Home Enteral Nutrition (HEN) refers to the administration of nutrition through a feeding tube directly into the gastrointestinal tract and is reserved for patients unable to maintain nutrition orally [1-2]. Over recent decades, HEN has become an essential component of chronic care, allowing patients to receive long-term nutritional support outside hospital settings. It has been particularly valuable for individuals with chronic illness or disability, helping to maintain nutritional status, body composition, and quality of life [3-4]. HEN is commonly prescribed for patients with stroke, cancer, and neurological disorders where swallowing impairment or gastrointestinal dysfunction prevents adequate oral intake [5]. Evidence suggests that HEN may prolong survival, facilitate earlier hospital discharge, and support continuity of care at home [6].   Despite these advantages, HEN use is not without challenges. Patients remain at risk of nutrient deficiencies due to inadequate intake, intolerance to formulas, or tube-related complications. Clinical issues such as aspiration, diarrhoea, or tube obstruction can compromise nutrient absorption and contribute to weight loss [7]. These risks underscore the importance of reliable nutritional screening and monitoring in community settings.   The World Health Organization (WHO) defines malnutrition as an imbalance between nutrient supply and bodily requirements, driven by deficiency, excess, or metabolic alterations [8-9]. Traditionally, Body Mass   Index (BMI) has been the most widely used screening tool. However, BMI alone is insufficient for accurately detecting malnutrition, especially in patients with chronic disease, highlighting the need for more comprehensive assessment approaches [10].   The Malnutrition Universal Screening Tool (MUST) is a widely validated instrument designed to identify adults at risk of malnutrition. It incorporates three simple criteria: BMI, unintentional weight loss, and the impact of acute illness on dietary intake, which together classify patients into low, medium, or high risk categories [11]. While the Mini Nutritional Assessment-Long Form (MNA-LF) has often been considered a gold standard in certain clinical and community contexts due to its predictive validity [2,11], the practicality of MUST makes it more feasible for HEN patients, particularly in home or outpatient environments. Its ease of application, reliance only on basic anthropometric data, and suitability for use by both professionals and trained caregivers make it especially advantageous in resource-limited or home-based care settings [2,12].   Globally, HEN is increasingly used, but there remains a lack of evidence on its outcomes in Saudi Arabia [13-14]. Local studies have explored general nutritional support practices but provide limited data on prevalence rates or predictors of malnutrition among adults on long-term HEN. This knowledge gap impedes the development of culturally relevant policies and tailored nutritional interventions.   Therefore, the present study aims to assess malnutrition risk among Saudi adults on HEN using the MUST tool. Specifically, the study seeks to: Estimate the proportion of patients classified as low, medium, or high nutritional risk Identify demographic, clinical, and care-related predictors of malnutrition risk

Study Design and Setting This study employed a cross-sectional descriptive design and was conducted across home care units and outpatient services in three major Saudi Arabian cities: Arar, Riyadh, and Dammam. These sites were selected in collaboration with local healthcare authorities to capture regional diversity and enhance generalizability. The study focused on adult patients receiving long-term Home Enteral Nutrition (HEN).   The sample size was calculated using an assumed malnutrition prevalence of 60% among HEN patients, with a 95% confidence level and 7% margin of error, yielding a minimum requirement of 185 participants. To account for missing data and exclusions, the sample was increased by 15%, resulting in a final recruitment target of 210 participants. This sample was sufficient to provide adequate statistical power for subgroup comparisons and multivariable regression modeling.   Sampling, Inclusion, and Exclusion Criteria Participants were recruited through a multi-center convenience sampling approach coordinated by treating clinicians in the selected cities. While this ensured feasibility and access to patients across diverse diagnoses, it may have introduced a risk of selection bias.   Inclusion criteria Adults aged ≥18 years Receiving enteral nutrition through nasogastric, gastrostomy, or jejunostomy tubes On HEN for at least one month prior to enrollment   Exclusion Criteria Terminal illness with life expectancy <1 month (to avoid confounding by rapid end-of-life decline). Missing critical data (e.g., baseline weight, MUST components, or diagnosis). Patients on exclusive oral or parenteral nutrition. Severe cognitive impairment without a proxy caregiver able to provide informed consent or reliable medical history   Data Collection Procedures Data collection combined structured caregiver interviews, direct patient assessments (where possible), and review of medical records. Trained health personnel performed home visits, ensuring completeness of data capture. To minimize recall bias, caregivers’ reports were cross-verified with available records whenever possible.   Variables and Measures   Demographic and Clinical Variables   Age: Recorded in years (continuous). Gender: Male or female (binary nominal). Primary Diagnosis: Underlying medical condition requiring HEN (categorical: neurological disorder, cancer, gastrointestinal dysfunction, others). Duration of HEN: Recorded in months since initiation (continuous).   Feeding Care, Regimen, and Formula Type   Feeding Regimen: Mode of administration (bolus, continuous, intermittent) (categorical). Formula Type: Enteral nutrition classification (standard, high-protein, disease-specific) (categorical). Dietitian Follow-Up Frequency: Categorized as none, irregular (≤1/month, non-scheduled), or regular (≥2/month, scheduled). Caregiver Training: Whether the primary caregiver received structured HEN management training (yes/no). Feeding Complications Aspiration: Documented aspiration pneumonia (yes/no) Diarrhoea: ≥3 loose stools/day attributed to enteral feeding (yes/no) Tube Blockage: Any obstruction requiring intervention (yes/no) 2.4.4 Anthropometric Measurements Height (cm): Measured to the nearest 0.5 cm using a stadiometer. For bedridden patients, height was estimated via ulna length or knee height using validated prediction equations Current Weight (kg): Measured to the nearest 0.1 kg using calibrated portable scales Previous Weight (kg): Obtained from medical records 3–6 months prior Body Mass Index (BMI, kg/m²): Calculated as weight (kg)/height (m²)   Nutritional Risk Assessment (MUST Components) Malnutrition risk was assessed using the Malnutrition Universal Screening Tool (MUST) [2]   BMI 0: ≥20.0 1: 18.5–19.9 2: <18.5   Unintentional Weight Loss (3–6 months):   0: <5% 1: 5–10% 2: >10% Formula: % Change: [(Previous Weight – Current Weight)/Previous Weight] × 100   Acute Disease Effect   0 = no acute illness/normal intake 2 = acute illness with no intake for >5 days   Outcome Measures Primary Outcome:    Prevalence of malnutrition risk by MUST category: Low (score = 0) Medium (score = 1) High (score ≥2)   Secondary Outcomes:    Associations between malnutrition risk and: Demographics (age, gender) Clinical factors (diagnosis, HEN duration, complications) Care-related factors (dietitian follow-up, caregiver training)   Data Quality and Validation To ensure reliability, all field assessors were trained in standardized anthropometric protocols and MUST scoring. Data entry was double-checked, and discrepancies resolved by secondary verification.   Ethical Considerations Ethical approval was obtained from the Northern Border University Ethics Committee. Written informed consent was obtained from participants or legal guardians prior to participation. Confidentiality was maintained throughout, in line with international research standards.   Statistical Analysis Analyses were performed using Stata v19 (StataCorp LLC, College Station, TX). Descriptive statistics summarized participant characteristics. Categorical variables were reported as n (%) and compared using Chi-square or Fisher’s exact test. Continuous non-normally distributed variables were expressed as medians (IQR) and compared using the Kruskal-Wallis test.   Prevalence of malnutrition risk categories was estimated with 95% confidence intervals (CIs) and displayed graphically.   To identify predictors of malnutrition risk, multinomial logistic regression was applied, with “low risk” as the reference category. Model building followed a two-step approach:   Bivariate Screening: Variables associated with malnutrition risk at p<0.20 were considered for multivariable modeling. This liberal threshold was intentionally selected to avoid excluding potential confounders [2]. Multivariable Model: Candidate variables were entered and refined. Multicollinearity among anthropometric predictors (BMI, weight, % weight change) was assessed; BMI was retained due to high correlation and clinical interpretability. Age and gender were included irrespective of significance to control for demographic effects.   Results are reported as Relative Risk Ratios (RRRs) with 95% CIs. A p-value <0.05 was considered statistically significant.

Participant Characteristics Ourstudy included a total of 210 participants receiving HEN, the majority of whom were female (56.2%) with a median age of 54 years (IQR: 34–72 years). The primary clinical diagnoses varied, with stroke being the most common (30.5%), followed by cancer (24.8%) and neurodegenerative diseases (22.9%). A significant portion of the sample was nutritionally compromised; according to the MUST screening, 65.7% were at high risk for malnutrition. This was reflected in a median BMI of 21 kg/m² (IQR: 18–24). (Table 1). BMI differed significantly (p<0.001), with median values decreasing from the low-risk group (25 (IQR: 23–28)) to the high-risk group (19 (IQR: 17–22)). Acute illness effects (>5 days no intake) were exclusive to the high-risk group (44.9% vs. 0% in the low/medium group, p<0.001). No significant associations were found for gender, primary diagnosis.   Table 1: Participants’ Characteristics by MUST* Nutritional Categories Parameters MUST Risk Category Low Medium High Total P# N 57 (27.1%) 15 (7.1%) 138 (65.7%) 210 (100.0%) - Gender Female 32 (56.1%) 9 (60.0%) 77 (55.8%) 118(56.2%) 0.953 Male 25 (43.9%) 6 (40.0%) 61 (44.2%) 92 (43.8%) - Age 52 (33, 71) 75 (47, 81) 54 (34, 72) 54 (34, 72) 0.170 Primary Diagnosis Cancer 13 (22.8%) 6 (40.0%) 33 (23.9%) 52 (24.8%) 0.459 Head injury 5 (8.8%) 1 (6.7%) 14 (10.1%) 20 (9.5%) - Neurodegenerative disease 16 (28.1%) 5 (33.3%) 27 (19.6%) 48 (22.9%) - Other 5 (8.8%) 0 (0.0%) 21 (15.2%) 26 (12.4%) - Stroke 18 (31.6%) 3 (20.0%) 43 (31.2%) 64 (30.5%) - Acute Illness Effect (>5 days no intake) No 57 (100.0%) 15 (100.0%) 76 (55.1%) 148 (70.5%) <0.001 Yes 0 (0.0%) 0 (0.0%) 62 (44.9%) 62 (29.5%) - BMI 25 [23, 28] 21 [20, 22] 19 [17, 22] 21 [18, 24] <0.001 *MUST: Malnutrition Universal Screening Tool. #Categorical variables compared using Pearson X2 (exact test if expected cell count<5). #Continuous variables reported as median (IQR) and compared using the Kruskal-Wallis test   Table 2: Prevalence of Malnutrition Risk (Based on MUST Categories) MUST Risk Category Count Percentage (%) 95% CI (Lower–Upper) High 138 65.71% 59.29–72.13% Low 57 27.14% 21.13–33.16% Moderate 15 7.14% 3.66–10.63%   Table 3: Enteral Feeding Practices and Nutrition by MUST* Nutritional Categories Parameters MUST Risk Category Low Medium High Total p# N 57 (27.1%) 15 (7.1%) 138 (65.7%) 210 (100.0%) Months on Tube Feeding 17 [10, 26] 6 [4, 20] 20 [9, 26] 18 [8, 26] 0.033 Dietitian Follow-Up Irregular 24 (42.1%) 10 (66.7%) 61 (44.2%) 95 (45.2%) 0.468 None 10 (17.5%) 1 (6.7%) 27 (19.6%) 38 (18.1%) Regular 23 (40.4%) 4 (26.7%) 50 (36.2%) 77 (36.7%) Caregiver Trained No 24 (42.1%) 7 (46.7%) 41 (29.7%) 72 (34.3%) 0.146 Yes 33 (57.9%) 8 (53.3%) 97 (70.3%) 138 (65.7%) Feeding Method Bolus 17 (29.8%) 7 (46.7%) 45 (32.6%) 69 (32.9%) 0.713 Continuous 20 (35.1%) 3 (20.0%) 49 (35.5%) 72 (34.3%) Intermittent 20 (35.1%) 5 (33.3%) 44 (31.9%) 69 (32.9%) Formula Type Diabetic-specific 13 (22.8%) 2 (13.3%) 37 (26.8%) 52 (24.8%) 0.067 Fiber-enriched 15 (26.3%) 2 (13.3%) 36 (26.1%) 53 (25.2%) High protein 14 (24.6%) 9 (60.0%) 28 (20.3%) 51 (24.3%) Standard 15 (26.3%) 2 (13.3%) 37 (26.8%) 54 (25.7%) Weight (kg) 67 (62, 75) 57 (55, 60) 51 (46, 58) 55 (50, 65) <0.001 Past (3–6 months) Weight 68 (64, 78) 61 (57, 64) 56 (51, 63) 61 (54, 68) <0.001 Weight % Change (3–6 months) –3 (–4,–1) –7 (–8, –5) –8 (–11, –5) –6 (–10, –3) <0.001 Energy Adequacy (%) 89 (77,100) 80 (77, 85) 88 (76, 95) 88 (77, 96) 0.262 Malnutrition Status Malnourished 2 (3.5%) 11 (73.3%) 106 (76.8%) 119 (56.7%) <0.001 Well-nourished 55 (96.5%) 4 (26.7%) 32 (23.2%) 91 (43.3%) *MUST: Malnutrition Universal Screening Tool.#Categorical variables compared using Pearson X2 (exact test if expected cell count<5). #Continuous variables reported as median (IQR)and compared using the Kruskal-Wallis test. Past weight: Last recorded weight in the past 3–6 months   Prevalence of Malnutrition The prevalence of malnutrition risk based on MUST categories was high (65.71%, 95% CI: 59.29–72.13%), followed by low (27.14%, 95% CI: 21.13–33.16%) and moderate (7.14%, 95% CI: 3.66–10.63%) risk levels (Table 2, Figure 1).   Table 4: Enteral Feeding Complications by MUST* Nutritional Categories Parameters MUST Risk Category Low Medium High Total P# N 57 (27.1%) 15 (7.1%) 138 (65.7%) 210 (100.0%) - Aspiration No 44 (77.2%) 11 (73.3%) 107 (77.5%) 162 (77.1%) 0.934 Yes 13 (22.8%) 4 (26.7%) 31 (22.5%) 48 (22.9%) Diarrhea No 42 (73.7%) 10 (66.7%) 107 (77.5%) 159 (75.7%) 0.593 Yes 15 (26.3%) 5 (33.3%) 31 (22.5%) 51 (24.3%) Tube Blockage No 46 (80.7%) 13 (86.7%) 111 (80.4%) 170 (81.0%) 0.842 Yes 11 (19.3%) 2 (13.3%) 27 (19.6%) 40 (19.0%) *MUST: Malnutrition Universal Screening Tool. #Categorical variables compared using Pearson X2 (exact test if expected cell count<5)   Table 5: Multinomial Logistic Regression Predicting MUST Risk Category MUST Categories/ Predictors RRR 95% CI vs. Low Risk Low Months on tube feeding 1.00 (1.00,1.00) Diabetic-specific formula 1.00 (1.00,1.00) Fiber-enriched formula 1.00 (1.00,1.00) High protein formula 1.00 (1.00,1.00) Standard formula 1.00 (1.00,1.00) BMI 1.00 (1.00,1.00) Age 1.00 (1.00,1.00) Female 1.00 (1.00,1.00) Male 1.00 (1.00,1.00) Medium (vs. Low) Months on tube feeding 0.96 (0.90,1.03) Diabetic-specific formula 1.00 (1.00,1.00) Fiber-enriched formula 0.68 (0.08,6.02) High protein formula 3.29 (0.54,20.01) Standard formula 0.87 (0.10,7.74) BMI 0.81** (0.68,0.95) Age 1.02 (0.99,1.05) Female 1.00 (1.00,1.00) Male 0.76 (0.21,2.72) High (vs. Low) Months on tube feeding 1.04* (1.00,1.08) Diabetic-specific formula 1.00 (1.00,1.00) Fiber-enriched formula 0.73 (0.24,2.24) High protein formula 0.47 (0.14,1.56) Standard formula 0.79 (0.25,2.49) BMI 0.65*** (0.58,0.74) Age 1.00 (0.98,1.02) Female 1.00 (1.00,1.00) Male 1.06 (0.47,2.39) Observations 210 Pseudo R2 0.313 Exponentiated coefficients; 95% confidence intervals in brackets. *p< 0.10, **p< 0.05, ***p< 0.001     Figure 1: Proportion of MUST Risk Categories Among Participants   Enteral Feeding Practices The median duration of tube feeding was 18 months (IQR: 8–26 months), and approximately two-thirds of caregivers (65.7%) received training in feeding administration. Dietitian follow-up was irregular for most patients (45.2%), and various feeding methods were used, including continuous (34.3%), bolus (32.9%), and intermittent (32.9%). We found that current weight (p<0.001) and past weight (p<0.001) were lower in high-risk participants (51 (46–58) kg and 56 (51–63) kg, respectively) compared to low-risk (67 (62–75) kg and 68 [64–78] kg, respectively). Weight changes over 3–6 months also varied significantly (p<0.001), with high-risk participants experiencing a greater median loss (−8% (−11 to −5%)) than low-risk participants (−3% (−4 to −1%)). Months on tube feeding differed significantly (p = 0.033), butenergy adequacy did not (p = 0.262). Malnutrition status was strongly associated with MUST categories (p<0.001), with 76.8% of high-risk participants classified as malnourished versus 3.5% in the low-risk group. Dietitian follow-up, caregiver training, and formula type also showed no significant differences across MUST categories (all p>0.05) (Table 3).   Enteral Feeding Complications The most common complications reported were diarrhoea(24.3%), aspiration (22.9%), and tube blockage (19.0%). No significant associations were found for feeding complications (aspiration, diarrhoea, tube blockage; all p>0.05) (Table 4). Of the feeding-related complications assessed, only aspiration showed a significant association with formula type (p = 0.045). Aspiration was more frequent among patients receiving diabetic-specific (32.7%) and high-protein (29.4%) formulas compared to those on fibre-enriched (13.2%) or standard (16.7%) formulas. No other significant associations were observed between complications and caregiver training or dietitian follow-up.   Predictors of MUST Risk Categories The multinomial logistic regression model was statistically significant, explaining approximately 31.3% of the variance in risk status (LR) = 107.67, p<0.001, Pseudo R2 0.313. For the high-risk category, BMI was the most significant predictor. For each one-unit increase in BMI, the relative probabilityof being in the high-risk group decreased by 35% (RRR = 0.65, 95% CI [0.58, 0.74), p<0.001). Alonger duration of tube feeding showed a borderline significant association with increased risk (RRR = 1.04, p = 0.072). Formula type, age, and gender were not significant predictors for this group.   When comparing the medium-risk category to the low-risk reference, lower BMI was the only statistically significant predictor. A one-unit increase in BMI was associated with a 19% decrease in the relative chanceof being in the medium-risk category (RRR = 0.81, 95% CI (0.68, 0.95), P = 0.012). None of the other variables –including months on tube feeding, formula type, age, andgender –had a significant impact on the probabilityof being classified as medium-risk versus low-risk.

This multicenter study provides new insights into the nutritional vulnerabilities of Saudi adults receiving Home Enteral Nutrition (HEN). Using the MUST tool, we found that nearly two-thirds (65.7%) of participants were classified as high risk for malnutrition. This prevalence mirrors international findings, underscoring that malnutrition remains a persistent and widespread complication in long-term care despite the therapeutic intent of HEN.   Key Predictors of Malnutrition Risk Among evaluated predictors, BMI emerged as the most robust determinant of MUST category classification. Each unit increase in BMI was associated with significantly lower odds of being categorized as medium or high risk, consistent with Poulia et al. [11] who emphasized BMI’s value in malnutrition screening among chronically ill patients. Elia [2] and Corbelli et al. [11] likewise highlighted the importance of BMI and weight change as practical markers in community-based assessments. In line with this, recent weight loss was also a strong correlate of malnutrition risk, validating MUST’s original conceptual framework [2-9]. Together, these findings reinforce the utility of simple anthropometric indicators in contexts where laboratory-based markers may not be readily available.   Comparison with International Literature Our prevalence estimates align with global studies of HEN patients. Mundi et al. [5] reported malnutrition rates above 60%, and Madrid-Paredes et al. similarly documented undernutrition in 64% of HEN users. Soljan et al. [15] found comparable protein–energy malnutrition rates among long-term HEN patients in Croatia, further highlighting the challenges of sustaining nutritional adequacy despite tube feeding. Collectively, these findings confirm that malnutrition risk is not unique to Saudi Arabia but rather reflects a global challenge in HEN populations.   Duration of HEN and Nutritional Decline We observed a borderline association between longer HEN duration and malnutrition risk, with high-risk patients having a median feeding duration of 20 months (p = 0.072). Although this trend did not reach statistical significance, it may suggest progressive nutritional deterioration during prolonged dependence on enteral feeding. Similar patterns have been described by Silver et al. [16], who noted frequent gastrointestinal complications interrupting feeding in older adults, and by Sabbouh and Torbey [17], who emphasized that inadequate protein and calorie delivery can perpetuate malnutrition despite access to tube feeding. These findings underline the importance of periodic MUST re-screening, individualized regimen adjustments, and proactive multidisciplinary oversight (dietetic, nursing, and medical). Without such measures, nutritional adequacy may deteriorate over time even in patients maintained on HEN.   Feeding Complications and Care-Related Factors Feeding complications were common in our cohort, with aspiration (22.9%), diarrhea (24.3%), and tube blockage (19%) frequently observed. Although these were not statistically associated with MUST categories, their clinical impact cannot be overlooked. Mundi et al. [5] and Wiekmeijer et al. similarly reported these complications as recurring challenges in enteral nutrition. Importantly, the lack of statistical association in our regression may reflect limited power, potential under-reporting, or the complex interplay of multiple care variables. Likewise, caregiver training and frequency of dietitian follow-up were not significant predictors of malnutrition risk. While unexpected, this may be explained by variability in training quality, inconsistent follow-up protocols, or caregiver burden—factors not fully captured in our study. Future research should investigate these dimensions more deeply to clarify their role.   Value of the MUST Tool The current findings reinforce MUST’s utility in HEN contexts. Poulia et al. [11] highlighted its reliability across clinical and community settings, and Cortés-Aguilar et al. [12] affirmed its predictive value in resource-limited environments. Almasaudi et al. [18] further showed that higher MUST scores predict poor clinical outcomes in colorectal cancer, demonstrating the tool’s broad applicability across disease contexts. For Saudi Arabia, where community-based nutritional services are still developing, MUST offers a practical, cost-effective, and evidence-based screening approach.   Strengths and Limitations This study’s strengths include its multicenter design across three cities, rigorous statistical methods (including multinomial logistic regression), and the use of standardized data collection protocols. These features enhance both the generalizability and internal validity of findings.   However, several limitations should be acknowledged. The cross-sectional design precludes causal inference. Reliance on caregiver recall for past weights introduces potential recall bias, although triangulation with medical records mitigated this to some degree. The absence of biochemical markers (e.g., albumin, prealbumin) limited the ability to capture metabolic aspects of malnutrition [19]. Additionally, small subgroup sizes within specific diagnoses restricted statistical power for subgroup comparisons. Finally, the use of a convenience sampling method, while pragmatic, raises the possibility of selection bias.   Implications and Future Directions Our findings reinforce the urgent need for structured, routine nutritional screening among long-term HEN patients. Regular reassessment using simple tools like MUST, combined with individualized dietetic input and caregiver education, can substantially reduce malnutrition risk. Emerging strategies such as tele-nutrition and digital monitoring platforms may provide innovative ways to support continuity of care, particularly in geographically dispersed populations.   Future research should include prospective and interventional studies to test whether structured follow-up, improved training programs, or digital monitoring can mitigate malnutrition risk. Further exploration of socioeconomic disparities and regional variations in access to HEN services would also inform national policy and resource allocation. By addressing these gaps, healthcare systems can strengthen patient outcomes and reduce the burden of malnutrition in this vulnerable population.

This study demonstrates a high prevalence of malnutrition among Saudi adults receiving long-term Home Enteral Nutrition (HEN), with 65.7% classified as high risk according to MUST. BMI and unintentional weight loss were the most consistent predictors of nutritional risk, confirming the value of simple anthropometric indicators for screening in community-based care. Although feeding complications and care-related factors (dietitian follow-up frequency, caregiver training) were not statistically significant predictors, their clinical importance remains noteworthy and warrants further exploration.   Overall, these findings underscore the need for routine nutritional screening using validated tools such as MUST, coupled with individualized feeding plans, structured follow-up, and active caregiver and dietitian involvement. Integrating these practices into HEN services can facilitate earlier detection of malnutrition risk, guide timely interventions, and improve long-term outcomes.   Back Matter Author Contributions All authors contributed equally to the conceptualization, data collection, statistical analysis, interpretation, and manuscript drafting. Both authors reviewed and approved the final version of the manuscript. Funding This research was funded by the Deanship of Scientific Research at Northern Border University, Arar, KSA, under project number NBU-FFR-2025-2975-16.   Ethical Approval and Informed Consent The study protocol received prior approval from the Ethics Committee of Northern Border University, Saudi Arabia, and was conducted in accordance with the Declaration of Helsinki and all applicable ethical standards. Written informed consent was obtained from all participants or their legal guardians prior to data collection. Consent for publication of anonymized clinical data was also obtained and documented. The corresponding author retains the original signed consent forms, which can be made available to the journal’s editorial board upon request.   Data Availability Statement The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request. Due to privacy and ethical restrictions, the raw dataset is not publicly accessible but can be provided in anonymized form for academic and research purposes.   Acknowledgements The authors express their sincere gratitude to the home care teams and medical records departments in Arar, Riyadh, and Dammam for their invaluable assistance in data collection. Special thanks are extended to the caregivers and patients whose participation made this research possible. The authors also acknowledge the significant contributions of clinical dietitians Ms. Hanan Alanazi, Ms. Yasmin Flimpan, Ms. Arwa Barakat, Ms. Jinan Alrashid, and Ms. Samiah Alshehri, whose expertise and support were instrumental to the study’s success.   Conflicts of Interest The authors declare no conflicts of interest related to the conduct or publication of this research.