Introduction
Changes in lifestyles and dietary habits, smoking, obesity and aging have attributed to increases in the prevalence rate of kidney diseases annually [1]. The pathogenesis of CKD involves complex interactions among genetic susceptibility, environmental exposures, and lifestyle factors. Among these, dietary patterns are a key modifiable risk factor that plays a pivotal role in both the development and progression of CKD [2]. Dietary manipulation is an important strategy in the management of patients with NCDs, including CKD. A systematic review highlighted the diverse dietary patterns in India, including large variations across regions and over time. For example, vegetables, rice and pulses were popular in the North and West, sweets, snacks, meat or fish were the most prevalent diets in the Eastern and Southern parts of India. Accurate assessment of dietary intake is therefore essential to develop appropriate dietary advice for people with chronic conditions [3]. In the field medical nutrition therapy and dietary intervention, few number studies have concluded that dietary Approaches to Stop Hypertension (DASH) which are rich in protective nutrients such as antioxidant vitamins including vitamin E, C, A, potassium, magnesium, calcium, fibre, omega fatty acids, and phytochemicals, can affect kidney function and decrease the risk of CKD [4]. Studies have indicated that enough intake of micronutrients such as vitamin C, vitamin E, cobalamin, vitamin D, potassium, magnesium can decrease the risk of CKD. In addition, there can be delay the course of CKD in case of reducing protein intake which will further lower the production of blood urea nitrogen. The kidneys of patients with CKD are partially impaired and are unable to metabolize excessive nutrients and toxins from the body. Thus, these patients are prone to secondary hyperparathyroidism and hyperphosphatemia [1]. Dietary intake has potential influences on the occurrence and progression of CKD [1]. Dietary patterns represent a broader picture of food and nutrient consumption, and may thus be more predictive of disease risk than individual foods or nutrients [5]. Due to the paucity of studies on this topic from the Andaman and Nicobar Islands, and considering the potential role of diet in the development and progression of chronic kidney disease (CKD), we investigated the association between dietary food patterns and the prevalence of CKD.
Methods
Aim
To assess the adequacy of dietary intake pattern in terms of calorie and protein intake among patients with chronic kidney disease undergoing dialysis in South Andaman.
Study Design and Setting
A cross-sectional, facility-based study was conducted among patients diagnosed with chronic kidney disease (CKD) undergoing dialysis at the Dialysis Unit of G.B. Pant Hospital, Andaman and Nicobar Island Institute of Medical Sciences (ANIIMS), Port Blair and the Dialysis Unit at Community Health Centre (CHC), Bambooflat.
Ethical approval was obtained from the Institutional Ethics Committee of Andaman and Nicobar Island Institute of Medical Sciences (ANIIMS) prior to the commencement of the study. Data collection was carried out during the study period through direct interviews with the participants.
Study Population
The study population consisted of patients diagnosed with advanced CKD who were receiving dialysis at the selected centres during the study period.
Sampling Technique
A universal sampling technique was used. All eligible CKD patients attending the dialysis units during the study period and fulfilling the inclusion criteria were approached for participation in the study.
Inclusion Criteria
-
Patients diagnosed with CKD.
-
Patients undergoing dialysis at the selected dialysis units
-
Patients who were willing to provide written informed consent
Exclusion Criteria
-
Patients with severe cognitive or physical impairment that prevented participation in the interview
Data Collection
After obtaining written informed consent, data were collected using a pre-structured and pre-tested questionnaire administered through face-to-face interviews.
Information collected included:
-
Dietary intake pattern of different food groups was assessed using a food frequency approach, where participants reported the frequency of consumption of various food groups including:
-
Cereals and cereal products
-
Vegetables (vitamin A–rich vegetables, dark green leafy vegetables, other vegetables)
-
Fruits (vitamin A–rich fruits and other fruits)
-
Animal-source foods (organ meats, flesh meats, eggs, fish)
-
Legumes, nuts and seeds
-
Milk and milk products
-
Oils and fats
-
Sweets and sugar-containing foods
-
Spices, condiments and beverages
Responses were categorized as daily, weekly, bi-weekly, monthly, or never. The data were recorded using EpiCollect software
Statistical Analysis
Data were entered and analysed using Statistical Package for the Social Sciences (SPSS) version 26.
-
Frequencies and percentages were calculated to describe the dietary intake pattern of participants.
-
The Chi-square test was used to assess the association between frequency of consumption of different food groups and CKD stage (Stage IV and Stage V).
-
A p-value <0.05 was considered statistically significant.
Results
In Table I, the majority of participants were aged <60 years (63.5%) and predominantly male (65.0%). Most belonged to urban areas (62.6%) and were married (83.7%). Regarding education, the largest proportion had attained middle school level (32.0%), followed by high school (25.1%). Nearly equal proportions were skilled (46.3%) and unemployed (45.8%), while only a small fraction were unskilled (7.9%). According to the modified BG Prasad Scale, most participants belonged to the upper class (45.8%) and upper middle class (32.5%). A vast majority lived in nuclear families (83.3%).
| Socio-Demographic Characteristics | Frequency (N=203) | Percentage (%) | |
| Age | <60 | 129 | 63.54 |
| >60 | 74 | 36.46 | |
| Sex | Female | 71 | 34.98 |
| Male | 132 | 65.02 | |
| Residence | Rural | 76 | 37.44 |
| Urban | 127 | 62.56 | |
| Marital status | Married | 170 | 83.74 |
| Widowed/ Divorces | 15 | 7.79 | |
| Single | 18 | 8.86 | |
| Education Level | Illiterate | 25 | 12.31 |
| Primary school certificate | 34 | 16.74 | |
| Middle school certificate | 65 | 32.01 | |
| High school certificate | 51 | 25.12 | |
| Intermediate or diploma | 8 | 3.94 | |
| Graduate & above/ Professional | 20 | 9.84 | |
| Occupation | Skilled | 94 | 46.29 |
| Unskilled | 16 | 7.90 | |
| Unemployed | 93 | 45.81 | |
| Socio-economic status (as per modified BG Prasad scale, 2025): | Upper class | 93 | 45.81 |
| Upper middle | 66 | 32.51 | |
| Middle class | 16 | 7.88 | |
| Lower middle | 19 | 9.35 | |
| Lower class | 9 | 4.43 | |
| Type of Family | Nuclear | 169 | 83.25 |
| Joint | 24 | 11.82 | |
| Three Generation | 10 | 4.92 |
Table II shows that more than half of the participants (55.7%) had adequate calorie intake; however, a substantial proportion (37.9%) remained in calorie deficit. In contrast, protein intake was suboptimal, with nearly half (48.3%) exhibiting deficiency, highlighting a gap between caloric sufficiency and protein adequacy among the study population.
| Calorie (Kcal) | Frequency(n=203) | Percentage |
| <1600 | 77 | 37.9% |
| 1600-2200 | 113 | 55.7% |
| >2200 | 13 | 6.4% |
| Protein(g/day) | Frequency(n=203) | Percentage |
| <50 | 98 | 48.3% |
| 50-75 | 96 | 47.3% |
| >75 | 9 | 4.4% |
In Table III, the dietary intake pattern of the 203 participants showed that cereals and cereal-based foods were the staple component of the diet, with 99.51% consuming them daily. A considerable proportion of participants also reported frequent consumption of other vegetables (60.59%), eggs (41.38%), legumes, nuts and seeds (38.92%), and fish (35.47%) on a daily basis. Oil and fats were consumed daily by 80.79%, while spices, condiments and beverages were consumed daily by 89.16% of the participants.
| Frequency(n=203) | Percentage (%) | ||
| Cereals | Daily intake | 202 | 99.51 |
| Weekly intake | 1 | 0.49 | |
| Vitamin A rich vegetables and tubers | Daily intake | 36 | 17.73 |
| Bi-weekly intake | 36 | 17.73 | |
| Weekly intake | 109 | 53.69 | |
| Monthly intake | 22 | 10.84 | |
| White tubers and roots | Daily intake | 41 | 20.20 |
| Bi-weekly intake | 38 | 18.72 | |
| Weekly intake | 65 | 32.02 | |
| Monthly intake | 59 | 29.06 | |
| Dark green leafy vegetables | Daily intake | 56 | 27.59 |
| Bi-weekly intake | 21 | 10.34 | |
| Weekly intake | 68 | 33.50 | |
| Monthly intake | 58 | 28.57 | |
| Other vegetables | Daily intake | 123 | 60.59 |
| Bi-weekly intake | 23 | 11.33 | |
| Weekly intake | 37 | 18.23 | |
| Monthly intake | 20 | 9.85 | |
| Vitamin A rich fruits | Daily intake | 14 | 6.90 |
| Bi-weekly intake | 41 | 20.20 | |
| Weekly intake | 76 | 37.44 | |
| Monthly intake | 72 | 35.47 | |
| Other fruits | Daily intake | 7 | 3.45 |
| Bi-weekly intake | 37 | 18.23 | |
| Weekly intake | 61 | 30.05 | |
| Monthly intake | 98 | 48.28 | |
| Organ meat | Daily intake | 11 | 5.42 |
| Bi-weekly intake | 48 | 23.65 | |
| Weekly intake | 60 | 29.56 | |
| Monthly intake | 77 | 37.93 | |
| Never | 7 | 3.45 | |
| Flesh meats | Daily intake | 15 | 7.39 |
| Bi-weekly intake | 41 | 20.20 | |
| Weekly intake | 80 | 39.41 | |
| Monthly intake | 60 | 29.56 | |
| Never | 7 | 3.45 | |
| Eggs | Daily intake | 84 | 41.38 |
| Bi-weekly intake | 16 | 7.88 | |
| Weekly intake | 81 | 39.90 | |
| Monthly intake | 15 | 7.39 | |
| Never | 7 | 3.45 | |
| Fish | Daily intake | 72 | 35.47 |
| Bi-weekly intake | 7 | 3.45 | |
| Weekly intake | 107 | 52.71 | |
| Monthly intake | 10 | 4.93 | |
| Never | 7 | 3.45 | |
| Legumes, nuts and seeds | Daily intake | 79 | 38.92 |
| Bi-weekly intake | 32 | 15.76 | |
| Weekly intake | 59 | 29.06 | |
| Monthly intake | 33 | 16.26 | |
| Milk and milk products | Daily intake | 36 | 17.73 |
| Bi-weekly intake | 37 | 18.23 | |
| Weekly intake | 67 | 33.00 | |
| Monthly intake | 63 | 31.03 | |
| Oil and fats | Daily intake | 164 | 80.79 |
| Bi-weekly intake | 21 | 10.34 | |
| Weekly intake | 13 | 6.40 | |
| Monthly intake | 5 | 2.46 | |
| Red palm products | Daily intake | 4 | 1.97 |
| Bi-weekly intake | 26 | 12.81 | |
| Weekly intake | 14 | 6.90 | |
| Monthly intake | 159 | 78.33 | |
| Sweets | Daily intake | 81 | 39.90 |
| Bi-weekly intake | 25 | 12.32 | |
| Weekly intake | 45 | 22.17 | |
| Monthly intake | 52 | 25.62 | |
| Spices, condiments, Beverages | Daily intake | 181 | 89.16 |
| Bi-weekly intake | 5 | 2.46 | |
| Weekly intake | 15 | 7.39 | |
| Monthly intake | 2 | 0.99 |
Consumption of vitamin A rich vegetables and tubers was predominantly weekly (53.69%), while dark green leafy vegetables were most commonly consumed weekly (33.50%), followed by monthly (28.57%) and daily intake (27.59%). White tubers and roots were mainly consumed weekly (32.02%) and monthly (29.06%), with only 20.20% reporting daily intake. With respect to fruit intake, vitamin A rich fruits were consumed weekly by 37.44% and monthly by 35.47%, while only 6.90% consumed them daily. Similarly, other fruits were mainly consumed monthly (48.28%) or weekly (30.05%), with very few participants reporting daily intake (3.45%), indicating relatively low daily fruit consumption among the study population.
Regarding animal source foods, flesh meat was mainly consumed weekly (39.41%), whereas organ meat was most commonly consumed monthly (37.93%). Fish consumption was relatively frequent, with 52.71% consuming it weekly and 35.47% daily. Milk and milk products were consumed weekly by 33.00% and monthly by 31.03%. Consumption of sweets was reported daily by 39.90% of participants, and the majority reported eating outside the home on a monthly basis at both the individual (85.22%) and household level (84.73%).
Table IV shows that, among Stage IV CKD patients, more than half had a calorie deficit (54.5%), while 45.5% had adequate intake and none reported excess intake. Similarly, in Stage V patients, the majority also had a calorie deficit (53.6%), followed by adequate intake (42.2%) and a small proportion with excess intake (4.2%). Overall, calorie intake patterns were comparable between Stage IV and Stage V patients, and the association was not statistically significant (p = 0.784).
| Calorie interpretation | CKD Stage IV | CKD Stage V | p- value |
| Adequate | 5(45.5%) | 81(42.2%) | 0.784 |
| Deficit | 6(54.5%) | 103(53.6%) | |
| Excess | 0(0.0%) | 8(4.2%) |
In Table V, among patients with Stage IV CKD, a majority had high dietary diversity (72.7%), followed by medium diversity (27.3%), with no participants in the low diversity category. In contrast, among Stage V patients, high dietary diversity was observed in 53.1%, while 29.2% and 17.7% had medium and low dietary diversity, respectively.
Table V: Association between dietary diversity and stage of CKD.
| Diet Diversity | Stage IV | Stage V | p-value |
| High | 8(72.7%) | 102(53.1%) | 0.259 |
| Medium | 3(27.3%) | 56(29.2%) | |
| Low | 0(0%) | 34(17.7%) |
Although a higher proportion of Stage IV patients exhibited better dietary diversity compared to Stage V, the association between dietary diversity and CKD stage was not statistically significant (p = 0.259).
Table IV shows, intake of cereals was almost universal among the study participants. Daily consumption was reported by 90.91% of patients in CKD stage IV and 100% in CKD stage V, while 9.09% of stage IV patients reported weekly intake. However, this difference was not statistically significant (p = 0.054). Regarding vegetable intake, vitamin A–rich vegetables and tubers were most commonly consumed on a weekly basis by 55.21% of stage V patients, whereas stage IV patients showed a more varied intake pattern including bi-weekly, weekly, and monthly consumption. Similarly, white tubers and roots were consumed mostly weekly or monthly in both groups. Dark green leafy vegetables were consumed daily by 63.64% of stage IV patients compared to 25.52% of stage V patients, although this difference was not statistically significant (p > 0.05). Intake patterns of other vegetables were also comparable between the two groups.
| Stage of CKD | p-value | |||||
| IV | V | |||||
| Frequency(n=203) | Percentage | Frequency(n=203) | Percentage | |||
| Cereals | Daily intake | 10 | 90.91 | 192 | 100.00 | 0.054 |
| Weekly intake | 1 | 9.09 | 0 | 0.00 | ||
| Vitamin A rich vegetables and tubers | Daily intake | 2 | 18.18 | 34 | 17.71 | 0.171 |
| Bi-weekly intake | 3 | 27.27 | 33 | 17.19 | ||
| Weekly intake | 3 | 27.27 | 106 | 55.21 | ||
| Monthly intake | 3 | 27.27 | 19 | 9.90 | ||
| White tubers and roots | Daily intake | 1 | 9.09 | 40 | 20.83 | 0.456 |
| Bi-weekly intake | 4 | 36.36 | 34 | 17.71 | ||
| Weekly intake | 4 | 36.36 | 61 | 31.77 | ||
| Monthly intake | 2 | 18.18 | 57 | 29.69 | ||
| Dark green leafy vegetables | Daily intake | 7 | 63.64 | 49 | 25.52 | 0.18 |
| Bi-weekly intake | 0 | 0.00 | 21 | 10.94 | ||
| Weekly intake | 4 | 36.36 | 64 | 33.33 | ||
| Monthly intake | 0 | 0.00 | 58 | 30.21 | ||
| Other vegetables | Daily intake | 9 | 81.82 | 114 | 59.38 | 0.385 |
| Bi-weekly intake | 1 | 9.09 | 22 | 11.46 | ||
| Weekly intake | 0 | 0.00 | 37 | 19.27 | ||
| Monthly intake | 1 | 9.09 | 19 | 9.90 | ||
| Vitamin A rich fruits | Daily intake | 2 | 18.18 | 12 | 6.25 | 0.46 |
| Bi-weekly intake | 3 | 27.27 | 38 | 19.79 | ||
| Weekly intake | 0 | 0.00 | 76 | 39.58 | ||
| Monthly intake | 6 | 54.55 | 66 | 34.38 | ||
| Other fruits | Daily intake | 1 | 9.09 | 6 | 3.13 | 0.634 |
| Bi-weekly intake | 2 | 18.18 | 35 | 18.23 | ||
| Weekly intake | 2 | 18.18 | 59 | 30.73 | ||
| Monthly intake | 6 | 54.55 | 92 | 47.92 | ||
| Organ meat | Daily intake | 2 | 18.18 | 9 | 4.69 | 0.094 |
| Bi-weekly intake | 5 | 45.45 | 43 | 22.40 | ||
| Weekly intake | 2 | 18.18 | 58 | 30.21 | ||
| Monthly intake | 2 | 18.18 | 75 | 39.06 | ||
| Never | 0 | 0.00 | 7 | 3.65 | ||
| Flesh meats | Daily intake | 2 | 18.18 | 13 | 6.77 | 0.321 |
| Bi-weekly intake | 4 | 36.36 | 37 | 19.27 | ||
| Weekly intake | 3 | 27.27 | 77 | 40.10 | ||
| Monthly intake | 2 | 18.18 | 58 | 30.21 | ||
| Never | 0 | 0.00 | 7 | 3.65 | ||
| Eggs | Daily intake | 6 | 54.55 | 78 | 40.63 | 0.042 |
| Bi-weekly intake | 1 | 9.09 | 15 | 7.81 | ||
| Weekly intake | 1 | 9.09 | 80 | 41.67 | ||
| Monthly intake | 3 | 27.27 | 12 | 6.25 | ||
| Never | 0 | 0.00 | 7 | 3.65 | ||
| Fish | Daily intake | 10 | 90.91 | 62 | 32.29 | 0.008 |
| Bi-weekly intake | 0 | 0.00 | 7 | 3.65 | ||
| Weekly intake | 1 | 9.09 | 106 | 55.21 | ||
| Monthly intake | 0 | 0.00 | 10 | 5.21 | ||
| Never | 0 | 0.00 | 7 | 3.65 | ||
| Legumes, nuts and seeds | Daily intake | 0 | 0.00 | 79 | 41.15 | 0.14 |
| Bi-weekly intake | 4 | 36.36 | 28 | 14.58 | ||
| Weekly intake | 6 | 54.55 | 53 | 27.60 | ||
| Monthly intake | 1 | 9.09 | 32 | 16.67 | ||
| Milk and milk products | Daily intake | 1 | 9.09 | 35 | 18.23 | 0.780 |
| Bi-weekly intake | 2 | 18.18 | 35 | 18.23 | ||
| Weekly intake | 5 | 45.45 | 62 | 32.29 | ||
| Monthly intake | 3 | 27.27 | 60 | 31.25 | ||
| Oil and fats | Daily intake | 10 | 90.91 | 154 | 80.21 | 0.622 |
| Bi-weekly intake | 0 | 0.00 | 21 | 10.94 | ||
| Weekly intake | 1 | 9.09 | 12 | 6.25 | ||
| Monthly intake | 0 | 0.00 | 5 | 2.60 | ||
| Red palm products | Daily intake | 0 | 0.00 | 4 | 2.08 | 0.29 |
| Bi-weekly intake | 4 | 36.36 | 22 | 11.46 | ||
| Weekly intake | 2 | 18.18 | 12 | 6.25 | ||
| Monthly intake | 5 | 45.45 | 154 | 80.21 | ||
| Sweets | Daily intake | 2 | 18.18 | 79 | 41.15 | 0.187 |
| Bi-weekly intake | 3 | 27.27 | 22 | 11.46 | ||
| Weekly intake | 4 | 36.36 | 41 | 21.35 | ||
| Monthly intake | 2 | 18.18 | 50 | 26.04 | ||
| Spices, condiments, Beverages | Daily intake | 11 | 100.00 | 170 | 88.54 | 0.702 |
| Bi-weekly intake | 0 | 0.00 | 5 | 2.60 | ||
| Weekly intake | 0 | 0 | 15 | 7.81 | ||
| Monthly intake | 0 | 0.00 | 2 | 1.04 |
For fruits, vitamin A–rich fruits and other fruits were predominantly consumed monthly or weekly among both CKD stages, with no statistically significant association observed between CKD stage and frequency of fruit consumption (p > 0.05). Among protein-rich foods, organ meats and flesh meats were mostly consumed weekly or monthly in both groups without significant differences. However, egg consumption showed a statistically significant association with CKD stage (p = 0.042), with higher daily intake reported among stage IV patients (54.55%) compared to stage V patients (40.63%). Fish intake also demonstrated a significant association (p = 0.008), with 90.91% of stage IV patients reporting daily consumption compared to 32.29% in stage V, where weekly intake was more common (55.21%). Legumes, nuts, and seeds were most frequently consumed weekly among stage IV patients (54.55%) and daily among stage V patients (41.15%), although the difference was not statistically significant. Milk and milk products were commonly consumed weekly or monthly in both groups.
Daily consumption of oils and fats was reported by the majority of participants in both CKD stages (90.91% in stage IV and 80.21% in stage V). Intake of sweets and spices/condiments was also common across both groups, particularly daily consumption of spices and beverages, which was reported by all stage IV patients and 88.54% of stage V patients. However, these differences were not statistically significant.
Discussion
The present study assessed the dietary intake pattern among chronic kidney disease (CKD) patients undergoing dialysis in South Andaman and evaluated its association with the stage of CKD. The findings revealed that cereals constituted the staple food consumed daily by almost all participants (99.5%). This observation is consistent with findings from an exploratory study by Ekbote et al. in New Delhi in 2024, which reported that cereals such as rice and wheat formed the major component of the daily diet whereas other food groups including vegetables, fruits, and milk products were consumed less frequently compared to cereals, reflecting the typical dietary pattern among CKD patients in India [6].
The consumption of vegetables varied across food groups in this study. While other vegetables were consumed daily by a majority of participants, vitamin A–rich vegetables and dark green leafy vegetables were mainly consumed weekly. Vegetables are important sources of vitamins, minerals, and antioxidants and play a significant role in maintaining metabolic balance in CKD patients. Previous studies have shown that vegetable and fruit intake tends to decline as CKD progresses, partly due to dietary potassium restrictions and reduced appetite. A cross sectional study by Nakano et al. in Japan published in 2022 reported that intake of vegetables, green leafy vegetables, and fruits significantly decreased with advancing CKD stages, indicating a progressive decline in consumption of nutrient-rich plant foods among patients with more severe kidney disease [7].The present study also demonstrated frequent intake of animal-source foods such as fish and eggs. Fish consumption was particularly common among participants, which may be influenced by the geographical setting of the Andaman and Nicobar Islands where fish forms a major component of the local diet. A statistically significant association was observed between CKD stage and intake of fish and eggs, suggesting that dietary patterns may change as the disease progresses. Dietary protein intake plays an important role in CKD management, as excessive protein consumption can increase nitrogenous waste products and accelerate renal function decline. According to a randomization study by Yaping Li et al., in China in 2025,nutritional guidelines recommend controlled protein intake among CKD patients to reduce metabolic burden on the kidneys [8].
Legumes, nuts, and seeds were consumed daily or weekly by many participants, indicating their role as plant-based protein sources. Previous research on dietary patterns and kidney disease has highlighted the benefits of diets rich in whole grains, legumes, fruits, vegetables, and fish, while limiting intake of processed foods and sugars. A meta-analysis of cohort studies by Bach et al., in2019 at Australia reported that adherence to healthy dietary patterns characterized by high intake of fruits, vegetables, legumes, nuts, and whole grains was associated with lower odds of developing CKD and reduced risk of albuminuria [9]. Another notable finding of the present study was the high prevalence of daily consumption of oils, fats, spices, and sweets. Excessive intake of fats and sugar-containing foods may contribute to metabolic disorders such as obesity, diabetes, and cardiovascular disease, which are common comorbidities among CKD patients. Cross sectional study by Santin et al., conducted in 2019 at Brazil have identified dietary patterns characterized by high intake of processed foods, sugary beverages, and red meat as “unhealthy dietary patterns” that may negatively influence kidney health [10].
Overall, the findings of the present study indicate that CKD patients undergoing dialysis in South Andaman follow a diet dominated by cereals and certain protein sources, while the intake of fruits and some nutrient-rich vegetables remains relatively limited. Considering the important role of nutrition in slowing CKD progression and improving patient outcomes, these findings highlight the need for targeted nutritional counselling and dietary interventions among dialysis patients.
In conclusion the study reveals that CKD patients predominantly consume a cereal-based diet with high intake of fats and spices, while fruit and nutrient-rich food consumption remains low. Although calorie intake was adequate in many patients, protein deficiency was common, indicating an imbalance in dietary quality. Most dietary factors did not show a significant association with CKD stage; however, intake of eggs and fish was significantly associated. Overall, the findings highlight the need for focused nutritional counselling to improve dietary quality and support better management of CKD patients undergoing dialysis.
Abbreviations
CKD: Chronic Kidney Disease
SPSS: Statistical Package for the Social Sciences
Declarations
Ethical Approval and Consent to participate
The study was conducted in accordance with ethical principles for biomedical research involving human participants. Ethical approval was obtained from the Institutional Ethics Committee of Andaman and Nicobar Islands Institute of Medical Sciences. Written informed consent was obtained from all participants prior to data collection. Confidentiality and anonymity of participants were strictly maintained.
Consent for publication
Not applicable. The manuscript does not contain any individual person’s data in any form (including images or videos)
Availability of supporting data
The datasets used and/or analysed during the current study are not publicly available due to confidentiality considerations but are available from the corresponding author on reasonable request
Competing interests
The authors declare that they have no competing interests.
Funding
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Authors' contributions
Dr Mitul Saha: Conceptualization, data collection, analysis, manuscript drafting
Dr Aanchal Anand: Conceptualization, data collection, analysis, manuscript drafting
Dr Samar Hossain: Conceptualization, data collection, analysis, manuscript review
Dr Ajay Raj: Supervision, critical revision of manuscript