Introduction

Severe acute malnutrition (SAM) presents a ubiquitous health dilemma, primarily impacting young children in regions characterized by limited access to adequate nutritional and healthcare infrastructure within low- and middle-income countries. Despite sustained worldwide initiatives, SAM continues to stand as a prominent contributor to the prevalence of morbidity and mortality in the population of children under the age of 5 [1].

Approximately 2.2 million fatalities in the cohort of children under the age of 5 can be ascribed to severe wasting, stunting, and intrauterine growth restriction. Within the developing regions, one out of every five children experiences undernourishment, and this condition is linked to 50% of child mortalities on a global scale [2]. The mortality rate associated with SAM among children below the age of 5 exhibits a range between 30% and 50%, with malnutrition being the primary or contributing factor in the majority of child fatalities with comorbidities [3]. In India, as per the recent National Family Health Survey-5 (NFHS-5) (2019–2021), the prevalence of SAM remains alarmingly high at 7.7%. As per the findings from the NFHS-5 reports concerning the nutritional status of children, it was noted that 35.58% of children below the age of 5 exhibited stunting (signifying reduced height in relation to their age), 19.21% were afflicted by wasting (indicating low weight concerning their height), and 32.16% were underweight (suggesting inadequate weight concerning their age) [4]. “Severe acute malnutrition (SAM) is defined by very low weight for height or length [z-score below—3 standard deviation (3SD) of the median World Health Organization (WHO) child growth standards], or a mid-upper arm circumference (MUAC) less than 115 mm, nutritional bipedal oedema, or visible severe wasting.” [5]. SAM represents a complex issue encompassing both social and medical dimensions. The child’s medical complexities are, to some degree, an outcome of prevailing social problems within the household. When parents or caregivers face challenges in offering appropriate care and nutrition due to factors like insufficient awareness, constrained resources, or interpersonal disputes, it leads to the development of malnutrition [6]. Anemia is defined by a decreased level of hemoglobin in the bloodstream and is associated with micronutrient deficiencies, including vitamins B-12 and B-9, as well as several infectious diseases that primarily affect red blood cells. This hematological disorder can impact individuals across all age groups, but it is the most widespread and severe among women of childbearing age, children below the age of 5, individuals suffering from other illnesses, and those with additional nutritional deficiencies [7]. Common symptoms of anemia include lethargy, tachycardia, and pallor. In 2020, it was estimated that worldwide, there were 149 million children under the age of 5 who experienced stunted growth (shorter than expected for their age), 45 million children who suffered from wasting (being too thin for their height), and 38.9 million who were classified as overweight or obese [8]. Severe anemia plays a substantial role in the morbidity, hospitalization, and mortality of pediatric patients. However, there exists a notable research gap when it comes to understanding its influence on malnutrition-related mortality. In India, a significant portion of children experiences the co-occurrence of SAM and severe anemia, highlighting the need for further investigation [9]. In fact, anemia is the most frequent concomitant medical condition encountered in children with SAM and is sometimes referred to as “complicated SAM”, which slows down recovery and raises the risk of mortality when compared to anemic children without SAM and non-anemic children with SAM [10]. The extensive utilisation of suitable anthropometric tools facilitates the prompt and precise diagnosis of SAM. Early identification and management are crucial for reducing mortality and preventing long-term complications associated with SAM and its comorbidities. The timely intervention leads to reduced treatment delays, diminished disease transmission, lower case fatality rates, prevention of adverse outcomes, and an overall enhancement in patient outcomes. Early recognition and dietary modifications can also contribute to decreased mortality and morbidity rates [11]. Liver function tests, kidney function tests, and complete blood counts, together with anthropometric assessments, are abnormal in SAM, although it is unclear how these abnormalities relate to the prognosis. Thus, a study to emphasize its predictive importance was required. The current study was carried out for this aim in the pediatric ward of the G.S.V.M. Medical College, Kanpur, Uttar Pradesh, India.

Materials and methods

This cross-sectional cohort study was performed at the departments of pediatrics and biochemistry at G.S.V.M. Medical College, Kanpur, and at the department of biotechnology at Amity University, Rajasthan, Jaipur. A total of 106 children with SAM were included in the study. Among them, 53 children had additional health problems, i.e., dehydration, and they were grouped as “SAM with complications”, who were recruited from the outpatient department (OPD) and inpatient department (IPD) of the hospital. The other 53 children did not have any complications, and they were categorized solely based on their body measurements. These children were referred to as “SAM without complications” samples, and they were approached through house-to-house visits in an area with Anganwadi workers at the community level.

Results

Demographic and anthropometric data pertaining to the study participants reveal that the mean age in Group I was 15.11 months ± 10.06 months, consisting of 28 males and 25 females. In contrast, the mean age in Group II was 23.36 months ± 12.77 months, with 35 males and 18 females. In total, across both groups, there were 63 males and 43 females. Regarding economic status, it was observed that in Group I, 51 participants fell into the low-income category, while 53 participants in Group II also belonged to the low-income group. However, 2 participants from Group I were categorized as high-income. In the broader context, the majority of participants in both groups were found to belong to the low-income category. In terms of anthropometric measurements, it was observed that Group II exhibited significantly higher values for height, weight, MUAC, head circumference, and body mass index (BMI) for age percentile in comparison to Group I (P = 0.001). Additionally, both Group I and Group II demonstrated similar z-scores for height for age and weight for height. The mean values for height for age z-score were –3.4 ± 0.53 (P = 0.001), and for weight for height z-score, they were –3 ± 0.00 (P = 0.001), respectively. The demographic and anthropometric measurements for study participants are also presented in Table 1.

A comparison of blood parameters between the two groups is presented in Table 2. Group I exhibited lower hemoglobin levels at 8.86 g/dL ± 2.21 g/dL, whereas Group II had higher levels at 10.0 g/dL ± 1.83 g/dL (P = 0.003). However, the other parameters, such as leukocyte count, platelet count, red blood cell count, mean platelet volume, urea, and creatinine, did not exhibit significant differences between the groups.

In Group I, the levels of direct bilirubin (0.47 mg/dL ± 0.57 mg/dL) were higher when compared to Group II, where they measured at 0.22 mg/dL ± 0.08 mg/dL (P < 0.001). Conversely, Group II had higher levels of protein and albumin (P = 0.002 and 0.001), while the levels of serum glutamic pyruvic transaminase (SGPT) and serum glutamic oxaloacetic transaminase (SGOT) were lower in Group II (P = 0.009 and 0.031).

As indicated in Table 3, Group I consisted of 43 individuals with anemia and 10 without anemia, whereas Group II included 33 individuals with anemia and 20 without anemia. The prevalence of anemia was significantly higher in Group I compared to Group II (P = 0.026).

The results of the regression analysis are presented in Table 4. Regarding the dependent variable, SAM with complications, age did not show a significant association (P = 0.680). However, gender exhibited a significant association (P < 0.01), with males having 6.122 times higher odds. Additionally, MUAC showed a significant positive association (P < 0.001), where a one-unit increase in MUAC was associated with 8.729 times higher odds. Hemoglobin levels were also significantly associated (P < 0.05), with a one-unit increase in hemoglobin resulting in 1.368 times higher odds, while holding other variables constant.

Discussion

The prevalence of SAM in India is alarmingly high, demanding urgent attention. Among the numerous comorbidities that exacerbate the mortality risk in severely undernourished children, severe anemia stands out as a critical concern.

From an intervention development standpoint, it is important to highlight that around 90% of children afflicted by SAM do not present with medical complications. This implies that they can receive care within their local communities, obviating the need for hospitalization. In contrast, those with medical complications necessitate admission to healthcare facilities, as noted in the study by Panda S et al. (2016) [13]. This cross-sectional study was performed to analyse the risk of complicated SAM in anaemic patients. Males are more prominent for uncomplicated SAM compared to females (Table 1). Additionally, we found a significant difference in height, weight, MUAC, head circumference, BMI for age percentile, height for age, and weight for height between Groups I and II. Similarly, In the study conducted by Chiabi A et al. in 2017, it was reported that the median age of the children was nine months, with an almost equal gender distribution, consisting of 50.8% male and 49.2% female participants [14]. The study carried out in Sri Lanka concentrated on a single rural district known as Vavuniya, where more than 70% of children diagnosed with SAM originate from socioeconomically disadvantaged backgrounds. This finding aligns with the results of our own study [9]. Panda S et al. (2016) suggested that the weight for height z-score, which indicates both acute and chronic nutritional deficits, described that 4 out of the 5 villages were in a critical stage of malnutrition [13]. In our comparison of the biochemical profiles between Groups I and II (as shown in Table 2), significant disparities were observed in the blood levels of hemoglobin, protein, and albumin. This finding aligns with the research conducted by Kumar D et al. in 2020 [1], where they demonstrated that hyponatremia and hypocalcemia are more prevalent and carry a higher risk of mortality in children with complicated SAM. According to the guidelines (2012) for SAM, approximately 70% of children aged 6 to 59 months who have SAM also experience anemia. Among these children, 26% exhibit mild anemia, 40% have moderate anemia, and 3% have severe anemia [15]. In this study, a higher frequency of anemia in complicated SAM as compared to uncomplicated SAM was found. Similarly, Thakur N et al. (2014) found a significant number of severely anemic patients with SAM, of whom approximately 25% need blood transfusions, suggesting that nutritional anemia is a prevalent concurrent condition in SAM cases that necessitate hospitalisation. Given the close occurrence of megaloblastic anemia and microcytic anemia, it is advisable to consider supplementing with vitamin B12 in conjunction with iron and folic acid [9].

In this study, as depicted in Table 4, we identified significant associations between male gender, MUAC, and hemoglobin levels with the risk of anemia. These findings are in accordance with the research conducted by Takele WW in 2021, which highlighted that anemia among severely malnourished infants and children poses a significant public health concern in the Amhara region. Furthermore, the study by Takele WW in 2021 [7] underscores that infants below the age of 6 months are at a higher risk of developing anemia.

Chowdhury MRK et al. (2020) [16] revealed that around 52.6% of the children (95% CI, 49.8–55.4%) were identified as anemic. Among them, 26.6% (95% CI, 24.0–29.3%) were found to have moderate to severe anemia. The occurrence of anemia exhibited a pronounced increase in children below the age of 11 months, children with low body weight, children whose mothers were underweight, anemic, and had limited formal education, and children living in ecologically demanding environments. A comprehensive analysis considering multiple variables uncovered that children under 11 months of age, those with lower body weight, and those with mothers afflicted by anemia were at an elevated risk of developing moderate to severe anemia. This suggests that these specific factors contribute significantly to the severity of anemia in children.