Abstract
Objective
Appropriate nutrition risk screening (NRS) with timely intervention improves malnutrition outcomes; however, limited knowledge and inconsistent use of validated tools hinder effective implementation. This study assessed knowledge and practice of NRS among nurses and nutritionists/dietitians in three Kenyan national referral hospitals—Kenyatta National Hospital (KNH), Moi Teaching and Referral Hospital (MTRH), and Kisii Teaching and Referral Hospital (KTRH), and established factors influencing implementation of validated nutrition screening tools. A mixed-methods cross-sectional design was used among 349 healthcare professionals through structured questionnaires, complemented by 18 key informant interviews and direct observations. Knowledge and practices related to commonly recommended nutritional screening tools (NRS-2002, MUST, and MST) were evaluated.
Results
A mixed-methods cross-sectional study was conducted among 349 healthcare professionals across Kenyatta National Hospital (KNH), Moi Teaching and Referral Hospital (MTRH), and Kisii Teaching and Referral Hospital (KTRH). Quantitative data were collected using structured questionnaires, complemented by 18 key informant interviews and direct clinical observations. Knowledge and practice of commonly used nutritional screening tools (NRS-2002, MUST, and MST) were assessed. The mean knowledge score was 5.04 ± 1.21 (maximum = 8), with MTRH scoring significantly higher than KNH and KTRH (p < 0.001). High knowledge levels were observed among 44% of respondents at MTRH compared with 14% at KNH and 4% at KTRH. The mean practice score was 6.32 ± 2.23 (maximum = 12), with significant variation across hospitals (p < 0.001). Knowledge level, education, and professional experience significantly predicted screening practice. Routine NRS was rarely conducted and relied mainly on anthropometric or clinical indicators rather than validated screening tools. Qualitative findings revealed barriers including limited training, lack of institutional policies, unclear professional responsibilities, and workforce shortages. Strengthening training, integrating standardized screening protocols, and prioritizing high-risk patient groups may improve NRS implementation in resource-constrained hospital settings. Future research should evaluate the effectiveness of targeted training interventions and institutional policy reforms in improving the implementation of nutrition risk screening in hospital settings.
Supplementary Information
The online version contains supplementary material available at 10.1186/s13104-026-07834-2.
Keywords: Nutrition risk screening, Hospital malnutrition, Healthcare professionals, Screening tools, Kenya
Introduction
Malnutrition is a frequent comorbidity among hospitalized adults, with prevalence estimates ranging from 20 to 70% [1–5]. Despite its high burden, it is often underrecognized in clinical settings, contributing to nutritional deterioration, increased complications, readmissions, prolonged hospital stays, poor clinical outcomes, and rising healthcare costs [6–8]. Inadequate clinician engagement and limited knowledge of nutrition screening tools have been identified as key barriers to effective screening [9, 10].
Nutrition Risk Screening (NRS) is a core component of the nutrition care process, designed to identify patients at risk and triage them for comprehensive assessment [11–14]. According to nutritional screening tools like MUST, MST, and NRS-2002, patients "at risk of" malnutrition are primarily those with low Body Mass Index (BMI), significant unintentional weight loss, reduced appetite, or acute illness leading to decreased food intake. These tools identify patients likely to have or develop poor nutritional status. Screening precedes detailed assessment and ensures timely intervention for those who are malnourished or at risk [12, 15]. Early identification using validated NRS tools, followed by appropriate intervention, is a cost-effective strategy to improve outcomes and reduce healthcare expenditure [16]. Screening outcomes guide action: patients not at risk undergo periodic re-screening, while at-risk individuals receive tailored care plans or referral for advanced evaluation when clinically indicated [17].
Hospital malnutrition remains highly prevalent in Africa, including South Africa, Kenya, and Ghana, where it contributes significantly to morbidity and mortality [18]. However, data on NRS practices in Kenya are scarce, and no prior study has documented the use of validated NRS tools in Kenyan hospitals. This gap is compounded by severe nurse shortages, with marked variability in staffing levels [19]. International guidelines strongly recommend routine NRS for hospitalized patients [13, 17, 20–22], as timely screening and intervention improve physiological stability, reduce complications, enhance recovery, and shorten hospital stays [16, 17]. Nevertheless, compliance with NRS remains low where skills, training, role clarity, protocols, and resources are inadequate [23–25]. Given the limited evidence in Kenya, this study investigated nutrition screening knowledge and practices among nurses and nutritionists in Kenyan National Teaching and Referral Hospitals. This study therefore aimed to assess knowledge and practices related to nutrition risk screening among nurses, nutritionists, and dietitians in Kenyan national referral hospitals, and to identify barriers influencing implementation of validated screening tools.
Materials and methods
Research design
A mixed-methods cross-sectional design was employed, integrating quantitative and qualitative approaches. Quantitative data were collected using structured questionnaires administered to healthcare professionals, while qualitative data were obtained through Key Informant Interviews (KIIs) with nurses, nutritionists and dieticians. This approach enabled triangulation to enhance understanding of Nutrition Risk Screening (NRS) knowledge and practice.
Study setting
The study was conducted in medical and surgical wards of three purposively selected Kenyan National Teaching and Referral Hospitals: Kenyatta National Hospital (KNH), Moi Teaching and Referral Hospital (MTRH), and Kisii Teaching and Referral Hospital (KTRH). These are the only gazetted level six public teaching and referral hospitals in Kenya (excluding the National Spinal Injury Referral Hospital, which manages specialized spinal cases) [26]. As tertiary referral centers and training institutions serving patients nationwide, they provide a representative context for hospital-based practice [27].
Study subjects
Participants included nurses, nutritionists and dietitians actively involved in patient care within the selected hospitals. In Kenya, nutritional screening is typically conducted during patient admission by nursing staff, with nutritionists and dietitians responsible for nutritional assessment and specialized dietary management. It is noteworthy that in Kenya, nutrition and dietetics are typically offered as a combined academic program. Both permanent and locum staff were eligible for inclusion. Student trainees were excluded.
Sample size and sampling techniques
A total of 349 healthcare professionals from Kenyatta National Hospital (KNH), Moi Teaching and Referral Hospital (MTRH), and Kisii Teaching and Referral Hospital (KTRH) participated in the study. Participants included nurses, nutritionists, and dietitians who were actively involved in patient care within medical and surgical wards.
These professional groups were selected because they are directly involved in hospital nutrition care processes. In the Kenyan hospital context, nurses typically conduct initial patient assessments at admission and may identify patients at potential risk of malnutrition, while nutritionists and dietitians are responsible for performing detailed nutritional assessments and providing dietary management and counselling. Therefore, their knowledge and practices are critical for effective implementation of Nutrition Risk Screening (NRS) (Figs. 1, 2, 3, 4, 5).
Fig. 1.
Weight measurement practices of health care professionals
Fig. 2.
Proportion of patients screened for malnutrition risk by health facility
Fig. 3.
Reasons for weighing patients by health facilities
Fig. 4.
Occasions for nutrition risk screening of patients
Fig. 5.
Type of NRS tools used by health facility
The three public National Referral and Teaching Hospitals were purposively selected since they were the only gazetted level 6 public teaching and referral hospitals in Kenya save for National Spinal Injury Referral Hospital, which was not considered in the study because the hospital is a specialized facility that only deals with spinal injury cases. In each hospital, stratified random sampling techniques were used, and males and females in the medical and surgical wards were sampled using stratified random sampling; thereafter, patients were selected through simple random selection using the Table of Random Numbers from the list of patients admitted within the previous 24 h. Patients who consented to participate in the study were enrolled and screened within 24 h of admission on a daily basis until the sample size was attained. A summary of the sampling plan is presented in Fig. 6.
Fig. 6.
Summary of sampling procedure
Summary of sampling procedure
Three data collection tools were used:
A structured questionnaire (appendix 4) adapted from Laur et al. [28] assessing socio-demographic characteristics, knowledge, and practices related to NRS.
An observation checklist (appendix 3) documenting routine screening practices during patient admission and ward care.
A key informant interview guide (appendix 5) exploring institutional practices and barriers to implementation and this was administered after an informed consent is established (appendix 2).
Direct clinical observations were conducted in selected wards to assess whether nutrition risk screening was performed during routine patient care. An observation checklist was used to systematically record key practices related to nutrition screening. The checklist captured information on whether patients were weighed at admission, whether any nutrition risk screening procedures were conducted, and whether screening results were documented in patient records. The observations were carried out during routine ward activities without interfering with clinical care. Data were recorded using the structured observation checklist, and brief field notes were taken to capture contextual information related to screening practices observed in the wards. Direct observations were recorded as field notes during ward rounds and admission processes to document real-time clinical practices related to patient weighing and screening.
Validity and reliability
The questionnaire was pre-tested among 42 nurses, nutritionists and dieticians in the study hospitals to assess clarity and validity, and revisions were made accordingly. Content validity of the questionnaire was assessed through expert review by three academic specialists in nutrition and dietetics from Kenyatta University. The experts evaluated the questionnaire items for relevance, clarity, and comprehensiveness in relation to the study objectives and the measurement of Nutrition Risk Screening (NRS) knowledge and practices. Their feedback informed revisions to improve the wording, structure, and contextual appropriateness of the items for hospital-based healthcare professionals.
Reliability was evaluated using a test–retest method among 42 healthcare professionals at Mbagathi Hospital. The instrument was re-administered after seven days, producing a Cronbach’s correlation coefficient of 0.89, indicating good internal consistency.
Data collection and analysis
Knowledge scores were computed on an 8-point scale and categorized using Bloom’s cut-off points [29]: ≥ 80% (6.4–8) high, 60–79% (4.8–6.3) moderate, and < 60% (< 4.8) low. Practice scores were calculated on a 12-point scale using equivalent thresholds: ≥ 80% (9.6–12) good, 60–79% (7.2–9.5) moderate, and < 60% (< 7.2) poor.
Qualitative data were collected through key informant interviews and direct clinical observations. The interviews were conducted using a semi-structured interview guide and audio-recorded with participants’ consent. In addition, direct observations were carried out in selected wards to document routine practices related to nutrition risk screening during patient admission and ward care. Observational data were recorded as structured field notes using an observation checklist focusing on practices such as patient weighing, use of screening tools, and documentation of nutrition-related information.
All interviews were transcribed verbatim and analysed using Braun and Clarke’s six-phase thematic analysis approach. The transcripts were read repeatedly to achieve familiarization with the data, followed by initial coding and identification of recurring patterns. Codes were then grouped into broader themes representing barriers and facilitators influencing the implementation of Nutrition Risk Screening in the hospitals and analysed thematically using NVivo version 12 Plus (QSR International Pty Ltd).
The principal researcher, a doctoral student in nutrition and dietetics, conducted the interviews and observations. Reflexive notes were maintained throughout the data collection and analysis process to acknowledge the researcher’s positionality and minimize potential bias in interpretation.
Quantitative data were analysed using SPSS version 25.0 (IBM Corp., Armonk, NY, USA). Dependent variables were NRS knowledge and practice levels. Independent variables included profession, years of experience, education level, ward type, hospital, gender, age group, and prior NRS training. Statistical tests included Chi-square, Fisher’s Exact Test, independent-samples t-tests, and one-way ANOVA.
The qualitative component was reported in accordance with elements of the COREQ (Consolidated Criteria for Reporting Qualitative Research) guidelines to enhance transparency and methodological rigor.
Logistical and ethical considerations
Ethical approval was obtained from Kenyatta University (Ref. H87/37116/2017; PKU/2187/I1331), National Commission for Science, Technology and Innovation (NACOSTI) (NACOSTI/P/21/10259), KNH–UoN (P547/07/2021), MTRH (0004112; ELD/MTRH/R&P/10/2/V.2/2010), and KTRH (ISERC/KTRH/002/22). Written informed consent was obtained from all participants. Supporting documentation related to logistical and ethical approvals is provided in Appendices 1, 2, and 8–15. This study was conducted in accordance with the ethical principles of the Declaration of Helsinki (World Medical Association, 2013).
Results
Socio-demographic characteristics
Table 1 summarizes the socio-demographic characteristics of healthcare professionals across the three the hospitals. Respondents were predominantly female, with similar gender distributions across facilities. Most were young to middle-aged adults. The workforce was largely diploma- or certificate-trained, with few postgraduate qualifications. Nurses constituted the majority, followed by nutritionists and dietitians. A substantial proportion had more than five years of experience, particularly at KNH, whereas MTRH had relatively more early-career staff. Overall, the sample reflects a predominantly nursing-based, moderately experienced, diploma-level workforce with comparable demographic patterns across hospitals.
Table 1.
Distribution of the study respondent health care professionals (HCPs) by their socio-demographic characteristics
| Variable | Category | Total N = 349 | KTRH N = 100 | KNH N = 140 | MTRH N = 109 |
|---|---|---|---|---|---|
| n (%) | n (%) | n (%) | n (%) | ||
| Gender |
Male Female |
128 (36.7) 221 (63.3) |
29 (29) 71 (71) |
59 (42.14) 81 (57.86) |
40 (36.7) 69 (63.3) |
| Age category |
18–30 years 31–40 years 41–50 years 51–60 years > 60 years |
139 (39.8) 129 (37) 66 (18.9) 15 (4.3) |
44 (44) 30 (30) 20 (20) 6 (6) |
62 (44.29) 47 (33.57) 24 (17.14) 7 (5) |
33 (30.28) 52 (47.71) 22 (20.18) 2 (1.83) |
| Education |
≥ Masters Degree Diploma ≤ Certificate |
9 (2.6) 127 (36.4) 211 (60.5) 2 (0.6) |
1 (1) 26 (26) 73 (73) 0 (0) |
4 (2.86) 65 (46.43) 71 (50.71) 0 (0) |
4 (3.67) 36 (33.03) 67 (61.47) 2 (1.83) |
| Profession |
Nutritionist & dietitian Nurse Nurse aid Others |
69 (19.8) 249 (71.3) 16 (4.6) 15 (4.3) |
19 (19) 76 (76) 1 (1) 4 (4) |
23 (16.43) 109 (77.86) 2 (1.43) 6 (4.29) |
27 (24.77) 64 (58.72) 13 (11.93) 5 (4.59) |
| Years of practice |
< 1 Year 1–3 Years 3–5 Years > 5 Years |
36 (10.3) 84 (24.1) 74 (21.2) 155 (44.4) |
18 (18) 28 (28) 12 (12) 42 (42) |
5 (3.57) 28 (20) 34 (24.29) 73 (52.14) |
13 (11.93) 28 (25.69) 28 (25.69) 40 (36.7) |
*Others: nurses, nutritionists & dieticians on training
Healthcare professionals’ knowledge and practices on NRS
A total of 349 nurses and nutritionists and dieticians were assessed for NRS knowledge (maximum score = 8) and practice. Table 2 shows inconsistencies in role clarity, routine implementation, and institutionalization of NRS across the three facilities. Most respondents identified nurses, nutritionists and dieticians as primarily responsible for NRS, while doctors and clinical officers were less frequently cited, indicating partial but fragmented multidisciplinary ownership. Although many reported that initiating nutrition within 24 h for at-risk patients was routine, uncertainty and disagreement especially at KNH suggested gaps in timely intervention. Similar inconsistencies were observed regarding routine patient weighing and nutrition risk screening practices as reported by nurses, nutritionists, and dietitians (Figs. 1 and 2). These discrepancies were further compounded by variations in the reasons for weighing patients (Fig. 3), indicating a lack of standardized protocols for nutritional screening across the facilities. While referral of malnourished patients to nutritionists and dieticians was commonly reported, nurse-led management, delayed referral, or lack of referral were also noted. Knowledge gaps were evident in differentiating nutritional assessment from NRS, and documentation practices varied across facilities. Multidisciplinary discussions on malnutrition were reported inconsistently, particularly at KNH, indicating weak institutional coordination. Overall, the findings demonstrate inter-facility variation and persistent gaps in both knowledge and routine NRS practice.
Table 2.
Health care professionals’ (HCPs) knowledge and practices on aspects of nutrition risk screening of patients
| Variable | Category | Total, N = 349 | KTRH, N = 100 | KNH N = 140 | MTRH N = 109 | |
|---|---|---|---|---|---|---|
| n (%) | n (%) | n (%) | n (%) | |||
| 1 | NRS to be conducted by |
Nurses Nutritionists & dieticians Doctors and clinical officers |
182 (52.1) 343 (98.3) 108 (30.9) |
28 (28) 97 (97) 21 (21) |
95 (67.86) 138 (98.57) 44 (31.43) |
59 (54.13) 108 (99.08) 43 (39.45) |
| 2 |
It is routine practice to initiate nutrition regime within 24 h for patients who are classified as nutrition risk |
Not true True Not sure |
14 (4) 246 (70.5) 89 (25.5) |
5 (5) 75 (75) 20 (20) |
8 (5.71) 78 (55.71) 54 (38.57) |
1 (0.92) 93 (85.32) 15 (13.76) |
| 3 | It is mandatory std procedure to weigh patients at regular intervals hospital stay? |
Not mandatory True Not sure |
107 (30.7) 215 (61.6) 27 (7.7) |
28 (28) 63 (63) 9 (9) |
64 (45.72) 65 (46.43) 11 (7.86) |
15 (13.76) 87 (79.82) 7 (6.42) |
| 4 | It is std practice that patients are classified as malnourished. or at risk be |
a) Referred to nutritionist &dietician b) Managed at nurses’ level c) Referred to doctor/COs d) Discuss with family for support d) Not referred for nutritional care |
291 (83.4) 7 (2) 55 (15.8) 8 (2.3) 2 (0.6) |
82 (82) 4 (4) 16 (16) 5 (5) 1 (1) |
112 (80) 1 (0.71) 28 (20) 2 (1.43) 0 (0) |
97 (88.99) 2 (1.83) 11 (10.09) 1 (0.92) 1 (0.92) |
| 5 | Nutritional assessment and NRS differ |
No Yes Do Not Know |
130 (37.2) 120 (34.4) 99 (28.4) |
48 (48) 27 (27) 25 (25) |
19 (13.57) 71 (50.71) 50 (35.71) |
63 (57.8) 22 (20.18) 24 (22.02) |
| 6 |
NRS results and intervention should always be included in patient records |
Not true True Not sure |
78 (22.3) 213 (61) 58 (16.7) |
7 (7) 62 (62) 231 (31) |
64 (45.71) 67 (47.86) 9 (6.42) |
7 (6.42) 84 (77.06) 18 (16.51) |
| 7 | It is standard practice to have regular meetings to discuss hospital malnutrition |
Not true True Not sure |
40 (11.5) 208 (59.6) 101 (29.0) |
14 (14) 74 (74) 12 (12) |
19 (13.57) 42 (30) 79 (56.43) |
7 (6.42) 92 (84.4) 9.18) |
Nutrition risk screening knowledge scores across hospitals
Table 3 presents NRS knowledge levels. Overall, 20.6% of respondents had high knowledge, 44.4% moderate, and 35.0% poor knowledge, indicating substantial gaps. Significant inter-facility differences were observed. MTRH demonstrated the strongest knowledge profile, with 44.0% high knowledge and 19.3% poor knowledge. In contrast, KNH recorded 40.7% poor and 14.3% high knowledge, while KTRH had 44.0% poor and only 4.0% high knowledge. Pairwise comparisons confirmed statistically significant differences:
MTRH vs KNH (χ.2 = 30.46, df = 2, p < 0.001)
MTRH vs KTRH (χ.2 = 47.34, df = 2, p < 0.001)
KNH vs KTRH (χ.2 = 6.91, df = 2, p = 0.031)
Table 3.
Knowledge scores across hospitals and pairwise comparisons based on bloom’s cut-off
| Facility | Poor (< 4.8) | Medium (4.8–6.3) | High (≥ 6.4) | Total (n) |
|---|---|---|---|---|
| MTRH | 21 (19.3%) | 40 (36.7%) | 48 (44.0%) | 109 |
| KNH | 57 (40.7%) | 63 (45.0%) | 20 (14.3%) | 140 |
| KTRH | 44 (44.0%) | 52 (52.0%) | 4 (4.0%) | 100 |
| Overall | 122 (35.0%) | 155 (44.4%) | 72 (20.6%) | 349 |
| Pairwise comparison of knowledge scores across facilities | ||||
|---|---|---|---|---|
| Comparison | χ2 | df | p-value | Interpretation |
| MTRH vs KNH | 30.46 | 2 | < 0.001 | Highly significant |
| MTRH vs KTRH | 47.34 | 2 | < 0.001 | Highly significant |
| KNH vs KTRH | 6.91 | 2 | 0.031 | Significant |
Knowledge scores were categorized using Bloom’s cut-off points, where scores of ≥ 80% of the maximum (≥ 6.4) were classified as high, 60–79% (4.8–6.3) as moderate, and < 60% (< 4.8) as poor knowledge [30]. 1 Chi-square test of independence was used to assess the association between facility and knowledge level
These findings highlight institutional disparities in NRS knowledge, with MTRH consistently outperforming the other facilities.
Nutrition screening practice scores across hospitals
Marked variations in nutrition risk screening practices were observed across the health facilities (Fig. 2). These variations were further compounded by inconsistencies among nurses, nutritionists, and dietitians regarding the timing and occasions on which nutrition risk screening was conducted for patients (Fig. 4). Table 4 summarizes NRS practice scores using Bloom’s criteria. Overall practice was low: 53.3% poor, 45.6% moderate, and only 1.1% high practice. KNH recorded the highest proportion of poor practice (72.1%), compared with MTRH (40.4%) and KTRH (41.0%). High practice scores were rare and observed only at MTRH (3.7%). A global association test showed significant variation by hospital (χ2, p < 0.001). Pairwise comparisons indicated significantly poorer practice at KNH compared with MTRH (χ2 = 34.21, df = 2, p < 0.001) and KTRH (χ2 = 28.34, df = 2, p < 0.001). No significant difference was found between MTRH and KTRH (χ2 = 0.72, df = 2, p = 0.698). Overall, KNH demonstrated consistently poorer practice outcomes, while MTRH and KTRH showed comparable performance (Table 5).
Table 4.
Practice scores (Mean ± SD) across hospitals and pairwise comparisons based on bloom’s cut-off
| Facility | Poor (< 7) | Medium (7–9) | High (≥ 10) | Total (n) |
|---|---|---|---|---|
| MTRH | 44 (40.4%) | 61 (56.0%) | 4 (3.7%) | 109 |
| KNH | 101 (72.1%) | 39 (27.9%) | 0 (0.0%) | 140 |
| KTRH | 41 (41.0%) | 59 (59.0%) | 0 (0.0%) | 100 |
| Overall | 186 (53.3%) | 159 (45.6%) | 4 (1.1%) | 349 |
| Pairwise comparison of practice scores across facilities | ||||
|---|---|---|---|---|
| Comparison | χ2 | df | p-value | Interpretation |
| MTRH vs KNH | 34.21 | 2 | < 0.001 | Significant difference: KNH has a much higher proportion of poor practice (72.1%) compared to MTRH (40.4%) |
| MTRH vs KTRH | 0.72 | 2 | 0.698 | Not significant: Similar distribution of practice scores between MTRH and KTRH |
| KNH vs KTRH | 28.34 | 2 | < 0.001 | Significant difference: KNH shows considerably poorer practice than KTRH, with higher poor practice scores |
Practice scores were categorized using Bloom’s cut-off criteria: scores ≥ 10 were classified as high, 7–9 as moderate, and < 7 as poor practice [30]. 1Fisher’s Exact Test was used due to establish significant difference.
*p-value calculated using one-way ANOVA comparing practice scores across MTRH, KNH, and KTRH.
Fisher’s Exact Test showed a significant difference in practice level distribution across facilities (p < 0.001)
Table 5.
Predictors of NRS practices among health care professionals in the three health facilities
| Predictor (IV) | MTRH (p-value) | KNH (p-value) | KTRH (p-value) | Summary of Effect |
|---|---|---|---|---|
| Age | 0.056 | 0.066 | 0.219 | Not significant in any hospital |
| Profession | 0.051 | 0.019* | 0.640 | Significant only at KNH |
| Gender | 0.557 | 0.822 | 0.112 | Not significant |
| Education Level | 0.691 | < 0.001* | 0.835 | Significant only at KNH |
| NRS Knowledge | < 0.001* | < 0.001* | < 0.001* | Strong predictor across all hospitals |
| Experience (Years) | 0.003* | 0.001* | 0.189 | Significant at MTRH and KNH; not at KTRH |
Healthcare professionals’ NRS practices
Practices varied considerably across hospitals. Slightly over half of respondents reported consistently weighing patients, with highest adherence at KTRH and lowest at KNH (Fig. 1). Weight estimation rather than direct measurement was more common at MTRH. Although many respondents weighed patients at admission or during hospitalization, only about one-quarter reported screening all patients for malnutrition. Weighing was primarily done for medication dosing rather than NRS. Many respondents conflated nutritional assessment with screening. Most nurses and nutritionists and dieticians assessed anthropometric measures and appetite loss but did not apply validated NRS tools. Nutrition Risk Screening was more commonly conducted during hospital stay rather than at admission, and some staff reported not conducting NRS at all with BMI confused as a NRS tool. BMI was the most frequently used measure, often replacing validated tools such as NRS-2002, MST or MUST (Fig. 5). KNH relied almost exclusively on BMI, while MTRH showed relatively greater but still limited use of validated instruments.
Availability and use of NRS tools
Table 6 indicates that none of the hospitals reported using standardized NRS tools (NRS-2002, MUST, MST). All responses fell under “Not applicable,” confirming complete absence of validated screening tools across facilities.
Table 6.
Availability and use of nutrition risk screening tools in the Kenyan referral hospitals
| KNH (N = 82) |
KTRH (N = 41) |
MTRH (N = 46) |
||
|---|---|---|---|---|
| NRS conducted |
No yes |
82 0 |
41 0 |
46 0 |
| The NRS tool used |
NRS 2002 MUST MST other Not applicable |
0 0 0 0 82 |
0 0 0 0 41 |
0 0 0 0 46 |
| Availability of NRS tool |
Shown Not shown |
0 82 |
0 41 |
0 46 |
Predictors of NRS knowledge and practice
Regression analyses examined associations between demographic/professional factors and NRS practice. Variables included age, sex, profession, education level, years of experience, and NRS knowledge. NRS knowledge, education level, and professional experience were significant predictors. At MTRH, knowledge and experience predicted practice (p < 0.001). At KNH, knowledge, education, and experience were significant (p < 0.001). At KTRH, knowledge alone predicted practice (p < 0.001). These findings emphasize the central role of knowledge in shaping screening behaviour.
Qualitative findings from key informant interviews
Eighteen Key Informant Interviews (KIIs) were conducted with senior nurses, nutritionists, and hospital administrators to explore institutional practices, perceptions, and barriers related to Nutrition Risk Screening (NRS). Thematic analysis identified several interconnected themes: the perceived burden of hospital malnutrition, absence of structured nutrition governance systems, limited institutionalization of NRS, policy gaps, limited awareness and use of validated screening tools, and systemic barriers affecting implementation.
Thematic analysis followed the six-step framework described by Braun and Clarke, involving familiarization with the data, generation of initial codes, development of themes, review of themes, definition of themes, and final reporting.
Summary of Qualitative Findings:
Prevalence and importance of malnutrition: Malnutrition is a prevalent issue in Kenyan hospitals, significantly affecting clinical outcomes and prolonging hospital stay.
Lack of Multidisciplinary Teams and Structured Support: Most hospitals lack a structured multidisciplinary team for nutritional support, resulting in fragmented care.
Absence of Standard NRS Practices and Policies: NRS is not a standard practice, and there are no policies or guidelines mandating its implementation.
Underutilization of Validated Screening Tools: Validated nutritional screening tools are not commonly used, with body mass index (BMI) being the primary method for nutritional evaluation.
Educational Gaps and Training Needs: There is critical need to incorporate NRS into educational curricula and provide continuous training for healthcare providers.
Systemic and Workforce Challenges: Addressing systemic issues, including the limited workforce and perception of NRS responsibilities, is essential for improving NRS practices.
Eighteen KII’s explored NRS practices and influencing factors.
Malnutrition Burden: All informants acknowledged that adult hospital malnutrition is common and associated with poor outcomes, prolonged stays, and increased mortality.
Multidisciplinary Support: Eighty-nine percent reported absence of structured nutrition support teams. Malnutrition management was described as fragmented and often viewed as the nutritionist’s and dietician’s responsibility.
NRS as Routine Practice: Participants unanimously stated that NRS is not routinely performed. While nutritional assessments occur, validated NRS tools are unfamiliar and unused.
Policies and Guidelines: All informants confirmed absence of institutional or national policies mandating NRS at admission.
- Use of Validated Tools: Validated tools were not used. BMI was commonly employed for assessment, and NRS was not integrated into practice despite curricular exposure to nutrition assessment.
- Key Challenges
- Limited knowledge and skills in NRS
- Absence of clear protocols
- Inadequate staffing, especially nutritionists and dieticians
- Perception that screening is solely the nutritionist’s and dietician’s role
Summary of Mixed-Methods Integration.
| Quantitative findings | Qualitative evidence | Integrated interpretation |
|---|---|---|
| Moderate or poor NRS knowledge among majority of staff | Informants reported limited exposure to NRS during training | Knowledge gaps contribute to poor screening implementation |
| No hospital used validated screening tools | Participants reported unfamiliarity with screening tools | Tool availability and training barriers limit use |
| Poor screening practices across facilities | Staff cited heavy workloads and unclear responsibilities | Structural and institutional barriers affect screening |
| Knowledge strongly predicted practice | Informants reported low confidence in screening skills | Training may significantly improve screening practice |
Discussion
This study reveals substantial gaps in both knowledge and implementation of Nutrition Risk Screening (NRS) among nurses and nutritionists and dieticians in Kenya’s national referral hospitals. Although most healthcare professionals recognized the importance of early malnutrition detection, NRS was rarely performed. When undertaken, practitioners relied primarily on BMI, weight loss, appetite changes, or general clinical indicators rather than validated screening tools, reflecting confusion between nutrition screening and assessment. Similar competence gaps and low confidence in applying validated tools have been widely reported internationally [31–35].
Across facilities, NRS knowledge consistently predicted screening practice. At KNH and MTRH, additional factors ncluding professional experience, education level, age, and role were also significant, aligning with prior evidence [36]. Key Informant Interviews corroborated these findings, highlighting limited exposure to NRS in pre-service training, lack of mentorship, low confidence in using validated tools, and persistent perceptions particularly among nurses that screening is solely a nutritionist’s and dietician’s responsibility. Similar knowledge and practice gaps have been documented elsewhere [37–39].
MTRH consistently demonstrated stronger NRS performance compared to KNH and KTRH. This may reflect institutional advantages, including structured in-service training, academic partnerships with Moi University, and stronger clinical governance. Evidence shows that regular training, adequate resources, and integration of malnutrition assessment into routine care improve NRS implementation [40]. In contrast, KNH and KTRH showed weaker integration of NRS into workflows, limited training opportunities, and less consistent managerial emphasis on nutrition services. Comparable knowledge and attitudinal barriers have been widely reported [23, 41–43].
Notably, none of the hospitals used validated NRS tools (NRS-2002, MUST, MST). This mirrors international evidence that screening remains inconsistent due to limited tool availability, weak protocol enforcement, and insufficient clinician familiarity [44–49]. Similarly, a Brazilian study found that fewer than 20% of malnourished inpatients had documentation in medical records, underscoring global underdiagnosis where systematic screening is absent [50].
Workforce shortages emerged as a major barrier. Limited numbers of nutritionists, dieticians and high nurse-to-patient ratios constrained routine screening. Similar staffing limitations have been linked to poor NRS uptake elsewhere [51–54]. Competing clinical demands and perceptions of NRS as non-urgent further reduced adherence, consistent with findings that heavy workloads, unclear responsibilities, and low perceived relevance impede screening [23, 25].
Institutional barriers were equally prominent. None of the hospitals had formal NRS policies or standardized screening pathways. The absence of clear directives diminishes accountability and results in fragmented nutritional care [55–57]. Without leadership endorsement, malnutrition screening remains deprioritized despite its clinical significance [44, 48].
Educational gaps also contributed significantly. Kenyan nursing and nutrition curricula inadequately address NRS, echoing findings from Tanzania and Kenya linking insufficient nutrition education to poor screening practice [24, 58]. Comparable shortcomings have been reported globally, where strengthening nutrition education improves screening behaviours [41].
Key informants further identified systemic constraints, including absence of multidisciplinary nutrition support teams, unclear screening expectations, delayed dietetic follow-up, and lack of routine audits or quality improvement mechanisms. Similar systemic weaknesses have been associated with poor NRS compliance and persistent underdiagnosis internationally [40, 59, 60].
Overall, these findings reinforce extensive global evidence that knowledge deficits, staffing shortages, unclear role delineation, policy gaps, and weak institutional support collectively hinder effective NRS implementation. Addressing these challenges requires a coordinated strategy: embedding NRS within national and hospital policies; strengthening pre-service and in-service training; ensuring availability of validated tools; clarifying professional responsibilities; and establishing multidisciplinary nutrition pathways. Structured nutrition training has been shown to improve health workers’ competence and quality of care [61]. Strengthening these systems is essential to improve NRS uptake, enable early malnutrition detection, and enhance patient outcomes [62].
Study limitaion
This study has several limitations. First, its cross-sectional design limits the ability to establish causal relationships between knowledge and practice of Nutrition Risk Screening (NRS). Secondly, data on knowledge and practice were largely self-reported, which may be subject to recall bias and social desirability bias, potentially leading to overestimation of compliance with recommended practices. Although direct observations were conducted to complement questionnaire findings, these were limited to selected wards and time points and may not fully reflect routine practice. Thirdly, the study was conducted in three national teaching and referral hospitals, which may limit generalizability to lower-level facilities, private hospitals, or rural health settings in Kenya. Fourthly, despite the near-census sampling approach, non-response or absence of some eligible staff during data collection may have introduced selection bias.
Finally, while qualitative interviews reached data saturation, perspectives were obtained primarily from senior staff, and the views of junior healthcare workers may not have been fully captured. These limitations should be considered when interpreting the findings.
Conclusion
This study demonstrates that Nutrition Risk Screening (NRS) knowledge and practice remain substantially inadequate across Kenya’s national referral hospitals. Although healthcare professionals recognize the importance of early malnutrition detection, routine screening is inconsistently performed and rarely utilizes validated tools. Knowledge was the strongest and most consistent predictor of practice, while education level and professional experience influenced implementation in some facilities. The complete absence of standardized NRS tools, combined with workforce shortages, unclear role delineation, limited training exposure, and lack of institutional policies, has resulted in fragmented and suboptimal nutrition care.
Marked inter-facility differences highlight the influence of institutional factors such as training opportunities, leadership support, and governance structures. Strengthening NRS implementation therefore requires a coordinated, system-level response. Embedding NRS within national and hospital policies, integrating validated tools into routine admission procedures, clarifying professional responsibilities, and investing in structured pre-service and in-service training are essential steps. Establishing multidisciplinary nutrition support mechanisms and routine quality monitoring processes will further enhance accountability and sustainability.
Improving these structural, educational, and policy foundations is critical to ensure early identification of malnutrition, timely intervention, and improved patient outcomes in Kenyan hospital settings.
Future research should evaluate the effectiveness of targeted training interventions and institutional policy reforms aimed at improving nutrition risk screening in hospital settings. Implementation studies examining structured screening programs in high-risk clinical units such as oncology, surgical, and gastrointestinal wards may provide valuable insights into scalable strategies for resource-constrained healthcare systems.
Supplementary Information
Acknowledgements
I extend my heartfelt gratitude to my wife for her professional guidance and valuable advice during the preparation of this manuscript. I also sincerely appreciate Dr. Raymond Musyoka for his expert support in data analysis and his invaluable contribution to this study.
Abbreviations
- BMI
Body Mass Index
- KNH
Kenyatta National Hospital
- KTRH
Kisii Teaching and Referral Hospital
- MST
Malnutrition Screening Tool
- MTRH
Moi teaching and Referral Hospital
- MUST
Malnutrition Universal Screening Tool
- NRS
Nutrition Risk Screening
- NRS-2002
Nutrition Risk Screening tool- 2002
Author contributions
Mahat Jimale Mohamed contributed to the conceptualization and design of the study, conducted data collection, and led the data analysis and manuscript preparation. Prof. Sophie Ochola (S. Ochola) was involved in the conceptualization and design of the study, as well as data analysis, interpretation, review, and manuscript preparation. All authors have reviewed and approved the final manuscript.
Funding
The authors declare that no financial support was received for the conduct of this study. The study was self-funded.
Data availability
No datasets were generated or analysed during the current study.
Declarations
Ethics approval and consent to participate
Ethical approval was issued by KUERC vide approval. no. PKU/2187/I1331, and KNH-UON ERC Research proposal approval vide ref. no. P547/07/2021, and the MTRH Institutional Research Ethics Committee (IREC) approval vide Ref. no. 0004112. The authority to conduct the research was in accordance with the respective ERC committees of KNH-UON (P547/07/2021), MTRH (ELD/MTRH/R&P/10/2/V.2/2010), and KTRH (ISERC/KTRH/002/22). The Study participants were enrolled upon obtaining their informed consent, and strict confidentiality of the data was upheld (refer to supplementary materials—appendices). Note: There were no procedures performed in studies involving human participants.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Chávez-Tostado M, Cervantes-Guevara G, López-Alvarado SE, et al. Comparison of nutritional screening tools to assess nutritional risk and predict clinical outcomes in Mexican patients with digestive diseases. BMC Gastroenterol. 2020;20(1):79. 10.1186/s12876-020-01214-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Khalatbari-Soltani S, Marques-Vidal P. Impact of nutritional risk screening in hospitalized patients on management, outcome and costs: a retrospective study. Clin Nutr (Edinburgh, Scotland). 2016;35(6):1340–6. 10.1016/j.clnu.2016.02.012. [DOI] [PubMed] [Google Scholar]
- 3.Leij-Halfwerk S, Verwijs MH, van Houdt S, et al. Prevalence of protein-energy malnutrition risk in European older adults in community, residential, and hospital settings: systematic review and meta-analysis. Maturitas. 2019;126:80–9. 10.1016/j.maturitas.2019.05.006. [DOI] [PubMed] [Google Scholar]
- 4.Liu G, Zhang S, Mao Z, Wang W, Hu H. Clinical significance of nutritional risk screening for older adult patients with COVID-19. Eur J Clin Nutr. 2020;74(6):876–83. 10.1038/s41430-020-0659-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Trollebø MA, Skeie E, Revheim I, et al. Comparison of nutritional risk screening with NRS2002 and the GLIM diagnostic criteria for malnutrition in hospitalized patients. Sci Rep. 2022;12(1):19743. 10.1038/s41598-022-23878-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Ahmed T, Haboubi N. Assessment and management of nutrition in older people and its importance to health. Clin Interv Aging. 2010;5:207–16. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Omidvari AH, Vali Y, Murray SM, Wonderling D, Rashidian A. Nutritional screening for improving professional practice for patient outcomes in hospital and primary care settings. Cochrane Database Syst Rev. 2013;2013(6):CD005539. 10.1002/14651858.CD005539.pub2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Watterson C, Fraser A, Banks M, Isenring E, Miller M, Silvester C, et al. Evidence based practice guidelines for the nutritional management of malnutrition in adult patients across the continuum of care. Nutr Diet. 2009;66(Suppl 3):S1–34. 10.1111/j.1747-0080.2009.01383.x. [Google Scholar]
- 9.Mowe M, Bosaeus I, Rasmussen HH, Kondrup J, Unosson M, Rothenberg E, et al. Insufficient nutritional knowledge among health care workers? Clin Nutr. 2008;27(2):196–202. 10.1016/j.clnu.2007.10.014. [DOI] [PubMed] [Google Scholar]
- 10.Patel V, Romano M, Corkins MR, et al. Nutrition screening and assessment in hospitalized patients: a survey of current practice in the United States. Nutr Clin Pract. 2014;29(4):483–90. 10.1177/0884533614535446. [DOI] [PubMed] [Google Scholar]
- 11.Barker LA, Gout BS, Crowe TC. Hospital malnutrition: prevalence, identification and impact on patients and the healthcare system. Int J Environ Res Public Health. 2011;8(2):514–27. 10.3390/ijerph8020514. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Cederholm T, Barazzoni R, Austin P, et al. ESPEN guidelines on definitions and terminology of clinical nutrition. Clin Nutr. 2016;36(1):1–16. 10.1016/j.clnu.2016.09.004. [DOI] [PubMed] [Google Scholar]
- 13.Mueller C, Compher C, Ellen DM, A.S.P.E.N. Board of Directors. A.S.P.E.N. clinical guidelines: nutrition screening, assessment, and intervention in adults. JPEN J Parenter Enteral Nutr. 2011;35(1):16–24. 10.1177/0148607110389335. [DOI] [PubMed] [Google Scholar]
- 14.Young AM, Kidston S, Banks MD, Mudge AM, Isenring EA. Malnutrition screening tools: comparison against two validated nutrition assessment methods in older medical inpatients. Nutrition. 2013;29(1):101–6. 10.1016/j.nut.2012.04.007. [DOI] [PubMed] [Google Scholar]
- 15.Skipper A, Ferguson M, Thompson K, Castellanos VH, Porcari J. Nutrition screening tools: an analysis of the evidence. JPEN J Parenter Enteral Nutr. 2012;36(3):292–8. 10.1177/0148607111414023. [DOI] [PubMed] [Google Scholar]
- 16.Kirkland LL, Shaughnessy E. Recognition and prevention of nosocomial malnutrition: a review and a call to action! Am J Med. 2017;130(12):1345–50. 10.1016/j.amjmed.2017.07.034. [DOI] [PubMed] [Google Scholar]
- 17.Kondrup J, Rasmussen HH, Hamberg O, Stanga Z, Ad Hoc ESPEN Working Group. Nutritional risk screening (NRS 2002): a new method based on an analysis of controlled clinical trials. Clin Nutr. 2003;22(3):321–36. 10.1016/S0261-5614(02)00214-5. [DOI] [PubMed] [Google Scholar]
- 18.Blaauw R, Achar E, Dolman RC, Harbron J, Moens M, Munyi F, et al. The problem of hospital malnutrition in the African continent. Nutrients. 2019;11(9):2028. 10.3390/nu11092028. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Wakaba M, Mbindyo P, Ochieng J, et al. The public sector nursing workforce in Kenya: a county-level analysis. Hum Resour Health. 2014;12:6. 10.1186/1478-4491-12-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Beck AM, Balknas UN, Furst P, Hasunen K, Jones L, Keller U, et al. Food and nutritional care in hospitals: how to prevent undernutrition—report and guidelines from the Council of Europe. Clin Nutr. 2001;20(5):455–60. 10.1054/clnu.2001.0494. [DOI] [PubMed] [Google Scholar]
- 21.Elia M, Stratton RJ, Russell C, Green C, Pang F. Malnutrition in the UK: policies to address malnutrition in the community. BAPEN; 2019. [DOI] [PubMed]
- 22.National Institute for Health and Clinical Excellence (NICE). Nutrition support in adults: oral nutrition support, enteral tube feeding, and parenteral nutrition. Clinical guideline 32. 2006. Available from: http://www.nice.org.uk/guidance/CG32/guidance/pdf/English. [PubMed]
- 23.Porter J, Raja R, Cant R, Aroni R. Exploring issues influencing the use of the Malnutrition Universal Screening Tool by nurses in two Australian hospitals. J Hum Nutr Diet. 2009;22(3):203–9. 10.1111/j.1365-277X.2008.00932.x. [DOI] [PubMed] [Google Scholar]
- 24.Munuo AE, Mugendi BW, Kisanga OA, Otieno GO. Nutrition knowledge, attitudes, and practices among healthcare workers in the management of chronic kidney diseases in selected hospitals in Dar es Salaam, Tanzania: A cross-sectional study. BMC Nutr. 2016;2:6. 10.1186/s40795-016-0045-y [Google Scholar]
- 25.Lindorff-Larsen K, Rasmussen HH, Kondrup J, Staun M, Ladefoged K. Management and perception of hospital undernutrition: A positive change among Danish doctors and nurses. Clin Nutr. 2007;26(3):371–8. 10.1016/j.clnu.2007.01.006 [DOI] [PubMed]
- 26.Ministry of Health, Kenya. (n.d.). Kenya Master Health Facility List: Facility Profile. https://kmhfl.health.go.ke/public/facilities/62f9bb7b-7cd2-4bb9-98c9-b40edc692a81.
- 27.Ministry of Health Kenya. Classification of health facilities in Kenya: levels 1–6. Kenya Gaz Suppl. 2018;CXX(45):124–8. [Google Scholar]
- 28.Laur C, Marcus H, Ray S, Keller H. Quality nutrition care: measuring hospital staff’s knowledge, attitudes, and practices. Healthcare Basel. 2016;4(4):79. 10.3390/healthcare4040079. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Odei Obeng-Amoako GA, Bennett J, Sinclair M, et al. Nutrition knowledge, attitudes, and practices of health workers in Ghana: applying Bloom’s cut-off points for KAP assessment. BMC Health Serv Res. 2021;21:1–10. 10.1186/s12913-021-06139-9.33388053 [Google Scholar]
- 30.Odetola TD. Knowledge, attitude and practice of nurses towards the prevention of pressure ulcers in selected secondary health facilities in Ogun State. Int J Nurs Midwifery. 2015;7(4):54–60. [Google Scholar]
- 31.Domènech Pérez M, Soriano JM, Merino-Torres JF. Development, validation and implementation of a program to detect malnutrition with NRS-2002 screening tool in patients from an onco-hematology service. Nutr Clín Diet Hosp. 2021;41(1):76–82. 10.12873/411SORIANO. [Google Scholar]
- 32.Hestevik CH, Molin M, Debesay J, Bergland A, Bye A. Healthcare professionals’ experiences of providing individualized nutritional care for older people in hospital and home care: a qualitative study. BMC Geriatr. 2019;19(1):317. 10.1186/s12877-019-1339-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Tangvik RJ, Guttormsen AB, Tell GS, Ranhoff AH. Implementation of nutritional guidelines in a university hospital monitored by repeated point prevalence surveys. Eur J Clin Nutr. 2012;66(3):388–93. 10.1038/ejcn.2011.149. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Watkinson-Powell A, Barnes S, Lovatt M, Wasielewska A, Drummond B. Food provision for older people receiving home care from the perspectives of home-care workers. Health Soc Care Community. 2014;22(5):553–60. 10.1111/hsc.12117. [DOI] [PubMed] [Google Scholar]
- 35.Bonetti L, Bagnasco A, Aleo G, Sasso L. ‘The transit of the food trolley’—malnutrition in older people and nurses’ perception of the problem. Scand J Caring Sci. 2013;27(2):440–8. 10.1111/j.1471-6712.2012.01043.x. [DOI] [PubMed] [Google Scholar]
- 36.Laur C, Valaitis R, Bell J, Keller H. Changing nutrition care practices in hospital: a thematic analysis of hospital staff perspectives. BMC Health Serv Res. 2017;17(1):498. 10.1186/s12913-017-2409-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Lepre B, Trigueiro H, Johnsen JT, Khalid AA, Ball L, Ray S. Global architecture for the nutrition training of health professionals: a scoping review and blueprint for next steps. BMJ Nutr Prev Health. 2022;5(1):106–17. 10.1136/bmjnph-2021-000354. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Lu P, Zhang Y, Zhang J. Influencing factors on nutritional knowledge, attitudes, and practices among nursing assistants in Shanghai. BMC Nurs. 2024;23(1):1–9. 10.1186/s12912-024-02553-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Cheng I, Rommel N, Duchac S, Regan J, Speyer R, Dziewas R. Understanding health care professionals’ knowledge and practice regarding malnutrition and dysphagia: insights from targeted education to address malnutrition and swallowing disorders (TEAMS) international survey. Nutrition. 2025;139:112858. 10.1016/j.nut.2025.112858. [DOI] [PubMed] [Google Scholar]
- 40.Moti BK, Atomsa GE, Tesso DW. Professionals’ perception on nutritional care of adult patients in comprehensive specialized hospitals of East Wollega Zone, Ethiopia. BMC Nutr. 2025;11:25. 10.1186/s40795-025-01000-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Shakhshir M, Alkaiyat A. Healthcare providers’ knowledge, attitude, and practice on quality of nutrition care in hospitals from a developing country: a multicenter experience. J Health Popul Nutr. 2023;42(1):15. 10.1186/s41043-023-00355-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Wocial B, Debiński W, Jabłońska-Skwicińska E, et al. Zawartość sodu w krwinkach czerwonych u chorych z nadciśnieniem tętniczym i u osób zdrowych [Sodium content of erythrocytes in patients with arterial hypertension and in healthy persons]. Pol Arch Med Wewn. 1984;72(4):167–74. [PubMed] [Google Scholar]
- 43.Kumbiley J, Amalba A, Aryee PA, Azure SA, Mogre V. Determinants of nutrition care practice by midwives and nurses in the antenatal and postnatal care settings: a multi-site cross-sectional survey from Ghana. Glob Pediatr Health. 2021;8:2333794X211048382. 10.1177/2333794X211048382. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Kondrup J, Johansen N, Plum LM, Bak L, Larsen IH, Martinsen A, et al. Incidence of nutritional risk and causes of inadequate nutritional care in hospitals. Clin Nutr. 2002;21(6):461–8. [DOI] [PubMed] [Google Scholar]
- 45.McWhirter JP, Pennington CR. Incidence and recognition of malnutrition in hospital. BMJ. 1994;308(6934):945–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Mowe M, Bosaeus I, Rasmussen HH, Kondrup J, Unosson M, Irtun Ø. Nutritional routines and attitudes among doctors and nurses in Scandinavia: a questionnaire-based survey. Clin Nutr. 2006;25(3):524–32. 10.1016/j.clnu.2005.11.011. [DOI] [PubMed] [Google Scholar]
- 47.Powell-Tuck JG, Connelly J, Haboubi H, et al. OC-076: Assessing knowledge of recognition and treatment of malnutrition among healthcare professionals. Gut. 2012;61(suppl 2):A33. 10.1136/gutjnl-2012-302514c.76. [Google Scholar]
- 48.Schindler K, Pernicka E, Laviano A, Howard P, Schütz T, Bauer P, et al. How nutritional risk is assessed and managed in European hospitals: findings from nutritionDay survey. Clin Nutr. 2010;29(5):552–9. 10.1016/j.clnu.2010.04.001. [DOI] [PubMed] [Google Scholar]
- 49.Yalcin N, Cihan A, Gundogdu H, Ocakci A. Nutrition knowledge level of nurses. Health Sci J. 2013;7(1): 99–108.
- 50.Pasquini TA, Neder HD, Araújo-Junqueira L, De-Souza DA. Clinical outcome of protein-energy malnourished patients in a Brazilian university hospital. Braz J Med Biol Res. 2012;45(12):1301–7. 10.1590/1414-431X20122586. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Kirkland LL, Kashiwagi D, Brantley S, Scheurer D, Varkey P. Nutrition in hospitalized patients. J Hosp Med. 2013;8(1):52–8. 10.1002/jhm.1969. [DOI] [PubMed] [Google Scholar]
- 52.Skipper A, Young M, Rotman N, Nagl H. Physicians’ implementation of dietitians’ recommendations: a study of the effectiveness of dietitians. J Am Diet Assoc. 1994;94(1):45–9. [DOI] [PubMed] [Google Scholar]
- 53.Somanchi M, Tao X, Mullin GE. The facilitated early enteral and dietary management effectiveness trial in hospitalized patients with malnutrition. JPEN J Parenter Enteral Nutr. 2011;35(2):209–16. 10.1177/0148607110392234. [DOI] [PubMed] [Google Scholar]
- 54.Tappenden KA, Quatrara B, Parkhurst ML, Lamone AM, Fanjiang G, Zeigler TR. Critical role of nutrition in improving quality of care: an interdisciplinary call to action to address hospital malnutrition. JPEN J Parenter Enteral Nutr. 2013;37(4):482–97. 10.1016/j.jand.2013.05.015. [DOI] [PubMed] [Google Scholar]
- 55.Braunschweig C, Gomez S, Sheean PM. Impact of declines in nutritional status on outcomes in adult patients hospitalized for more than 7 days. J Am Diet Assoc. 2000;100(11):1316–24. 10.1016/S0002-8223(00)00373-4. [DOI] [PubMed] [Google Scholar]
- 56.Eide HD, Halvorsen K, Almendingen K 2015. Barriers to nutritional care for the undernourished hospitalized elderly: perspectives of nurses. J Clin Nurs. 2015;24(5–6):696–706. 10.1111/jocn.12562. [DOI] [PMC free article] [PubMed]
- 57.Serón-Arbeloa C, Labarta-Monzón L, Puzo-Foncillas J, et al. Malnutrition Screen Assess Nutrients. 2022;14(12):2392. 10.3390/nu14122392 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58.Kobe JA. Aspects of nutritional knowledge, attitudes, and practices of nurses working in the surgical division at the Kenyatta National Hospital, Kenya. Master’s thesis. University of Stellenbosch; 2006. http://hdl.handle.net/10019.1/1514.
- 59.Taipa-Mendes AM, Amaral TF, Gregório M. Undernutrition risk and nutritional screening implementation in hospitals: barriers and time trends (2019–2020). Clin Nutr ESPEN. 2021;45:192–9. 10.1016/j.clnesp.2021.08.029. [DOI] [PubMed] [Google Scholar]
- 60.Zalina AZ, Amira NMM, Nur ASMN, Aishah ZAA. Knowledge, perception and challenges of implementing nutrition screening: A survey of healthcare professionals. Qeios. 2023. 10.32388/FL7EJJ [Google Scholar]
- 61.Sunguya BF, Poudel KC, Mlunde LB, Urassa DP, Yasuoka J, Jimba M. Nutrition training improves health workers’ nutrition knowledge and competence to manage child undernutrition: a systematic review. Front Public Health. 2013;1:37. 10.3389/fpubh.2013.00037. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 62.Cortés-Aguilar R, Malih N, Abbate M, Fresneda S, Yañez A, Bennasar-Veny M. Validity of nutrition screening tools for risk of malnutrition among hospitalized adult patients: a systematic review and meta-analysis. Clin Nutr. 2024;43(5):1094–116. 10.1016/j.clnu.2024.03.008. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
No datasets were generated or analysed during the current study.