Abstract
Background: Decreased diet intake and malnourishment have profound implications on cancer patients' quality of life and survival. Malnutrition increases the risk of postoperative complications, increases hospital length stays, reduces patient's tolerance to radiation and chemotherapy treatment, and results in poor response to treatment. In the present study, we intended to assess the nutritional status of cancer patients and find the correlation of body mass index with anthropometric and blood parameters.
Material & methods: The study was prospective and cross-sectional, and 104 patients with newly diagnosed solid tumors were included. Patient demographics, symptoms, and anthropometric and blood parameters were collected. The correlation was estimated with Pearson’s correlation coefficient. A p-value of less than 0.05 was considered significant.
Results: The association between stages of the disease, dental status, type of diet, and BMI was p=0.701, 0.216, and 0.422, respectively, and was not statistically significant. The anthropometric parameters mid upper arm circumference (MUAC cm), mid arm circumference (MAC cm), and triceps skinfold thickness (TSF mm) correlated with body mass index (BMI kg/m2) and had statistically significant p values of 0.0001, 0.0001, and 0.033, respectively. The correlation was assessed between hemoglobin, red cell distribution width, neutrophil-to-lymphocyte ratio, and serum albumin levels with BMI, but except for albumin (p=0.05), no other blood parameter correlated.
Conclusion: Nutritional assessment is vital in recognizing patients at risk of treatment-associated complications and poor responders to treatment. In this study, BMI correlated with anthropometric parameters MUAC, MAMC, and TSF. Baseline dietary assessments of patients will help focus on the nutritional build-up of patients before starting treatment.
Keywords: albumin, dietary, body mass index, cancer, malnutrition
Introduction
Cancer is one of the main reasons for morbidity and mortality throughout the world. Weight loss and nutritional problems are often associated with cancer. In advanced cancer stages, extreme weight loss is seen. Undernutrition is a hallmark of cancer. Approximately 40% of cancer patients present with weight loss [1]. Several studies indicate that malnutrition resulting from reductions in dietary intake occurs in 30 to 50% of cancer patients [1,2]. Decreased diet intake and malnourishment have profound implications on cancer patients' quality of life and survival [2]. Weight loss in cancer patients is associated with symptom distress (including fatigue, depression, and social withdrawal), poor quality of life, and increased treatment morbidity. Many cancer patients may not be candidates for potentially curative treatment because of poor nutritional status and performance status. Also, the effects of malnutrition increased the risk of postoperative complications, increased hospital length stay, reduced patient’s tolerance to radiation and chemotherapy treatment, and resulted in poor response to treatment [3]. Therefore, custom-made approaches to identify patients at nutritional risk are crucial to implementing nutritional support efficiently to reduce cancer morbidity. Cancer patients' nutritional status can be measured by history, physical assessment, and blood parameters [4,5]. This can help patients tolerate the oncology treatment effectively, improve their response to treatment, and reduce complications. In the present study, we intended to assess factors leading to decreased dietary intake and nutritional assessment of cancer patients so that we can identify patients at risk of malnourishment, help patients increase or maintain weight, and find the correlation of body mass index with anthropometric and blood parameters.
Materials and methods
Study design
The current study design was a prospective, cross-sectional study. One hundred four patients with newly diagnosed solid tumors who were visiting Radiation Oncology and Surgery OPD between January 2021 and December 2021 were included in the present study.
The inclusion criteria for patients older than 18 years and recently diagnosed cancer patients with solid tumors. Previously treated cancer patients, disease-free patients on follow-up, and patients suffering from hematological malignancies were excluded.
Data collection procedure
After taking written informed consent, a complete history and physical examination with symptoms of all patients were recorded. Each site was staged according to the 8th AJCC (American Joint Committee on Cancer) classification or FIGO (The International Federation of Gynecology and Obstetrics) in gynecological malignancies. Section I included patient demographics questions, i.e., age, gender, comorbidities, performance status, Cancer site, dietary habits, weight loss, and ongoing medication recorded. Section II included symptom assessment by assessing the history of risk factors and symptoms affecting dietary intake. Dietary history included evaluation of symptoms such as pain, nausea, vomiting, early satiety, constipation, taste alterations, dental and oral problems, and dysphagia leading to decreased appetite. Weight loss was defined as losing at least 5% of initial body weight and maintaining the loss for at least six months. Section III included anthropometric measurement for nutritional assessment. The instrument used was measuring tape and calipers. Height and weight were measured to calculate body mass index (BMI kg/m2), mid-upper arm circumference (cm)/ mid-arm circumference (cm), and triceps skinfold thickness (mm). Baseline blood investigations of hemoglobin, red cell distribution width (RDW), total leucocyte count, serum albumin, total protein, and serum creatinine of all patients were recorded. All the anthropometric and blood parameters and their normal values in both males and females, which were included in the study, are mentioned in Table 1.
Table 1. Anthropometric parameters and blood parameters' normal values.
| Variable | Normal Values |
| Body mass index (BMI) | Underweight <18.5 |
| Normal 18.5-25 | |
| Overweight 25-29.9 | |
| Obese > 30 | |
| Mid-upper arm circumference (MUAC) (cm) | Normal: >29 cm (Male) |
| Normal: >28.5 cm (Female) | |
| Mid-arm muscle circumference (MAMC) (cm) | Normal: >25 cm (Male) |
| Normal: >23cm (Female) | |
| Triceps skinfold thickness (TSF) (mm) | Normal: >12.5 mm (Male) |
| Normal: >16.5 mm (Female) | |
| Hemoglobin (gm/dl) | 13.5 - 17.5 g/dL (Male) |
| 12.0 -15.5 g/dL(Female) | |
| Red cell distribution width | 11.5 - 14.5% |
| Total leucocyte count (mm3 ) | 4-11 x 103 /mm3 |
| Absolute neutrophil count | 1,500 - 8,000 / mm3 |
| Absolute lymphocyte count | 1000 - 4000 /mm3 |
| Serum albumin (gm/dl) | 3.5 - 5.0 gm/dl |
| Total protein (gm/dl) | 6.0 - 8.3 g/dL |
Before patient recruitment, ethical committee approval was obtained from All India Institute of Medical Sciences Rishikesh Institute Ethical Committee (AIIMS/IEC/21/492 dated 02/09/2021). Written informed consent was obtained from all patients prior to commencement of the study.
Statistical analysis
IBM SPSS Statistics for Windows, Version 25 (Released 2017; IBM Corp., Armonk, New York, United States) was used for data analysis. Categorical variables were expressed using descriptive statistics (frequency and percentages), and continuous variables using mean and standard deviation. Pearson’s correlation coefficient was used to identify correlation. A p-value of less than 0.05 was considered significant.
Results
Sociodemographic profile and clinical characteristics
We analyzed 104 consecutive patients with solid malignancies during the study period. The age of patients ranged from 18-84 years, with a mean of 52.7 years. The male-to-female ratio was 1.4. Most of the patients, 75(72.1%), had ECOG-1 (Eastern Cooperative Oncology Group), and only one was ECOG-4. Thirty-seven (35.6%) patients were habituated to smoking. Only seven (6.7%) patients were edentulous. The most common site of cancer was the head and neck region 41(39.4%), followed by breast cancer in 25 (24&) patients. Eighty-four (80.7%) patients had stage III and IV, i.e., advanced stages of malignancies. At the presentation time, 32(30.8%) patients were underweight and had a BMI of less than 18.5 (Table 2).
Table 2. Sociodemographic profile and clinical characteristics of study patients (N=104).
| Variables | Options | Frequency (%) |
| Age (in years) | 18-30 | 06 (5.8) |
| 31-40 | 11 (10.6) | |
| 41-50 | 23 (22.1) | |
| 51-60 | 31 (29.8) | |
| 61-70 | 26 (25.0) | |
| > 70 | 07 (6.7) | |
| Gender | Male | 61 (58.7) |
| Female | 43 (41.3) | |
| Marital status | Married | 101 (97.1) |
| Single | 03 (2.9) | |
| ECOG* | 0 | 15 (14.4) |
| 1 | 75 (72.1) | |
| 2 | 11 (10.6) | |
| 3 | 02 (1.9) | |
| 4 | 01 (1.0) | |
| Personal Habits | Smoking | 37 (35.6) |
| Tobacco | 07 (6.7) | |
| Smoking+ Alcohol+ Tobacco | 16 (15.3) | |
| Nil | 44 (42.3) | |
| Comorbidities | Cardiac disease | 03 (2.9) |
| Hypertension | 04 (3.8) | |
| Diabetes | 05 (4.8) | |
| Others | 06 (5.7) | |
| None | 86 (82.7) | |
| Dental status | Edentulous | 07 (6.7) |
| Intact | 77 (74.0) | |
| Missing | 20 (19.3) | |
| Cancer Site | Head and Neck | 41 (39.4) |
| Breast | 25 (24.0) | |
| Lung | 05 (4.8) | |
| Gastrointestinal | 15 (14.4) | |
| Genitourinary | 06 (5.8) | |
| Gynaecological | 06 (5.8) | |
| Others(CNS**/thyroid) | 04 (3.8) | |
| Stage | I | 01 (01.0) |
| II | 18 (17.3) | |
| III | 62 (59.5) | |
| IV | 22 (21.2) | |
| Unknown | 01 (01.0) | |
| Diet | Liquid | 07 (06.7) |
| Semisolid | 19 (18.3) | |
| Solid | 75 (72.1) | |
| Tube feed | 03 (02.9) | |
| Mouth Opening | More than 35 mm | 100 (96.2) |
| 26-35 mm | 01 (01.0) | |
| 16-25 mm | 03 (02.8) | |
| BMI*** | Underweight | 32 (30.8) |
| Normal | 53 (51.0) | |
| Overweight | 15 (14.4) | |
| Obese | 04 (03.8) | |
| *ECOG: Eastern Cooperative Oncology Group, **CNS: Central nervous system, ***BMI: Body mass Index | ||
Anthropometric and blood parameters
The height of the patients ranged from 134 to 183 cm (mean 161.5). The mean mid-upper arm circumference (MUAC), mid-arm muscle circumference (MAMC), and triceps skinfold thickness (TSF) were 24.7, 21.5 cm, and 10.2 mm, respectively, but below average in both genders in all the patients (Table 3).
Table 3. Anthropometric and blood parameters of the study patients.
| Variables | Range | Mean ± SD (Standard Deviation) |
| Anthropometric parameters | ||
| Height (in cm) | 134-183 | 161.5±10.4 |
| Weight (in kg) | 33.6-86 | 53.4±10.6 |
| Body mass index (kg/m2) | 11.5-40.9 | 20.7 ± 4.7 |
| Mid-upper arm circumference (MUAC) (cm) | 18-33 | 24.7± 3.0 |
| Mid-arm muscle circumference (MAMC) (cm) | 15.4-29.5 | 21.5± 2.8 |
| Triceps skinfold thickness (mm) | 04-20 | 10.2± 2.4 |
| Blood parameters | ||
| Hemoglobin (gm/dl) | 8.6-16.7 | 12.3± 1.5 |
| Red cell distribution width (RDW) | 11.2-18.4 | 13.8±1.6 |
| Total leucocyte count (TLC) (mm3) | 1010-19700 | 7075.8 ± 3729.4 |
| Absolute neutrophil count (ANC) | 650.5-13708 | 4655.8 ± 2787.9 |
| Absolute lymphocyte count (ALC) | 64.3-4052 | 1536.2 ± 999.0 |
| Neutrophil to lymphocyte ratio (NLR) | 0.05-87.4 | 4.24 ± 8.42 |
| Serum albumin (gm/dl) | 1.2-4.8 | 3.19 ± 0.89 |
| Total protein (gm/dl) | 3.2-9.2 | 6.7 ± 1.2 |
| Blood sugar (random) mg/dl | 65-339 | 102 ± 41.0 |
Association of BMI with clinical variables
Twelve patients with head and neck cancer had low BMI, followed by eight with gastrointestinal cancer, whereas six patients with breast cancer were obese. Twenty-two and four patients of stage III and stage IV respectively were underweight. The association between stages of the disease, dental status, type of diet, and BMI was p=0.701, 0.216, and 0.422, respectively, and not statistically significant (Table 4).
Table 4. Association of BMI with clinical variables of study patients.
| Variables | Options | BMI Category | F-value | p-value | |||
| Underweight | Normal | Overweight | Obese | ||||
| Gender | Male | 20 | 33 | 7 | 1 | 10.246 | 0.086NS |
| Female | 12 | 20 | 8 | 3 | |||
| Cancer site | Breast | 04 | 13 | 06 | 02 | 5.546 | 0.814NS |
| Gastrointestinal | 08 | 05 | 02 | 00 | |||
| Genitourinary | 01 | 03 | 00 | 02 | |||
| Gynaecological | 01 | 03 | 02 | 00 | |||
| Head and Neck | 12 | 24 | 05 | 00 | |||
| Lung | 05 | 00 | 00 | 00 | |||
| Other | 00 | 04 | 00 | 00 | |||
| Total | 32 | 53 | 15 | 04 | |||
| Stage | I | 00 | 01 | 00 | 00 | 11.172 | 0.701NS |
| II | 06 | 10 | 01 | 01 | |||
| III | 22 | 28 | 09 | 03 | |||
| IV | 04 | 13 | 05 | 00 | |||
| Unknown | 00 | 01 | 00 | 00 | |||
| Total | 32 | 53 | 15 | 04 | |||
| Dental status | Edentulous | 02 | 05 | 00 | 00 | 7.558 | 0.216 NS |
| Intact | 22 | 36 | 15 | 04 | |||
| Missing | 08 | 12 | 00 | 00 | |||
| Total | 32 | 53 | 15 | 04 | |||
| Diet | All | 00 | 01 | 00 | 00 | 12.389 | 0.422 NS |
| Liquid | 01 | 03 | 03 | 00 | |||
| Semisolid | 10 | 07 | 02 | 00 | |||
| Solid | 20 | 40 | 10 | 04 | |||
| Tube Feed | 01 | 02 | 00 | 00 | |||
| Total | 32 | 53 | 15 | 04 | |||
| NS- Non-significant at 0.05 level | |||||||
Association of BMI with anthropometric and blood parameters of patients
The anthropometric parameters MUAC, MAMC, and TSF were associated with changes in BMI and had statistically significant p values of 0.0001, 0.0001, and 0.033, respectively, but not with hemoglobin, RDW, and NLR (Table 5).
Table 5. Association of BMI with anthropometric and blood parameters of patients.
| Variables | BMI Options | N | Mean | SD | F-value | p-value |
| Mid-upper arm circumference | Underweight | 32 | 22.07 | 2.13 | 22.873 | 0.0001* |
| Normal | 53 | 25.61 | 2.17 | |||
| Overweight | 15 | 26.28 | 3.39 | |||
| Obese | 4 | 29.13 | 1.65 | |||
| Mid-arm muscle circumference | Underweight | 32 | 19.14 | 2.06 | 19.815 | 0.0001* |
| Normal | 53 | 22.35 | 2.08 | |||
| Overweight | 15 | 22.89 | 3.19 | |||
| Obese | 4 | 25.24 | 1.51 | |||
| Triceps skinfold thickness (mm) | Underweight | 32 | 9.33 | 3.20 | 3.023 | 0.033* |
| Normal | 53 | 10.38 | 2.02 | |||
| Overweight | 15 | 10.81 | 1.39 | |||
| Obese | 4 | 12.38 | 0.48 | |||
| Hemoglobin | Underweight | 32 | 12.41 | 1.90 | 0.366 | 0.778 NS |
| Normal | 53 | 12.34 | 1.26 | |||
| Overweight | 15 | 12.45 | 1.28 | |||
| Obese | 4 | 11.60 | 2.00 | |||
| Red cell distribution width (RDW) | Underweight | 32 | 13.86 | 1.74 | 0.703 | 0.553 NS |
| Normal | 53 | 13.79 | 1.57 | |||
| Overweight | 15 | 13.53 | 1.45 | |||
| Obese | 4 | 14.83 | 1.35 | |||
| Neutrophil lymphocyte ratio (NLR) | Underweight | 32 | 5.95 | 14.95 | 0.633 - | 0.596 NS |
| Normal | 53 | 3.50 | 2.00 | |||
| Overweight | 15 | 3.43 | 1.25 | |||
| Obese | 4 | 3.25 | 1.34 | |||
| Serum albumin | Underweight | 32 | 2.96 | 0.97 | 2.670 | 0.05* |
| Normal | 53 | 3.32 | 0.80 | |||
| Overweight | 15 | 2.99 | 0.93 | |||
| Obese | 4 | 4.05 | 0.54 | |||
| NS- Non-significant at 0.05 level; *Significant at 0.05 level | ||||||
The anthropometric parameters MUAC, MAMC, and TSF showed positive correlation with BMI (Figure 1).
Figure 1. Correlation graphs of BMI with anthropometric parameters (A) MUAC (r=.636; p=0.0001), (B) MAMC (r=.596; p= 0.0001), and (C) TSF (r=.326; p=.033).
MUAC: Mid-upper arm circumference; MAMC: mid-arm circumference; TSF: triceps skinfold thickness
Discussion
Cancer patients are likely to develop nutritional deficiency owing to disease burden and the effect of treatment [6]. The incidence of malnutrition in patients with cancer varies from 40 to 80%, and its causes are multifactorial [7]. It depends on the type of disease, location, stage, treatment received, and method used for nutritional assessment. Also, dietary changes, cancer cachexia, and symptoms having an impact on nutrition are contributory factors [8]. Hence baseline assessment of the nutritional status of cancer patients is very vital. Anthropometric measurements such as weight, MAMC, TSF, and laboratory parameters (such as serum albumin) are frequently used techniques to assess the nutritional status of cancer patients [9]. Hence in the present study, baseline nutritional status of cancer patients was assessed using various anthropometric measurements.
Most common solid tumor sites were included in the present study; however, some, such as sarcoma and melanoma, were not represented. In the present study, we included all stages and sites of cancer disease cases, and overall 30.8% of patients suffered from malnutrition, whereas the study by Muhamed et al. reported around 48.1%, whereas Cuong and Argefa et al. reported 34.1% and 32 % of cancer patients suffered from malnutrition; hence, our study findings were similar to these studies' findings [10-12].
Muhamed et al. reported that the main reasons for malnutrition were low socioeconomic status, different nutritional methods for assessment, lack of adequate healthcare facilities, and dietician support. In our present study, 34.6% of patients with advanced stages (III and IV) presented with poor nourishment and were underweight in the present study. A study by Nourissat et al. reported a strong correlation between weight loss and quality of life in cancer patients [13].
In this study, we found a correlation between the BMI of patients with anthropometric parameters MUAC, MAMC, and TSF. In this study, we also identified a significant correlation of BMI with serum albumin, a widely used laboratory parameter for indices for malnutrition, because of its long half-life [14].
Jeong et al. studied the correlation of blood indices with BMI in children and adolescents. They identified that higher BMI was associated with higher levels of white blood cells (WBCs), red blood cells (RBCs), hemoglobin, hematocrit, and platelet count [15]. The reason for raised WBCs is the production of IL-6 by adipose tissue, which has a role in bone marrow granulopoiesis, and white cell differentiation [16]. However, the reasons for increased RBC indices with obesity are not well understood. Hemoglobin and serum albumin levels have been studied as markers of malnutrition in cancer. The association of blood parameters with BMI in cancer patients has been less studied. In the present study, blood parameters did not correlate with BMI except serum albumin.
The present study had limitations of a small sample size and all solid malignancies were not included. Also, anthropometric measurements (triceps skin fold, midarm muscle circumference) for the assessment of fat deposits and lean body mass are rarely used in a routine clinical setting owing to great variations among individuals and interobserver measurement variability.
Conclusions
Nutritional assessment is vital in recognizing patients at risk of treatment-associated complications and poor responders to treatment. In this study, BMI correlated with anthropometric parameters MUAC, MAMC, and TSF. Baseline dietary and anthropometric assessments of patients will help to focus on the nutritional build-up of patients before commencement of treatment.
The authors have declared that no competing interests exist.
Author Contributions
Concept and design: Sweety Gupta, Amit Gupta, K Vidhya, Deepika Raina, Kusum Kumari, Yogapriya Velumani
Acquisition, analysis, or interpretation of data: Sweety Gupta, Amit Gupta, K Vidhya, Kusum Kumari, Lekshmi R, Namitha RS, Yogapriya Velumani
Drafting of the manuscript: Sweety Gupta, Amit Gupta, K Vidhya, Deepika Raina, Lekshmi R, Namitha RS, Yogapriya Velumani
Critical review of the manuscript for important intellectual content: Sweety Gupta, Amit Gupta, Deepika Raina, Kusum Kumari, Yogapriya Velumani
Supervision: Sweety Gupta, Amit Gupta, Deepika Raina
Human Ethics
Consent was obtained or waived by all participants in this study. All India Institute of Medical Sciences Rishikesh issued approval AIIMS/IEC/21/492 dated 02/09/2021
Animal Ethics
Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue.
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