) in developed and developing countries (Agboton et al., 2017). In the United States, New Zealand, Japan, and some other Asian countries, type 2 diabetes mellitus accounts for almost 50% of patients having dialysis (United States Renal Data System (USRDS), 2014)
Table 7 shows body weight values of both groups of patients. A significant difference was observed in body weight between the groups (p = 0.90). A significant high value of weight may exert more pressure on the kidneys, leading to joint problems, diabetes, and a high lipid profile.
Table 7. Analysis of variance for body weight.
Source | DF | Ad SS | Ad MS | F-value | p-value |
---|---|---|---|---|---|
Weight | 31 | 1854 | 59.81 | 0.58 | 0.908 |
Error | 18 | 1842 | 102.31 | ||
Total | 49 | 3696 |
DF: Degree of freedom
Ad MS: Adjusted Mean square
F-Value: Frequently Value (variance of the group)
P-Value: Probability value
Another anthropometric measurement includes body fat (Table 8). A significant level of difference was discovered in body fat values between both groups (p = 0.3). High body fat means high BMI, which may affect the kidneys.
Table 8. Analysis of variance for body fat.
Source | DF | Ad SS | Ad MS | F-value | p-value |
---|---|---|---|---|---|
Body fat in control group | 24 | 935.7 | 38.99 | 1.24 | 0.302 |
Error | 25 | 789.2 | 31.57 | ||
Total | 49 | 1724.8 |
DF: Degree of freedom
Ad MS: Adjusted Mean square
F-Value: Frequently Value (variance of the group)
P-Value: Probability value
Table 9 shows BMI of both groups (p = 0.6), indicating a p-value of 0.6, which was more than 0.05, which shows that there is a significant figure present and the tests are inconclusive. Our reading of BMI resembling multi-centre Korean study has BMI values 23.6 ± 3.8. BMI is not a complete indicator of the health or nutrition of hemo-dialysis patients. The underweight group of hemodialysis with less BMI (less than 18.5) had high mortality hazard ration as compared to overweight group (greater than 25) (Kim et al., 2012).
Table 9. Analysis of variance for BMI.
Source | DF | Ad SS | Ad MS | F-value | p-value |
---|---|---|---|---|---|
BMI of control group | 34 | 1008.0 | 29.65 | 0.86 | 0.655 |
Error | 15 | 516.6 | 34.44 | ||
Total | 49 | 1524.6 |
DF: Degree of freedom
Ad MS: Adjusted Mean square
F-Value: Frequently Value (variance of the group)
P-Value: Probability value
Table 10 shows the hemoglobin levels of both groups, with a significant statistical analysis of variance (p = 0.14; SD = 1.46). Both groups showed different hemoglobin levels; however, the experiment group had disturbed hemoglobin levels.
Table 10. Analysis of variance for hemoglobin.
Source | DF | Ad SS | Ad MS | F-value | p-value |
---|---|---|---|---|---|
Hb | 18 | 58.73 | 3.263 | 1.53 | 0.147 |
Error | 31 | 66.32 | 2.139 | ||
Total | 49 | 125.05 |
DF: Degree of freedom
Ad MS: Adjusted Mean square
F-Value: Frequently Value (variance of the group)
P-Value: Probability value
Hemodialysis patients are more anemic. If the hemoglobin level is less than 11 g/100 mL, then it represents impairment in the quality of life and reduces exercise capacity, energy level, thereby affecting rate of morbidity and mortality (Perlman et al., 2005).
GFR for both groups shows significant differences in values (p = 0.57, SD = 3.86; Table 11).
Table 11. Analysis of variance for GFR
Source | DF | Ad SS | Ad MS | F-value | p-value |
---|---|---|---|---|---|
GFR | 25 | 346.8 | 13.87 | 0.93 | 0.573 |
Error | 24 | 358.5 | 14.94 | ||
Total | 49 | 705.3 |
DF: Degree of freedom
Ad MS: Adjusted Mean square
F-Value: Frequently Value (variance of the group)
P-Value: Probability value
The percentage of incident patients starting dialysis with an estimated GFR (eGFR) of ≥10 mL/min/1.73 m2 increased from 13% in 1996 to 43% in 2010 but declined to 39% in 2016. However, the mean eGFR at the initiation of dialysis in 2016 was 9.7 mL/min/1.73 m2 (USRDS, 2018).
The recent guidelines suggest the initiation of dialysis when clinical manifestations of kidney failure are present and not merely on a decrease in GFR.
The results of all anthropometric measurements showed that there was not a single grouped data whose p-value was less than 0.05, which indicated the correctness of data with significant differences between them.
After anthropometric measurements, we investigated dietary changes and implementations after the start of hemodialysis. The grouped data for patients were considered and converted into per day serving in calories. Table 12 shows the calorie intake of meat (p = 0.6). Thus, the statistical analysis of the data shows p > 0.05, with significant level of difference.
Table 12. Analysis of variance for meat intake.
Source | DF | Ad SS | Ad MS | F-value | p-value |
---|---|---|---|---|---|
Meat | 44 | 3018581 | 68604 | 0.81 | 0.688 |
Error | 5 | 421231 | 84246 | ||
Total | 49 | 3439812 |
DF: Degree of freedom
Ad MS: Adjusted Mean square
F-Value: Frequently Value (variance of the group)
P-Value: Probability value
Table 13 shows the calorie count for cereals. The cereal intake in both groups was different (p = 0.79), with a high protein intake, which is less recommended for dialysis patients.
Table 13. Analysis of variance for cereals.
Source | DF | Adj SS | Adj MS | F-value | p-value |
---|---|---|---|---|---|
Cereal | 36 | 3382721 | 93964 | 0.71 | 0.794 |
Error | 13 | 1711922 | 131686 | ||
Total | 49 | 5094643 |
DF: Degree of freedom
Ad MS: Adjusted Mean square
F-Value: Frequently Value (variance of the group)
P-Value: Probability value
Almost 50–70% of patients appeared to have total energy and protein content that was consistent with the minimum recommended intake. Our findings of generally low consistency of dietary intake were similar to dietary practice guidelines among the hemodialysis population (Bossala et al., 2014)
Table 14 shows significant statistical analysis of variance for dairy products. The difference level found between the grouped data and the results was inconclusive. Both groups showed different dairy intake values; however, more intake of dairy products with protein is not appropriate for dialysis patients.
Table 14. Analysis of variance for dairy products.
Source | DF | Ad SS | Ad MS | F-value | p-value |
---|---|---|---|---|---|
Dairy | 29 | 268395 | 9255 | 0.99 | 0.519 |
Error | 20 | 186740 | 9337 | ||
Total | 49 | 455135 |
DF: Degree of freedom
Ad MS: Adjusted Mean square
F-Value: Frequently Value (variance of the group)
P-Value: Probability value
Bones mostly comprise calcium and phosphorus. If the kidneys function well, a balance is maintained between calcium and phosphorus in the blood and bones. However, kidney disease causes imbalance of these two minerals and excess of phosphorus is accumulated in the blood. Diseased kidneys no longer activate vitamin D, which affects their ability to absorb calcium. Low blood calcium levels lead to absorption of calcium and phosphorus from bones, resulting in weakness (Yoke Mun et al., 2019). According to Quddoos et al. (2022), calcium from natural sources eggshell powder (ESP) and bone extract powder (BEP) could be the cheapest and richest calcium sources to be explored as “natural calcium fortificants.” fortified cookies with natural fortificants like ESP and BEP (75% Recommend daily allowance (RDA)) could be a beneficial for business of commercial FMCG companies to combat calcium deficiency amongst adolescent boys.
Table 15 shows significant values for vegetable intake by both groups. Uncooked toxic-free vegetables are good for dialysis patients.
Table 15. Analysis of variance for vegetables.
Source | DF | Ad SS | Ad MS | F-value | p-value |
---|---|---|---|---|---|
Vegetables | 20 | 139315 | 6966 | 1.00 | 0.494 |
Error | 29 | 202822 | 6994 | ||
Total | 49 | 342137 |
DF: Degree of freedom
Ad MS: Adjusted Mean square
F-Value: Frequently Value (variance of the group)
P-Value: Probability value
Hemodialysis leaves the patient with few or no nutrients at all. Therefore, protein and high-energy food is required for dialysis patients to have normal weight. Most of the Hemodialysis patients lose weight and are malnourished. The survey (Table 16) shows the significance of calorie intake of patients through fruits. Both groups showed different intake of fruits.
Table 16. Analysis of variance for fruits.
Source | DF | Ad SS | Ad MS | F-value | p-value |
---|---|---|---|---|---|
Fruits | 20 | 228912 | 11446 | 1.03 | 0.465 |
Error | 29 | 323495 | 11155 | ||
Total | 49 | 552407 |
DF: Degree of freedom
Ad MS: Adjusted Mean square
F-Value: Frequently Value (variance of the group)
P-Value: Probability value
Studies have shown that in 100 CKD patients, about 6% were males and 31% were females. Their average age was 46–50 years, and most of them were females. This shows that CKD is more prevalent in females than in males. In our study, we included 50 CKD patients having hemodialysis and 50 normal patients (Table 17).
Table 17. Age of gender and group.
Age of male and female patients | Variable | Mean | Median | Range |
---|---|---|---|---|
Age | 46.40 | 42.50 | 52.00 | |
Females | 7.90 | 8.00 | 18.00 | |
Males | 2.600 | 1.500 | 4.000 | |
Age of the control group | Age | 27.20 | 26.50 | 33.00 |
Females | 3.900 | 3.500 | 9.000 | |
Males | 2.900 | 2.000 | 6.000 |
Age = maximum (72 years), minimum (20 years). Females = males = 31%.
The survey showed that patients on hemodialysis and non-hemodialysis patients belonged to all strata of society. Thus, 40% of them belonged to lower income group, 30% were from middle-income families, and the rest 30% were from the upper socioeconomic strata of the society (Table 18).
Table 18. Socioeconomic status.
Socioeconomic status | Socioeconomic status | ||
---|---|---|---|
Lower class | 20 | Lower class | 20 |
Middle class | 15 | Middle class | 15 |
Upper class | 15 | Upper class | 15 |
Patients on hemodialysis experience some post-dialysis effects, and swelling in the body is one of them. About 96% of hemodialysis patients have body swelling (Table 19).
Table 19. Clinical manifestations of hemodialysis patients.
Sign and symptoms | Occurrence | Frequency |
---|---|---|
Post and pre-dialysis swelling | Yes | 48 |
No | 2 | |
Post-dialysis body pain | Yes | 34 |
No | 16 | |
Urge to urinate often | Yes | 23 |
No | 27 | |
Water retention | Yes | 49 |
No | 1 | |
Have you lost weight after having dialysis? | Yes | 45 |
No | 4 | |
Often | 1 | |
Do you have abnormal metabolic activities after dialysis? | Yes | 43 |
No | 4 | |
Often | 3 | |
Do you have muscle cramps after dialysis? | Yes | 39 |
No | 7 | |
Often | 4 | |
Do you consult any nutritionist for post-dialysis meal plans? | Yes | 19 |
No | 27 | |
Often | 4 | |
Edema on feet | Yes | 41 |
No | 9 | |
Triceps skin fold thickness(TSFT) | Yes | 38 |
No | 12 | |
Mid-arm circumference(MAC) | Yes | 43 |
No | 7 | |
Hand grip strength(HGS) | Normal | 20 |
Weak | 30 |
Body pain is another clinical manifestation experienced by CKD patients on hemodialysis. About 32% of patients don’t experience body pain, while 68% patients complain about severe muscles cramps (Table 19).
The urge or frequency to urinate states a lot about kidney functioning. Thus, the research data showed that 46% of hemodialysis patients get a sudden and intense urge to urinate, while the rest 54% have no such urge to urinate, which is rare but varies with patients (Table 19).
Water retention or edema is the most common symptom among CKD patients on hemodialysis. In edema, the body fluid accumulates in the specific location of patient’s body. The severity of edema depends upon the stage at which the patient is having hemodialysis. Thus, the data showed that 98% of hemodialysis patients experienced edema (Table 19).
Hemodialysis consumes a lot of body energy and the body starts losing fat, proteins, and essential vitamins. Therefore, a sudden decrease in weight takes place and this could be a warning sign for CKD patients. Weight loss affects 45 out of 50 patients. However, this could be treated with some good supplementations and dietary management practices (Table 19).
Hemodialysis happens in a constant loop and this could be done 3–4 times a week. Of the 50 patients, 48 usually have hemodialysis 3–4 times a week. When asked whether patients would like to have this fluid exchange treatment at home, out of 50, 48 patients were comfortable in having hemodialysis at the hospital. Most of the patients are affected by hemodialysis. Hemodialysis is process of exchanging fluid, and therefore there are maximum chances of losing a lot of weight/energy during this process. Thus, in hemodialysis all metabolic activities are affected and the patient starts losing energy plus body mass more than normal (Table 19).
Table 19 shows that out of 50 hemodialysis patients 39 suffer from muscle cramps and uneasiness. Hemodialysis could leave the patient skinny by absorbing all essential nutrients. Patients on hemodialysis are recommended to take a high protein and energy diet to avoid malnutrition (Table 19).
Only few patients consult dietician to avoid malnutrition. Our conducted survey showed that out of 50 hemodialysis patients about 34 had high-protein diet (Table 19).
Edema on the feet was diagnosed in 41 hemodialysis patients, while nine volunteers had no such clinical manifestation. The majority of our patients had TSFT (n = 38), and 43 patients showed mild to moderate depletion of fat and MAC, indicating good protein store. Most of our patients had weak HGS (n = 30). Demographic features and anthropometric measures are described in Table 19. According to Birajdar et al. (2019), most of hemodialysis patients have edema because of multiple factors, such as excessive fluid intake, low albumin, poor cardiac status, intradialytic hypotension, and poor performance of dialysis. The authors discovered that 21 patients had pedal edema in spite of having hemodialysis thrice per week. In an MAC study conducted by Araujo et al. (2006), 18 out of 68 females had less than 90% MAC.
In females having hemodialysis, the TSFT was 10.5 ± 3.8, which was significant. According to Stevenson et al. (2018), TSFT is a reliable method for mass assessment in daily practice in patients of stage IV/V CKD, compared to bio-impedance.
Handgrip strength is a reliable and straightforward method for evaluating muscle function. HGS is routinely used as a function of skeletal muscle strength and function in the nutritional evaluation of the general population. The functional status of general muscle strength is correlated consistently with the extent of HGS. In an Indian study, HGS in most males was weak, compared to the general population of the same age group (Visiedo et al., 2022).
Table 20 shows the nutrient intake of patients having dialysis. Sodium (p < 0.774) and β-carotene intake (p = 0.728) was higher in both control and hemodialysis groups. Other nutrient intake, including microelements and vitamins, showed no significant difference between the two groups. Conclusion
Table 20. Comparison of dietary intake between two groups.
Variables | Control group | Hemodialysis group | p-value |
---|---|---|---|
Cholesterol (mg) | 279.0120±122.11f | 225.223±111.90f | 0.021 |
Dietary fiber (g/kg) | 0.2704±0.10i | 0.2261±0.20i | 0.240 |
Phosphorus (mg) | 764.2541±242.15d | 741.82±142.72d | 0.581 |
Sodium (mg) | 3184.20±1132a | 3243.812±742a | 0.774 |
Potassium (mg) | 2154.1291±514c | 1843.1661±450c | 0.234 |
Zinc (mg) | 22.7151±6.27h | 8.5052±2.48h | 0.165 |
Vitamin A (μg) | 612.6312±203e | 615.4010±112.18e | 0.852 |
Retinol (μg) | 111.5174±84.21gh | 91.1438±58.22h | 0.061 |
β-carotene (μg) | 2537.7511±2221b | 2951.812±1438b | 0.728 |
Vitamin B1 (mg) | 0.5121±0.36l,m | 0.6175±0.34m | 0.177 |
Vitamin B2 (mg) | 0.9140±0.46l | 0.8708±0.39l,m | 0.142 |
Vitamin B6 (mg) | 1.5746±0.44k | 1.5556±0.22l | 0.755 |
Vitamin C (mg) | 86.7411±71.34h | 62.5221±21.83h,i | 0.067 |
Vitamin E (mg) | 12.5208±7.57i,j,k | 11.2016±3.90j,k | 0.276 |
Niacin (mg) | 13.517±5.08i,j | 13.123±5.26j | 0.707 |
Folate (μg) | 162.554±51.05g | 169.234±58.20g | 0.804 |
This study concludes that balanced nutrition plays an important role in maintaining the quality of life in hemo-dialysis patients. Nutritional assessment of hemodialysis patients was conducted to study nutritional requirements and its effect on such patients. Hemodialysis can play an important role in malnutrition. In both cases, patients suffer and their quality of life is degraded. Therefore, it is recommended to fulfil nutritional requirements and daily caloric intake of dialysis patients. These patients may go through severe traumas, which can affect their mental and physical well-being.
Dialysis patients must consult a dietician for proper meal plans to make sure to have daily calorie count. Hemodialysis patients should increase their calorie intake, but the studies have shown that they are not able to take the required amount of calories and end up losing weight. Poor nutrition, sedentary lifestyle, and unhygienic practices could compound this disease. On the other hand, good weight management practices, a balanced diet, and a healthy lifestyle could improve the quality of life of hemodialysis patients.
Data can be provided on demand.
The authors declared no conflict of interest and gave their consent for publishing the article.
The authors would like to thank the Researchers Supporting Project Number (RSP2024R35), King Saud University, Riyadh, Saudi Arabia.
The authors are thankful to PMAS Arid Agriculture University Rawalpindi, Pakistan for providing the research facilities used for this study. The authors would like to thank the Researchers Supporting Project Number (RSP2024R35), King Saud University, Riyadh, Saudi Arabia.
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