Role of nutritional status in predicting quality of life outcomes in patients with solid malignancies: an experience from a developing country

Abstract

Background

Cancer treatments can affect nutritional status by impairing a person’s ability to consume an adequate amount of food and absorb nutrients, which are important factors in reducing health-related quality of life (HRQoL). Consequently, this research aimed to investigate the correlation between the likelihood of malnutrition and quality of life among individuals with solid cancer in Palestine. In addition, factors that are linked to the HRQoL of these patients should be identified.

Methods

A cross-sectional study was conducted at two major cancer referral hospitals in the northern West Bank, Al-Watani Government Hospital and An-Najah National University Hospital in Nablus, between July 31, 2022, and February 28, 2023. The five-level EuroHRQOL five-dimensional instrument (EQ-5D-5 L) was used to assess HRQOL. Nutritional status was assessed via the Nutrition Risk Screening 2002 (NRS-2002) tool. Multiple linear regression analysis was performed to determine the most important variables related to HRQOL.

Results

A total of 304 patients with solid tumors were included in this study. The most common cancers among these patients were breast (40.5%) and colorectal (26%) cancers. A moderate negative correlation was observed between the EQ-5D-5 L score and the NRS-2002 score (r = − 0.207; 95% CI: − 0.26 to − 0.15; p < 0.001). Regression analysis revealed that working patients (β = 0.152; 95% CI: 0.045 to 0.255; p = 0.005), those with fewer disease-related complications related to dietary intake (β = − 0.311; 95% CI: − 0.415 to − 0.208; p < 0.001), and individuals with lower NRS scores (β = − 0.135; 95% CI: − 0.243 to − 0.027; p = 0.015) were independently associated with higher HRQoL.

Conclusions

Our results suggest that lower nutritional risk, employment, and fewer disease complications are associated with better HRQoL among cancer patients, underscoring the importance of early nutritional assessment and patient-centred care, especially in low-resource settings.

Background

Cancer is a diverse group of diseases that is characterized by unregulated growth and progression of abnormal cells that have the ability to invade adjacent areas and migrate to distant sites in the body [1–3]. Cancers are classified according to their site of origin as either hematologic cancers or solid cancers [4–6]. Solid cancers include those that originate in a particular body part, such as breast cancer, brain cancer, lung cancer, prostate cancer, or liver cancer [6, 7].

Malnutrition is a frequent and severe complication affecting people with cancer [8, 9]. This is because cancer, as well as its treatments, often leads to disruptions in metabolism, loss of appetite, and gastrointestinal problems that make it difficult for a cancer patient to enjoy their meals [10]. Consequently, malnutrition is a factor that is often related to poor responses to treatments because it leads to increased morbidity rates, longer hospitalization periods, and overall lower survival rates [11]. Studies have also indicated that between 30% and 80% of people diagnosed with cancer experience malnutrition, depending on the cancer type and stage [8, 9, 11].

Currently, cancer is a challenge globally when it comes to public health. An estimated 19.3 million new cancer cases and 10 million cancer-related deaths occur in a year, according to GLOBOCAN 2022 [12]. Solid cancers are a challenge because of their high incidence, complexity of care, and costs [13]. Curing such cancers demands a multimodal therapeutic approach such as surgery, chemotherapy, radiation, immunotherapy, and targeted therapy [13, 14]. Unfortunately, such therapies have a tendency to induce suffering in the form of inflammation, nausea, fatigue, and loss of appetite, thereby further deteriorating the nutritional status of a cancer patient [15, 16].

Health-related quality of life (HRQoL) is an important aspect of current cancer therapy. HRQoL is an assessment of how a cancer patient feels physically, mentally, and socially as they cope with cancer [3, 17, 18]. In developing countries such as Palestine, it is more difficult to maintain optimal HRQoL because of a lack of healthcare infrastructure, politically unstable conditions, and a lack of nutritional screening in cancer therapy sessions [19–21].

In Palestine, cancer incidence has been steadily increasing, with a rate of 135.5 per 100,000 in 2023, a 7% increase from 2022 [19, 20]. This increasing trend points to a pressing need for a cancer care strategy that focuses not only on cancer treatment but also on cancer nutrition and psychology. By understanding the relationship between nutrition status and HRQoL, healthcare professionals can work toward more holistic approaches to care and demand that nutrition care become a standard part of caring for cancer patients, regardless of healthcare system constraints. In this context, this study was designed to examine the relationship that exists between nutrition status and HRQoL in Palestinian cancer patients diagnosed with solid cancer.

Methods

Study design

A cross-sectional study design was employed over the periods of July 31, 2022, and February 28, 2023. Standardized and validated assessment tools were used to evaluate patients diagnosed with solid cancer.

Study settings

This research was undertaken on two premises that serve as the principal referral hospitals in the treatment of cancer patients for the entire northern West Bank region: Al-Watani Government Hospital and An-Najah National University Hospital.

Sampling procedure and sampling size calculation

The Raosoft sample size calculator, which is an automated software program accessible at http://www.raosoft.com/samplesize.html, was used to estimate the sample size of this study. Our findings indicate that a minimum effective sample size of 217 is required after a response rate of 50% is selected and that a 5% margin of error within 95% confidence intervals is considered. Ultimately, our study included a cohort of 304 patients derived from diverse hospital settings. Convenience cluster sampling was used to meet our research objective because of the logistical feasibility of recruiting from major oncology centers. Because convenience cluster sampling was used, the degree of selection bias could not be fully eliminated. To mitigate its influence, recruitment was conducted across two referral hospitals serving diverse patient groups. Missing data were minimal (< 2%) and handled via complete-case analysis. Furthermore, to reduce the likelihood of obtaining improper outcomes and improve the study’s reliability, we increased the estimated sample size by an additional 5% to 10%.

The inclusion and exclusion criteria

Patients aged > 18 years, diagnosed with solid cancer and who agreed to participate. The exclusion criteria were patients who were mentally retarded, patients who had multiple types of cancer and patients who were not followed up after discharge.

Data collection instruments

Four sections of a questionnaire were used to evaluate the participants. The first section was designed to obtain demographic data such as age, gender, marital status (married, single, divorced, or widowed), residency (urban, rural, or Palestinian refugee camp), educational level (ranging from illiterate to postgraduate), occupation (working or not working), and monthly income (low, moderate, or high), which was measured as the total monthly income from all sources, including employment, pensions, government aid, and support from relatives, in addition to weight and height, to calculate the body mass index (BMI, kg/m²).

The second section focused on the clinical characteristics of the study population, such as the presence of comorbidities, type of cancer, cancer duration, type of treatment that the patients had followed and some laboratory tests.

The third part covers the application of NRS-2002 in identifying cancer patients at risk of malnutrition and in need of early nutritional interventions. NRS-2002 was developed by Kondrup et al. [22] NRS-2002 is a widely recommended and validated malnutrition screening system. Though Patient-Generated Subjective Global Assessment (PG-SGA) is widely favored because of its cancer-specific analysis criteria, NRS-2002 is preferred in this study because of its ease of use, speed, proven validity in varied clinical settings, and applicability in inpatient as well as outpatient facilities, most so in those that lack resources [22]. Its ease of use enables it to be integrated within a system in a manner that allows it to be implemented within a limited timeframe so that it can be applied by authorized personnel.

The NRS-2002 also estimates nutritional risk through two key domains, which include nutrition status and disease severity. Both domains have scores ranging from 0 to 3, in which higher scores represent greater risks [22]. Nutritional status is determined through an examination of body mass index, recent weight loss, and food intake prior to admission to a healthcare facility. Weight and height were measured by trained nurses via calibrated hospital scales and stadiometers; self-reported data were not used, minimizing measurement bias.

Disease severity is assessed based on higher nutritional requirements as a result of an existing disease and any recent medical experience, such as surgeries, fractures, cancer treatments, or staying in an ICU. Points are also given if a patient is 70 years or older. If a total score of 3 or higher is achieved, it means that a malnourished or at-risk-of-malnourishment individual is in need of urgent nutritional care [22, 23]. Permission to use NRS 2002 was obtained from Prof. Kondrup via email.

In the fourth section, HRQoL is evaluated via the EQ-5D instrument, which was created by the Euro HRQoL Group. The EQ-5D is a well-known tool that has two essential components. The five EQ-5D dimensions are interpreted as follows: ‘Mobility’ refers to the individual’s ability to walk and move around; ‘Self-care’ concerns personal hygiene and dressing; ‘Usual activities’ includes work, study, housework, and leisure; ‘Pain/discomfort’ assesses both chronic and acute discomfort; and ‘Anxiety/depression’ captures emotional distress levels. Each dimension is rated on a 5-point scale ranging from no problems to extreme problems. The EQ-5D-5 L index score ranges from 0 to 1, where 0 indicates the worst imaginable health state and 1 indicates full health (perfect quality of life). Additionally, the EQ-VAS is a vertical visual analogue scale ranging from 0 (worst imaginable health) to 100 (best imaginable health), on which patients self-rate their overall health status. Higher scores reflect better quality of life. Permission to use the EQ-5D was formally obtained from the EuroQol Group. Although the instrument is freely available for noncommercial research purposes, official authorization is required and was granted prior to data collection.

The Arabic version of the EQ-5D was adopted following the guidelines provided by the Euro-HRQoL [24]. This tool is extensively used to assess overall HRQoL [25, 26] and has demonstrated its reliability and validity in measuring HRQoL in Palestine through various studies [27–33]. The Arabic version of the EQ-5D was made available through the EuroQol Research Foundation’s online system (ID: 57205) and has been thoroughly documented in previous studies conducted by the principal investigator Palestine [28, 30–37]. The EQ-5D index scores were calculated as described elsewhere [38–42] via the EQ-5D-5 L Crosswalk Index Value Calculator [43], which is based on the UK general population scoring algorithm.

We collected the data from patients via personal individual interviews, asked the patients questions in a direct way, and then collected the data from the patients’ health information system at each hospital.

Ethical approval

On March 9, 2022, the study was approved by An-Najah National University’s Institutional Review Board (IRB). Before beginning the study, permission was obtained from the Palestinian Ministry of Health, while the two chosen facilities, Al-Watani Government Hospital and An-Najah National University Hospital, granted permission for researchers to interview patients before the study began. Verbal consent was obtained from each patient who was informed about the objectives of the study and ensured the anonymity and confidentiality of the data, and the patient could withdraw from the study at any time.

Statistical analysis

The data were analysed via IBM SPSS Statistics version 21 (SPSS Inc., Chicago, IL, USA). Continuous variables are presented as the means ± standard deviations or medians with interquartile ranges, whereas categorical variables are expressed as frequencies and percentages. The Kolmogorov–Smirnov test was used to assess the normality of distributions. The Mann–Whitney U test and the Kruskal–Wallis test were used for data that were not normally distributed. A p value of < 0.05 was considered to indicate statistical significance. To identify factors independently associated with HRQoL, multiple regression analysis was conducted, including variables that demonstrated strong bivariate correlations. Cronbach’s alpha was used to evaluate the internal consistency of the HRQoL scale, and the variance inflation factor (VIF) was employed to assess multicollinearity. VIF values less than 3 were deemed acceptable.

Results

Demographic characteristics of the study sample

A total of 315 patients with solid cancers were approached, and 304 consented to participate (response rate: 96.5%). The majority were female (69.1%) and married (70.7%). Almost half (49.3%) had completed secondary education, and 40.4% were older than 60 years. Half of the participants lived in villages (50.3%), and 43.8% lived in cities. Most patients were not employed (82.2%), and more than half (58.2%) reported a monthly income between 2000 and 5000 NIS (1 NIS = 0.29 USD). Approximately 38.5% of the participants had a normal BMI, 32.2% were overweight, and 26.6% were obese. The full demographic details are presented in Table 1.

Table 1.

Sociodemographic characteristics of the study population

Variable	Frequency (%), n = 304
Gender
Male	94 (30.9)
Female	210 (69.1)
Age category (Years)
18–29	12 (3.9)
30–39	21 (6.9)
40–49	63 (20.7)
50–59	85 (28)
60–69	86 (28.3)
≥ 70	37 (12.2)
Marital status
Married	215 (70.7)
Single, separated, widowed	89 (29.3)
Educational level
Illiterate	16 (5.3)
Primary education	73 (24)
Secondary education	150 (49.3)
Higher education	65 (21.4)
Residency
City	133 (43.8)
Village	153 (50.3)
Camp	18 (5.9)
Occupation
Working	54 (17.8)
Not working	250 (82.2)
Monthly income
Less than 2000 NIS	85 (28)
2000–5000 NIS	177 (58.2)
≥ 5000 NIS	42 (13.8)
BMI category (kg/m²)
Underweight	8 (2.6)
Normal weight	117 (38.5)
Overweight	98 (32.2)
Obesity	81(26.6)

Abbreviations: BMI: Body mass index; NIS, New Israeli Shekel

Clinical characteristics of the study sample

Nutritional screening revealed that 26% of patients had NRS-2002 scores ≥ 3, indicating nutritional risk or malnutrition. As shown in Table 2, most patients (75.3%) were receiving chemotherapy, and approximately 38% of patients reported treatment-related complications (such as nausea, vomiting, mucositis, altered taste and smell, constipation, or swallowing difficulties) that markedly affected dietary intake. Hypertension (30.6%) and diabetes mellitus (24.0%) were the most common comorbidities. The three leading cancer types were breast cancer (40.5%), colorectal cancer (26.0%), and lung cancer (9.9%). Slightly more than half of the participants (51.3%) had been diagnosed 1–5 years prior, whereas 39.5% had had cancer for less than one year. The laboratory findings revealed a normal mean corpuscular volume (MCV) in 77.3% and abnormal haemoglobin (Hgb) values in 70.1% of the participants.

Table 2.

Clinical characteristics of the study population

Variable	Frequency (%), n = 304
Comorbidities
Hypertension	93 (30.6)
DM	73 (24)
Heart disease	8 (2.6)
Type of cancer
Gastric	9 (3)
Gastrointestinal-Colorectal	79 (26)
Breast	123 (40.5)
Lung	30 (9.9)
Bone	9 (3)
Ovarian	8 (2.6)
Prostate	14 (4.6)
Uterus	12 (3.9)
Thyroid	5 (1.6)
Liver	5 (1.6)
Others	10 (3.3)
Cancer duration
Less than one year	120 (39.5)
1–5 years	156 (51.3)
More than 5 years	28 (9.2)
Type of treatment
Chemotherapy	229 (75.3)
Radiotherapy	9 (3)
Surgery	26 (8.6)
Biological	71 (23.4)
Hormonal	52 (17.1)
Hgb (g/dL)
Normal	91 (29.9)
Abnormal	213 (70.1)
MCV (fL)
Normal	235 (77.3)
Abnormal	69 (22.7)
Creatinine serum
Normal	259 (85.2)
Abnormal	45 (14.8)
Complications’ effect on dietary intake
Very much	43 (14.1)
Relatively large impact	72 (23.7)
Modest impact	107 (35.2)
No effect	82 (27)
NRS score
< 3 not at risk	225 (74)
≥ 3 nutritionally at risk or already malnourished	79 (26)

Abbreviations: DM, diabetes mellitus; Hgb, haemoglobin; MCV, mean corpuscular volume; NRS, nutritional risk screening

HRQoL questionnaires (EQ-5D-5 L) of the study sample

The median EQ-5D-5 L index score was 0.72 (interquartile range [IQR] = 0.52–0.82), whereas the mean was 0.67, suggesting a moderate level of perceived health, with some participants reporting lower scores. The scale demonstrated high internal consistency reliability (Cronbach’s α = 0.815). With respect to specific health dimensions, 39.1% reported no mobility issues, 65.5% reported no self-care problems, and 41.1% reported no difficulty performing usual activities. Approximately 28.6% reported no pain or discomfort, whereas 31.6% reported moderate anxiety or depression. Severe or extreme problems in at least one dimension were reported by 13.9% of the participants, supporting the interpretation of moderate overall health status. The median EQ-VAS score was 70.0 (IQR = 50.0–80.0), and the mean score was 66.09, reflecting an overall positive perception of health and well-being. Table 3 presents the detailed EQ-5D-5 L dimension scores.

Table 3.

The five dimensions of the health-related quality of life scale (EQ-5D-5 L) of the participants

Variable	Frequency (%) n = 304
Mobility
I have no problems in walking about	119 (39.1)
I have slight problems in walking about	69 (22.7)
I have moderate problems in walking about	71 (23.4)
I have severe problems in walking	38 (12.5)
I am unable to walk about	7 (2.3)
Self-care
I have no problems washing or dressing myself	199 (65.5)
I have slight problems washing or dressing myself	50 (16.4)
I have moderate problems washing or dressing myself	31 (10.2)
I have severe problems washing or dressing myself	10 (3.3)
I am unable to wash or dress myself	14 (4.6)
Usual activities
I have no problems doing my usual activities	125 (41.1)
I have slight problems doing my usual activities	70 (23)
I have moderate problems doing my usual activities	63 (20.7)
I have severe problems doing my usual activities	20 (6.6)
I am unable to do my usual activities	26 (8.6)
Pain/discomfort
I have no pain or discomfort	87 (28.6)
I have slight pain or discomfort	66 (21.7)
I have moderate pain or discomfort	82 (27)
I have severe pain or discomfort	50 (16.4)
I have extreme pain or discomfort	19 (6.3)
Anxiety/depression
I am not anxious or depressed	72 (23.7)
I am slightly anxious or depressed	75 (24.7)
I am moderately anxious or depressed	96 (31.6)
I am severely anxious or depressed	49 (16.1)
I am extremely anxious or depressed	12 (13.9)

The EQ-5D-5 L scores range from 0 = worst health to 1 = best health

Relationships between demographic characteristics and HRQoL

The HRQoL index differed significantly across several demographic variables (Table 4). Younger patients had higher median EQ-5D-5 L index values than older patients did (p < 0.05). Employment status and higher monthly income were significantly associated with better HRQoL (p < 0.05). The BMI category also showed a significant positive association with HRQoL (p < 0.05); patients with a BMI ≥ 25 had higher median HRQoL scores than underweight patients did (BMI < 18.5). Marital status, sex, and educational level were not significantly related to HRQoL.

Table 4.

The five dimensions of the health-related quality of life scale (EQ-5D-5 L) of the participants by demographic characteristics

Variable	Median (IQR)	P value1
Age Category
18–29	0.79 (0.66–0.83)
30–39	0.67 (0.51–0.82)
40–49	0.78 (0.58–0.84)	0.003 3
50–59	0.75 (0.61–0.83)
60–69	0.65 (0.50–0.81)
≥70	0.61 (0.46–0.71)
Gender
Male	0.74 (0.50–0.84)	0.4942
Female	0.71 (0.56–0.82
Marital status
Married	0.72 (0.51–0.82)
Single, separated, widowed	0.73 (0.60–0.82)	0.5192
Educational level
Illiterate	0.66 (0.51–0.84)
Primary education	0.70 (0.60–0.83)
Secondary education	0.73 (0.50–0.82)	0.9043
Higher education	0.76 (0.57–0.82)
Residency
City	0.72 (0.52–0.81)
Village	0.71 (0.57–0.84)	0.6623
Camp	0.79 (0.40–0.81)
Occupation
Yes	0.81 (0.67–0.91)
No	0.69 (0.52–0.81)	< 0.001 2
Monthly average income
≤ 2000 NIS	0.68 (0.56–0.82)
2000–5000 NIS	0.70 (0.50–0.81)	0.007 3
≥ 5000 NIS	0.79 (0.68–0.91)
BMI category (kg/m 2 )
< 18.5
18.5–24.9	0.34 (0.21–0.67)
25–29.9.9	0.66 (0.50–0.81)	0.004 3
≥ 30	0.77 (0.62–0.82)
	0.74 (0.58–0.84)

 BMI: Body mass index; NIS, New Israeli Shekel

¹Bold values denote statistical significance at the level of p < 0.05

²Mann‒Whitney test

³Kruskal‒Wallis test

Relationships between clinical characteristics and HRQoL

Among the clinical characteristics (Table 5), hypertension was the only comorbidity significantly associated with a lower HRQoL (p = 0.03). Cancer duration was significantly positively associated with HRQoL (p = 0.02), with patients living with cancer for more than five years reporting higher scores. Neither cancer type nor treatment type was significantly related to HRQoL (p > 0.05). Patients with normal creatinine clearance had higher median HRQoL scores [0.73 (0.59–0.83)] than those with abnormal results [0.63 (0.46–0.81)], although this difference did not reach statistical significance (p = 0.055). Furthermore, complications that interfered with dietary intake were strongly associated with lower HRQoL (p < 0.001), indicating that symptom burden negatively influences nutritional status and perceived quality of life.

Table 5.

The five dimensions of the health-related quality of life scale (EQ-5D-5 L) of the participants by clinical characteristics

Variable	Median (IQR)	P value1
Presence of hypertension
Yes	0.65 (0.50–0.80)	0.0052
No	0.76 (0.57–0.84)
Presence of DM
Yes	0.67 (0.55–0.82)
No	0.74 (0.53–0.83)	0.2672
Presence of heart disease
Yes	0.72 (0.36–0.84)	0.6862
No	0.73 (0.53–0.82)
Type of cancer
Colorectal cancer	0.68 (0.50–0.83)
Stomach cancer	0.68 (0.64–0.83)
Breast cancer	0.76 (0.57–0.84)
Lung cancer	0.68 (0.40–0.80)
Ovarian cancer	0.76 (0.62–0.84)
Bone cancer	0.68 (0.26–0.81)
Prostate cancer	0.80 (0.59–0.85)	0.3433
Thyroid cancer	0.80 (0.67–0.84)
Uterine cancer	0.68 (0.50–0.75)
Liver cancer	0.79 (0.77–0.91)
Others	0.74 (0.43–0.86)
Cancer duration
<1 year	0.75 (0.59–0.82)
1–5 year	0.67 (0.50–0.81)	0.0453
> 5 years	0.80 (0.56–0.85)
Type of treatment
Chemotherapy
Yes	0.70 (0.52–0.82)
No	0.76 (0.58–0.84)	0.2262
Biological therapy
Yes	0.77 (0.53–0.84)
No	0.70 (0.53–0.82)	0.9162
Hormonal therapy
Yes	0.78 (0.56–0.84)
No	0.70 (0.52–0.82)	0.1742
Radiation therapy
Yes	0.67 (0.36–0.80)
No	0.73 (0.54–0.83)	0.1342
Surgery
Yes	0.77 (0.63–0.82)
No	0.72 (0.530.83)	0.4932
Hgb (g/dL)
Normal	0.76 (0.55–0.84)
Abnormal	0.70 (0.52–0.82	0.2382
MCV (fL)
Normal	0.72 (0.53–0.82)
Abnormal	0.73 (0.52–0.83)	0.8532
Creatinine
Normal	0.73 (0.59–0.83)
Abnormal	0.63 (0.46–0.81)	0.0552
Complications effect on dietary intake
Very much	0.63 (0.41–0.80)
Relatively large impact	0.66 (0.50–0.80)	< 0.0013
Modest impact	0.68 (0.52–0.82)
No effect	0.81 (0.69–0.86)

 DM, diabetes mellitus; Hgb, haemoglobin; MCV, mean corpuscular volume; NRS, nutritional risk screening

¹Bold values denote statistical significance at the level of p < 0.05

²Mann‒Whitney test

³Kruskal‒Wallis test

​ Correlations between the EQ-5D-5 L, EQ-VAS, and NRS-2002 scores

Correlation analyses (Table 6) revealed significant relationships among the study variables. First, a moderate negative correlation was observed between the EQ-5D-5 L and NRS-2002 scores (r = − 0.207; 95% CI: − 0.26 to − 0.15; p < 0.001). Second, a moderate positive correlation was found between the EQ-5D-5 L and EQ-VAS scores (r = 0.514; 95% CI 0.43 to 0.59; p < 0.001), indicating that patients who rated their overall health more highly also had better HRQoL index scores. Finally, a moderate negative correlation emerged between the NRS-2002 and EQ-VAS scores (r = − 0.369; 95% CI − 0.46 to − 0.27; p < 0.001).

Table 6.

Correlations between the NRS score and the two HRQoL scores in solid cancer patients

	EQ-5D-5 L score	VAS score	NRS score
EQ-5D-5 L score
Correlation coefficient	1		-
Sig. (2-tailed)	.
VAS score
Correlation coefficient	0.514**	1
Sig. (2-tailed)		.
NRS score
Correlation coefficient	−0.207**	−0.369	1
Sig. (2-tailed)			.

 EQ-5D-5 L, EuroQol-5 Dimensions; VAS, visual analogue scale; NRS, nutritional risk screening

Note: Values represent Pearson correlation coefficients. All the correlations are highly significant at p < 0.001

N = 304 patients

Multiple regression analysis of the associations of patient characteristics with HRQoL (EQ-5D-5 L score)

Multivariate linear regression analysis (Table 7) identified three independent predictors of HRQoL. Working status was positively associated with HRQoL (β = 0.152; 95% CI 0.045–0.255; p = 0.005), indicating that employed patients reported better quality of life than nonworking patients did. Fewer complications affecting dietary intake were also linked with better HRQoL (β = − 0.311; 95% CI − 0.415 to − 0.208; p < 0.001). Conversely, higher NRS-2002 scores predicted lower HRQoL (β = − 0.135; 95% CI − 0.243 to − 0.027; p = 0.015). The final model explained 26.1% of the variance in HRQoL (R² = 0.261; adjusted R² = 0.248; F = 9.52; p < 0.001). Multicollinearity was not detected (VIF = 1.017–1.243). These results emphasize that nutritional risk, occupational engagement, and dietary complications are key determinants of HRQoL in patients with solid tumors.

Table 7.

Multiple regression analysis of the associations of patient characteristics with HRQoL (EQ-5D-5 L score)

Variables	Unstandardized coefficients		Standardized coefficients	T	P value1	95.0% confidence interval for B		Collinearity statistics
	B	Std. error	Beta			Lower bound	Upper bound	Tolerance	VIF
Constant #	0.801	0.103		7.813	< 0.001	0.599	1.003
Age	− 0.001	0.001	− 0.047	− 0.797	0.426	− 0.003	0.001	0.812	1.232
Occupation	− 0.093	0.032	− 0.161	−2.863	0.005	− 0.156	− 0.029	0.912	1.096
Income	0.015	0.020	0.044	0.767	0.444	− 0.024	0.054	0.884	1.131
Hypertension	− 0.033	0.028	− 0.069	−1.196	0.233	− 0.088	0.021	0.850	1.176
Cancer duration	0.003	0.019	0.007	0.137	0.891	− 0.035	0.040	0.983	1.017
Complications effect on dietary intake	0.049	0.013	0.224	3.894	< 0.001	0.024	0.074	0.850	1.177
NRS score	− 0.024	0.010	− 0.147	−2.458	0.015	− 0.044	− 0.005	0.805	1.243

# The multiple linear regression model explained 26.1% of the variance in HRQoL (R² = 0.261; adjusted R² = 0.248), indicating acceptable model fit

 VIF, variance inflation factor; NRS, nutritional risk screening

¹Bold values denote statistical significance at the level of p < 0.05

Discussion

We have revealed that approximately one in four cancer patients, 26%, have a possible malnutrition risk. This is in line with findings in low- and middle-income countries, according to which cancer patients have a probability of malnutrition between 13% and 60% [44, 45]. In addition, we have found that a low HRQoL significantly contributes to unemployment and increased nutritional risks, along with complications that make eating difficult. This is in line with previous studies that indicate a close link between nutritional status and overall well-being [46, 47].

We have also been able to identify a link between NRS-2002 scores and body mass index (BMI) scores. Patient groups with lower BMI scores tended to have a score of 3 or higher on NRS-2002, signifying greater risks of malnutrition. This is in line with previous research that suggested that underweight patients were those that often fared worse in terms of nutritional status and those that had difficulty in receiving treatments [48, 49]. Adequate care of a patient’s nutrients leads to an improvement in their overall HRQoL [49]. To our knowledge, it is one of the first studies in a developing nation that attempts a quantitative relationship between NRS-2002, a measure of nutritional risk, and HRQoL in a cohort of solid tumor cancer patients. Though our findings have been modest in terms of relationship, they have a lot of clinical significance. That a negative relationship exists between NRS and HRQoL is an important aspect because it is an indication that malnutrition impacts an individual’s physical as well as mental well-being directly.

On the contrary, malnutrition leads to sarcopenia (muscle wasting) and psychologic stress, all of which decrease HRQoL and lead to greater dependence on caregivers [50–52]. Psychosocial consequences such as social withdrawal further shape the bidirectional relationship between nutritional status and HRQoL. Malnutrition contributes to sarcopenia, fatigue, immunosuppression, and impaired physical performance, all of which limit patients’ ability to tolerate therapy and perform daily activities [53, 54]. Solid tumor cancer patients, who must endure a significant tumor burden and treatment toxicities, are particularly susceptible to this [3, 50, 51]. Nutritional deficiencies may exacerbate emotional distress, depression, and anxiety, thereby reducing perceived quality of life [55]. Therefore, The relationship between malnutrition and poor HRQoL can be explained through sarcopenia which was found through previous research to have a substantial effect on cancer patients’ quality of life [51, 52]. Similar observations have been reported globally, where malnutrition and sarcopenia are recognized as independent predictors of poor HRQoL among cancer patients in low- and middle-income settings [50, 51]. Similarly, Alam et al. [46]. and Nourissat et al. [56]. reported that nutritional decline and impaired performance status are closely linked to diminished HRQoL. These convergent findings reinforce the external validity of our results across different cancer populations and healthcare contexts, supporting the notion that assessing and addressing malnutrition and sarcopenia should be integral components of comprehensive oncologic care, particularly in low-resource settings, and highlight the universal importance of integrating nutritional screening into comprehensive oncologic care to maintain functional capacity and psychological well-being.

Although solid cancer cases are increasing in Palestine and malnutrition is common among cancer patients globally, research on the risk of malnutrition and its further possible double-cause impact on HRQoL in high-risk groups is scarce. The nutritional status of the Palestinian population has generally declined as a result of political instability, parental unemployment, a limited food supply, poverty, and food insecurity [57]. The findings of this study have implications for both clinical care and healthcare policy and highlight the urgent need to integrate nutritional care into oncology services in developing contexts such as Palestine. Although 82% of the participants were unemployed, most reported household incomes within the national average (2000–5000 NIS), reflecting reliance on pensions and social assistance [58]. This reliance on household or governmental support highlights the socioeconomic vulnerability of cancer patients and its contribution to diminished HRQoL.

This study revealed that occupation, monthly income, and BMI were significantly positively associated with HRQoL, except for age, cancer duration and disease complications, which were negatively associated with HRQoL. This study provides evidence from previous observations that patients’ quality of life is negatively impacted by the cancer process itself and that the duration of the illness is more than 3 years [59, 60]. In contrast, our analysis did not reveal any statistically significant relationships between education status, marital status, or residency status and HRQoL. These results align with those of previous studies that reviewed the associations between demographic characteristics and HRQoL in individuals [55, 61–63]. In addition, HRQoL is not influenced by sex or type of cancer. These findings were also reported in a systematic literature review by Shrestha et al. [64].

Cohen et al. reported that hypertension is more common among cancer patients because of the cardiovascular toxicity of many anticancer medications, leading to cancer therapy–induced hypertension. This aligns with our finding that hypertension was the most prevalent comorbidity among individuals with solid cancer and was associated with poorer HRQoL. Furthermore, our analysis of laboratory parameters (Hgb, MCV, and creatinine) revealed that only the creatinine level was significantly associated with HRQoL. Together, these results emphasize the need for integrated, multidisciplinary care that addresses both cardiovascular and metabolic factors to improve the overall quality of life of cancer patients [65].

However, the analysis did not find a significant relationship between type of cancer [64] or type of treatment and HRQoL in this particular study. These results suggest that these factors may not have a substantial influence on the HRQoL reported by individuals with cancer in this specific sample. A possible explanation for this finding might be that the severity of malnutrition may vary according to the duration of cancer, stage of disease and treatment received, which affect the HRQoL [56].

Future research efforts should concentrate on the eating complications identified in this study. There is considerable potential for the development of an efficient system for classifying nutritional symptoms that could explain just how certain side effects of treatments lead to nutritional deficiencies. It would be advantageous, for instance, to investigate symptoms of post-chemotherapy vomiting, difficulty swallowing, loss of appetite, changes of taste or smell, diarrhea, constipation, and fatigue [66]. These symptoms could be grouped into three broad categories, namely: functional gastrointestinal symptoms, sensory changes, and systemic symptoms. By doing this, it would be easier to identify which combinations of these symptoms have more influence on eating and nutrient consumption behavior. Standardized patient-reported outcome measures and severity scales would allow for a more comprehensive understanding of how these complications affect cancer patients, enabling the provision of more personalized nutritional support.

Strengths and limitations

This study presents valuable findings related to the influence of nutritional status on cancer patients’ quality of life in limited-resource countries. Notably, this is one of the first studies in Palestine to use the NRS-2002 and EQ-5D-5 L methods together to assess nutrition and HRQoL. In fact, selecting participants from two large cancer hospitals was beneficial in terms of ensuring a more prompt and representative sample of participants.

Nevertheless, a few limitations have been identified. This convenience study, which involved interviews with patients, might be vulnerable to selection and interviewer biases. This issue was minimized by adequately training interviewers and validating answers given through medical records. Moreover, as it was a cross-sectional study, it is possible to reveal associations rather than causations. It also needs to be noted that it merely covered data from two hospitals in one region and might not accurately represent all cancer patients in Palestine.

There are also some limitations related to the methodology of this study. Although NRS-2002 is generally accepted and easy to use, it cannot accurately reflect cancer-specific issues such as muscle loss or vitamin deficiencies. Moreover, as it is a self-administered study, patients might have responded to EQ-5D-5 L in different ways, leading to biases in the study findings. Finally, while it is a large sample study, it is not large enough to make a detailed comparison between cancer types or treatments.

Despite its weaknesses, this study is an excellent addition to cancer research in Palestine. This study emphasizes that in countries such as Palestine, with strained healthcare facilities, a crucial aspect of cancer care would be ensuring that nutritional assessments and care are taken into consideration [67–71].

Conclusions

This research sheds light on a critical issue in cancer treatment: the fact that, regardless of cancer type or treatment regimen, a higher risk of malnutrition also correlates with a lower quality of life experienced by cancer patients. Other factors, including unemployment and difficulties with eating, also contributed to a lower HRQoL. These data highlight why addressing nutrition is a crucial component of cancer care. Early detection and assistance with respect to nutrition issues in cancer patients will also aid in helping cancer sufferers cope with their treatments. Nutrition is a modifiable issue, meaning we can influence it and make a real difference for our patients. Personalized approaches to care that factor in a patient’s unique needs and challenges, such as cancer care that incorporates a patient’s individualized needs related to their nutritional status, should be an integral part of cancer treatment, including in areas in which healthcare is limited in its capacities Nevertheless, given that this research was a cross-sectional study and that it took place in one particular region, it is prudent that its results be considered preliminary findings. Longitudinal research is needed to confirm the temporal relationship between nutritional status and HRQoL in cancer patients.

Recommendations and clinical implications

This study emphasizes the pressing need to incorporate nutrition screening as a routine aspect of cancer care, right from diagnosis through all phases of treatment. Use of tools such as NRS-2002 will assist healthcare professionals in identifying malnutrition early before it impacts treatment responses.

Having dietitians integrated within cancer care teams is imperative in ensuring that all cancer patients receive individualized nutrition care. Tailor-made diets would also aid in alleviating the usual side effects of treatment, such as loss of appetite, loss of taste, or deficiency of nutrients in a cancer patient’s body. Nutritional advice would also aid in relieving fatigue in cancer patients. Furthermore, the identified predictors, employment status, nutritional risk, and treatment-related complications, should guide the design of individualized supportive care strategies.

Because variables such as work status, nutritional status, or issues related to treatments have been found to affect HRQoL, it is important that supportive care also cater to such challenges. A multidisciplinary team comprising cancer specialists, nurses, nutritionists, and mental health professionals can actually provide holistic care.

Socioeconomic issues are also an area of concern. Issues such as unemployment and lack of income may lead to a lack of healthy food and healthcare, thus affecting HRQoL. Therefore, it is crucial to incorporate nutrition and psychosocial issues into cancer plans in countries with limited resources.

Looking ahead, it is clear that further research based upon these findings is warranted to better understand its effect regarding treatment success, rates of survival, and overall well-being. To further establish a foundation of a more patient-centric form of cancer care, tools need to be developed in which a patient is able to self-report their issues of cancer and related nutrition problems.

Abbreviations

HRQoL

Health-related quality of life

BMI

Body mass index

NRS

Nutrition risk screening

EQ-5D

European Quality of Life-5 Dimensions

EQ-VAS

European Quality of Life visual analogue scale

EuroQoL

European quality of life

EQ-5D-5L

European Quality of Life-5 Dimensions-5Levels

IRB

Institutional review board

DM

Diabetes mellitus

Hgb

Haemoglobin

MCV

Mean corpuscular volume

SPSS

Statistical Package for the Social Sciences

VIF

Variance inflation factor

PG-SGA

Patient-Generated Subjective Global Assessment

Author contributions

Shakhshir MH initiated and conceived the idea of the investigation, designed and supervised the study, analysed and coordinated the data, participated in the interpretation of the results, made significant contributions to the search and interpretation of the literature, critically revised the manuscript for important intellectual content, and wrote the final version. Samara S, Salameh R, and Zahdeh S reviewed the literature, collected the data, performed the analysis, and wrote the first draft of the manuscript. Salameh H. and Amer R. offered logistical support, assisted in data interpretation, and produced the final version of the manuscript. Zyoud SH conceptualized and supervised the field study, analysed the data, took responsibility for the integrity of the data, critically reviewed the manuscript to enhance intellectual content, and edited the final draft. All the authors reviewed and accepted the final manuscript.

Funding

There is no funding source for this research.

Data availability

This is an evidence-synthesis study; all data are available from the primary research studies or can be obtained from the corresponding author. The data and materials used in this work are available from the corresponding authors upon request.

Declarations

Ethics approval and consent to participate

The study protocol, encompassing access to and utilization of patient clinical data, received approval from the Institutional Review Boards (IRBs) at An-Najah National University and local health authorities. The IRB approval reference is (Ref. Pharm. D, March 2022/19), ensuring the protection of individuals without any associated risks. This research adhered to the principles outlined in the Helsinki Declaration and European guidelines for good clinical practice. Additionally, approval was sought and obtained from the NNUH search center. We want to emphasize that the collected information was exclusively utilized for clinical research purposes, with all patient data treated as confidential. The participants were provided with informed consent forms that assured data privacy, and the collected data remained confidential and dedicated solely to research. All the information was securely stored in a locked cabinet to safeguard human body rights, with limited access granted only to the researcher. Notably, the IRB of An-Najah National University exclusively approved verbal consent, as participants were solely required for interviews and faced no harm, provided that their privacy was maintained. The authors confirm that all methods adhered to the relevant guidelines and regulations.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.