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Risk factors for wasting among hospitalised children in Nepal

Abstract

Background

Malnutrition has various adverse effects in children. This study aimed to determine risk factors for malnutrition among hospitalised children, changes in nutritional status at admission and discharge and effects of use of systematic anthropometric measurement in identification of malnutrition.

Methods

We enrolled 426 children, aged between 6 months and 15 years, admitted to Siddhi Memorial Hospital, Bhaktapur, Nepal, from November 2016 to June 2017. Anthropometric measurements were performed at the time of admission and discharge. Risk factors were assessed by multivariable logistic regression models.

Results

Median age of children was 26 months (IQR: 13–49), and males were 58.7%. The prevalence of wasting was 9.2% (39/426) at admission and 8.5% (36/426) at discharge. Risk factors associated with wasting at admission were ethnic minority (aOR: 3.6, 95% CI 1.2–10.8), diarrhoeal diseases (aOR = 4.0; 95% CI 1.3–11.8), respiratory diseases (aOR: 3.4, 95% CI 1.4–8.1) and earthquake damage to house (aOR = 2.6; 95% CI 1.1–6.3). Clinical observation by care providers identified only 2 out of 112 malnutrition cases at admission and 4 out of 119 cases at discharge that were detected by the systematic anthropometric measurement.

Conclusions

Ethnic minority, diarrhoeal diseases, respiratory infections and house damage due to the earthquake were risk factors associated with wasting. Systematic anthropometric examination can identify significantly more malnourished children than simple observation of care providers.

Introduction

Undernourished children suffer not only from insufficient physical and mental growth, but also have a high susceptibility to the infectious diseases and have a high risk of death. The UNICEF–WHO–World Bank Group Joint Malnutrition Estimates shows that the 45.4 million under 5 children suffered from wasting in 2020 [1]. Primary risk factors for undernutrition are poverty, lack of adequate food, recurrent illnesses, inappropriate feeding practices and lack of care and poor hygiene [2].

Although hospitalised children are at high risk of malnutrition, they are not routinely assessed for wasting at the time of admission [3]. Knowing nutritional status can help clinical management of the children as poor nutritional status is associated with an increased length of hospital stay and a worse prognosis for both communicable and non-communicable diseases [4, 5]. Wasting in hospitalised patients is a neglected issue, and children who are discharged with poor nutritional status are more likely to be re-admitted and have an increased risk of post-discharge mortality.[6].

In 2015 Nepal suffered two major earthquakes that killed about 8900 people along with damaging thousands of houses, health centres and food storage buildings. Natural disasters, including earthquakes, can put children at risk for undernutrition [7, 8]. Bhaktapur was one of the 14 districts, which was affected heavily by the earthquakes. We conducted this nutritional survey in Siddhi Memorial Hospital (SMH), Bhaktapur after 1 year of the earthquake to assess the prevalence of undernutrition among paediatric patients, which was unknown before. It was important as we could detect undernourished children and provide them appropriate treatment and counselling while they were in the hospital. We carried out the survey by introducing systematic anthropometric measurements to the hospital. In addition, we quantified the disparity between systematic anthropometric measurements and the care providers’ detection and assessed risk factors associated with wasting at the time of admission.

Methods

Study design

This study was a cross-sectional study (serial surveys) in paediatric patients newly admitted to the paediatric ward in Siddhi Memorial Hospital (SMH), Bhaktapur, Nepal. Cross-sectional data were collected at a point of their admission and discharge.

Study setting

SMH is a 50-bed paediatric hospital in Bhaktapur district. It is the only paediatric hospital in the district where about 75,000 children (age < 15 years) live (https://dccbhaktapur.gov.np/en/brief-introduction/). SMH provides medical services in the following facilities: paediatric out-patient department, paediatric in-patient department, intensive care unit, emergency department, gynecology and obstetrics department and dental department. There are approximately 15,000 visits to the out-patient department and 1500 admissions to the in-patient department each year. The in-patient department has 50 beds. This hospital provides specialised care for relatively severe paediatric patients as it runs in-patient department and intensive care units, and patients out of Bhaktapur district also come for in-patient services.

Subjects and recruitment method

All patients who were admitted to the paediatric in-patient department in SMH from 17th November 2016 to 30th June 2017 were approached for the recruitment. Among them, those whose reported age ranged from 6 months to 191 months (15 years) were eligible, and their parents/guardian were counselled for the enrolment of their children in the study. We excluded those whose parents or guardians did not give a written consent to take part in the study. Children with a severe clinical condition, such as requiring respiratory support, immobilised, severe burns, fractures, abdominal trauma or congenital syndromes (e.g., Down syndrome, congenital cardiac diseases) were excluded from the enrolment. The estimated sample size was calculated as 340 to detect a 5% difference in the prevalence of wasting (z-score < − 2 of weight-for-length or weight-for-height, or BMI) compared to the national average of 11% (in children < 5 years), computed by using single-sample z-test of proportion with power of 80% and significance of 5%.

Case definition of wasting

Moderate wasting was defined as a weight-for-height/length z-score (WHZ) between -3 and -2 SD, and severe wasting was defined as WHZ below − 3 SD (WHO, 2009) or MUAC less than 115 mm for children less than 60 months. For children aged over 60 months, moderate wasting was defined as BMI for age z-score between − 3 and − 2 SD, and severe wasting was defined as below − 3 SD of the same indicator [9].

Enrolment and anthropometric measurement

Research assistants were trained to perform anthropometric measurements. Two research assistants checked the ward-admission register once daily (including weekends), and when they found newly hospitalised patients, their parents or guardians were asked if their children could take part in the study. After obtaining written consent from them (and written assent for those whose children are 10 years or more), they were interviewed using structured questionnaires, using the Nepali language. The questionnaire includes the information about demographic detail of the child (birthday, ethnic group, religion, place of living, etc.), socioeconomic status of the household, earthquake effects, immunisation history, usual feeding history, recent dietary intake, medical record, and lab test results. Home damage was defined as any damage due to earthquake to their residence reported by the parents. The results of the haematological test were obtained from laboratory results sheet and the clinical diagnosis was obtained from medical records of the patient. After interviewing the parents or guardians, participating children were measured for weight, height (or length for babies < 2 years) and MUAC by the trained research nurses. Seca 833 (https://www.seca.com/) was used for measuring weight scale for infant and Seca 803 for adults; the minimum display units of them were 10 g and 100 g, respectively. A stadiometer (Seca 417) was used for measuring length/height that had minimum display unit of 1 mm. Weights for diapers and/or clothes (40–450 g) were subtracted according to age group of children. In normal condition, their weight and height were measured in standing posture using a stadiometer. When children could not maintain a standing posture, weight was measured by holding the child by the parent or guardian and then subtracted the adult’s weight from the results. In case of dehydrated patients, weight was measured only after correction of dehydration. For height measurement in such cases, the results of arm span substituted, because arm span can serve as accurate and reliable surrogate measures of recumbent length and height [10]. Anthropometric measurements were conducted again on the day of hospital discharge. Laboratory results and diagnosis were updated if applicable. Clinical diagnosis of nutritional status was made by treating doctors by looking at the children and general physical examination during the ward round which occurred every day.

Data analysis

The anthropometric measurement and questionnaire survey data were entered into Epi Info (CDC, Atlanta, USA) software. The dataset was imported to STATA Version 15.0 (StataCorp, TX, USA) for further analysis. The sociodemographic characteristics of participants were described using descriptive statistics. Ethnicities were classified according to their prevalence in the hospitalised children. The first five ethnicities with higher prevalence were reported separately, and the remaining all were grouped as “Others”. Proportions were compared by using Chi-squared test. Inter-rater agreement for the clinical assessment and the measured assessment result was determined using the Kappa statistic. Calculated Kappa values of ≤ 0.20 are considered to reflect poor agreement, > 0.20 and ≤ 0.40 fair agreement, > 0.40 and ≤ 0.60 moderate agreement, > 0.60 and ≤ 0.80 good agreement and > 0.80 very good agreement. A logistic regression model was used to assess the risk factors. A priori variables (sex, child’s age and ethnicity) and variables whose p value < 0.2 in univariable analysis were included in the multivariable logistic regression model. The model was checked by the goodness of fit test.

Ethical consideration

Ethical approvals were obtained from Nepal Health Research Council, Kathmandu, Nepal (Reg. no. 265/2016) and School of Tropical Medicine and Global Health (TMGH), Nagasaki University, Japan (Approval Ref no. 4, 2016). The study did not involve any invasive procedures; anthropometric measurements were performed with extreme cautions not to give any discomfort to the participants. The result of anthropometric measurement and short nutritional counselling were provided to the parents/guardian of the children by the research assistants. When the malnourished children were found, their parents or guardians were introduced to the out-patient therapeutic nutrition centre or hospital nutrition facility according to their severity.

Results

A total of 830 patients were admitted to the paediatric general ward in SMH during the study period. Among them, 516 children were eligible, and complete anthropometric measurement data could be collected from 426 children at admission and discharge (Fig. 1). The demographic characteristics of the children are shown in Table 1. Median age was 26 months (IQR: 13–49), and 59.4% were male.

Fig. 1
figure 1

Flowchart showing the number of children from admission to enrolment

Table 1 Characteristics of children enrolled in the study

Prevalence of wasting, underweight and stunting at the time of admission and discharge are shown in Table 2. There was no significant change in any nutritional parameter during the hospital admission. Among the 426 children, care providers, including doctors identified 2 cases of malnutrition (wasting or underweight or stunting) compared to 112 cases by the systematic anthropometric measurement at admission (% of agreement = 74.2%; Cohen’s k = 0.02) and 4 cases compared to 119 cases by the anthropometric measurement (% of agreement = 72.5%; Cohen’s k = 0.02) at discharge. The Cohen’s kappa shows the slight agreement. The systematic anthropometric measurement identified far more numbers of wasting cases than the simple observation of doctors and nurses. Out of 39 children who were identified as wasting at admission, 12 (30.8%) improved to be normal at discharge; while 387 children who were identified as not-wasting (normal) at admission, 9 (2.3%) deteriorated to be wasting at discharge. All malnourished children were given nutritional counselling at the hospital, and severely malnourished cases were referred to a nutritional rehabilitation centre.

Table 2 Nutritional status of children at the time of admission and at discharge in Siddhi Memorial Hospital

Univariable and multivariable analyses showed children from minor ethnic group (Others, aOR: 3.6, 95% CI 1.2–10.8), children from earthquake affected home (aOR: 2.6, 95% CI 1.1–6.3), and with respiratory diseases (aOR: 3.4, 95% CI 1.4–8.1) diarrhoea diseases (aOR: 4.0, 95% CI 1.3–11.8) were at risk of wasting (Table 3). Childrens’ age group, sex, residence, mother’s age, mother’s education and source of drinking water were not associated.

Table 3 Risk factors associated with wasting in hospitalised children after 2015 earthquake in Bhaktapur, Nepal

There were 34 children from the ethnic minorities, which included Rai, Bishwokarma, Damai, Nepali, Majhi, Sewa, Thakuri, Limbu, Dalit, Tharu, Puri, Giri, Bangali, Gurung, Sanyashi. Newars were the major ethnic group in the community, which constituted 35.7% of children in the study. Comparisons between the minor ethnic group with the Newars are shown in Table 4. Children in the minority group were younger (78.4% vs 42.1% in 6–23 months age group), a higher proportion of them were from out of Bhaktapur, a lower proportion of their mothers went to university, had less private water source, and had higher proportions of wasting and underweight than those of children from the Newars (Table 4). This shows there were significant differences in socioeconomic and nutritional characteristics of children who came from the minor and the major ethnic groups.

Table 4 Comparing characteristics of children from a major ethnic group (Newars) and a group of the ethnic minorities

Discussion

In this cross-sectional study, conducted 18 months after the 2015 Nepal Earthquake, the prevalence of wasting among hospital admitted children was 9.2% at admission and 8.5% at discharge. Children from minor ethnic groups, children with respiratory infections, diarrhoeal disease, and whose house was damaged due to the earthquake were associated with wasting. Care providers, including medical doctors in routine care could only identify 2 out of 112 children with malnutrition at admission and 4 out of 119 children with malnutrition at discharge. This corresponds to 98.2% of cases missed at admission and 96.6% of cases not identified at discharge.

The prevalence of malnutrition among the study population at admission was wasting 9.2%, stunting 19.0% and underweight 15.3% which were lower than the national average of wasting 10%, stunting 36% and underweight 27% [11]. This is because our study population is from the Kathmandu valley where probably the access to food is better than the rural areas of Nepal. The prevalence of wasting in hospital-based study conducted in Brazil, Romania and Vietnam report 16.1%, 17.7% and 19.0%, respectively [4, 12, 13]. Compared with the national average of prevalence of wasting 1.6% in Brazil, 3.3% in Romania and 5.7% in Vietnam, hospitalised children were more likely to have wasting than non-hospitalised children [14]. Studies from Tanzania and Burkina Faso report the prevalence of malnutrition in hospitals were comparable to the national averages [15, 16]. These findings are comparable with the findings obtained from our study.

Our risk factor analysis for wasting showed that the children from minority ethnic group, whose house was damaged due to the earthquake, and who had respiratory or diarrhoeal diseases were independently associated with wasting. The minority ethnic group consisted of various minorities, such as Rai, Bishwokarma, Damai, Nepali, Majhi, Sewa, Thakuri, Limbu, Dalit, Tharu, Puri, Giri, Bangali, Gurung, Sanyashi. When minority ethnic group was compared with the Newars group, a major ethnic group in Bhaktapur, we found a less proportion of the mothers in minority ethnic group had university education as compared to Newars group. The proportions of children with wasting and underweight were significantly higher in minority ethnic group than that of Newars group. Previous studies from Nepal have also shown that lower mother’s education and ethnic minority are associated with underweight and stunting [17, 18]. Similarly, studies in other countries have shown that lower mother’s education and minor ethnicity can be a risk of malnutrition [19, 20]. Therefore, it is important that public health programmes should consider a targeted approach for the children with mothers with lower educational attainment and as well as ethnic minorities in the community.

In this study, diarrhoeal diseases and respiratory infections were associated with malnutrition. Malabsorption and nutrient loss occur during diarrhoea, which results in the deterioration of nutritional status of children. Recurrent infections, such as intestinal parasitic infections and diarrhoeal diseases, are causes of undernutrition in children. There is a risk of a vicious cycle of diarrhoea and malnutrition: repeated attacks of diarrhoea and infections leads to weight loss and compromise a child’s nutritional status, which makes the child vulnerable to infections and cause further weight loss, eventually leading to severe malnutrition unless the cycle is stopped [21, 22]. Association of malnutrition and respiratory infections in children is well known, and the association increases the risk of death [23, 24]. Malnourished children have deranged immune system; therefore, viral and bacterial pathogens can easily cause various infections, including the respiratory infections. Therefore, it is important to suspect and treat respiratory infections in malnourished children [25].

Malnutrition is viewed as one of the five major adverse health impacts of climate change and disaster [26]. Several studies showed deterioration of nutritional status of children after a huge disaster, irrespective of disaster type. In this study, children whose houses had suffered damage were at higher risk of wasting compared to the children whose house got no damage. A nutritional survey conducted 1 year after the Wenchuan Earthquake, China, reports higher prevalence of malnutrition [27]. There can be various reasons behind the causes of malnutrition in natural disasters. Some of them include nutrition insecurity, loss of income, damage to crops and death of livestock [28, 29]. Pörtner et al. points out a prolonged stay in temporary shelters can be a risk for malnutrition as it is not a secure place for breastfeeding because of lack of privacy [8].

In this study, care providers, including medical doctors, could identify 2 cases of malnutrition out of 112 at the time of admission and 4 cases out of 119 cases at the time of discharge by clinical observation alone. Thus, just depending on the clinical observations, many cases of malnutrition can be missed despite the chance to be examined by health care providers; similar findings were observed in other studies too [30, 31]. The research team presented these findings to the doctors and administrative staff in the hospital. Later, the hospital started the systematic anthropometric measurement of all admitted children to screen for malnutrition.

This study has limitations. We could not enrol all the children who were admitted to hospital. Some children, who had serious conditions, including sepsis and severe pneumonia that might have partly contributed to malnutrition. The study could not be conducted over a period of a year; so, we could not analyse any variation of nutritional status according to seasons of admission. Similarly, we could not analyse micronutrient deficiencies.

In conclusion, this study found that malnutrition among hospitalised children was associated with ethnic minority, diarrhoeal diseases, respiratory infections, and earthquake damage to house. Malnutrition remains an unrecognised problem among hospital admitted children. Due to lack of the systematic anthropometric measurement at the hospital at the time of this study, health care providers did not identify most malnutrition cases. This was a missed opportunity for identification, treatment and prevention of malnutrition, which could have multifaceted effects on children’s physical, mental and social developments. Therefore, health care facilities should provide the systematic anthropometric measurement to all hospital admitted children.

Availability of data and materials

De-identified data of this study are available upon reasonable request from the corresponding author.

Abbreviations

BMI:

Body mass index

CDC:

Centers for Disease Control and Prevention, USA

MUAC:

Mid upper-arm circumference

SMH:

Siddhi Memorial Hospital

UNICEF:

The United Nations Children's Fund

WHO:

World Health Organization

WHZ:

Weight-for-height Z-score

References

  1. Malnutrition. 2021. https://data.unicef.org/topic/nutrition/malnutrition/.

  2. UNICEF. Facts for life. 2010.

  3. Antwi S. Malnutrition: missed opportunities for diagnosis. Ghana Med J. 2008;42(3):101–4.

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Pileggi VN, Monteiro JP, Margutti AV, Camelo JS Jr. Prevalence of child malnutrition at a university hospital using the World Health Organization criteria and bioelectrical impedance data. Braz J Med Biol Res. 2016;49(3):e5012.

    Article  Google Scholar 

  5. Kyle UG, Schneider SM, Pirlich M, Lochs H, Hebuterne X, Pichard C. Does nutritional risk, as assessed by Nutritional Risk Index, increase during hospital stay? A multinational population-based study. Clin Nutr. 2005;24(4):516–24.

    Article  Google Scholar 

  6. Chisti MJ, Graham SM, Duke T, Ahmed T, Faruque AS, Ashraf H, et al. Post-discharge mortality in children with severe malnutrition and pneumonia in Bangladesh. PLoS ONE. 2014;9(9): e107663.

    Article  Google Scholar 

  7. Dhoubhadel BG, Raya GB, Shrestha D, Shrestha RK, Dhungel Y, Suzuki M, et al. Changes in nutritional status of children who lived in temporary shelters in Bhaktapur municipality after the 2015 Nepal earthquake. Trop Med Health. 2020;48:53.

    Article  Google Scholar 

  8. Pörtner CC. Natural hazards and child health. Available at SSRN 1599432. 2010.

  9. Unicef. Tracking progress on child and maternal nutrition. 2009.

  10. Forman MR, Zhu Y, Hernandez LM, Himes JH, Dong Y, Danish RK, et al. Arm span and ulnar length are reliable and accurate estimates of recumbent length and height in a multiethnic population of infants and children under 6 years of age. J Nutr. 2014;144(9):1480–7.

    Article  CAS  Google Scholar 

  11. Ministry of Health - MOH/Nepal NEN, and ICF. Nepal Demographic and Health Survey 2016. 2017.

  12. Mărginean O, Pitea AM, Voidăzan S, Mărginean C. Prevalence and assessment of malnutrition risk among hospitalized children in Romania. J Health Popul Nutr. 2014;32(1):97–102.

    PubMed  PubMed Central  Google Scholar 

  13. Huong PT, Lam NT, Thu NN, Quyen TC, Lien DT, Anh NQ, et al. Prevalence of malnutrition in patients admitted to a major urban tertiary care hospital in Hanoi, Vietnam. Asia Pac J Clin Nutr. 2014;23(3):437–44.

    PubMed  PubMed Central  Google Scholar 

  14. 2016 Global hunger index: Getting to zero hunger. 2016.

  15. Juma OA, Enumah ZO, Wheatley H, Rafiq MY, Shekalaghe S, Ali A, et al. Prevalence and assessment of malnutrition among children attending the Reproductive and Child Health clinic at Bagamoyo District Hospital, Tanzania. BMC Public Health. 2016;16(1):1094.

    Article  Google Scholar 

  16. Erismann S, Knoblauch AM, Diagbouga S, Odermatt P, Gerold J, Shrestha A, et al. Prevalence and risk factors of undernutrition among schoolchildren in the Plateau Central and Centre-Ouest regions of Burkina Faso. Infect Dis Poverty. 2017;6(1):17.

    Article  Google Scholar 

  17. Karkuki Osguei N, Mascie-Taylor CN. Association of nutritional status with socio-economic and demographic variables of under five year old Nepalese children. Med J Islam Repub Iran. 2019;33:28.

    PubMed  PubMed Central  Google Scholar 

  18. Devakumar D, Kular D, Shrestha BP, Grijalva-Eternod C, Daniel RM, Saville NM, et al. Socioeconomic determinants of growth in a longitudinal study in Nepal. Matern Child Nutr. 2018;14(1):e12462.

    Article  Google Scholar 

  19. Phengxay M, Ali M, Yagyu F, Soulivanh P, Kuroiwa C, Ushijima H. Risk factors for protein-energy malnutrition in children under 5 years: study from Luangprabang province, Laos. Pediatr Int. 2007;49(2):260–5.

    Article  Google Scholar 

  20. Pei L, Ren L, Yan H. A survey of undernutrition in children under three years of age in rural Western China. BMC Public Health. 2014;14:121.

    Article  Google Scholar 

  21. Tette EM, Sifah EK, Nartey ET. Factors affecting malnutrition in children and the uptake of interventions to prevent the condition. BMC Pediatr. 2015;15:189.

    Article  Google Scholar 

  22. Schlaudecker EP, Steinhoff MC, Moore SR. Interactions of diarrhea, pneumonia, and malnutrition in childhood: recent evidence from developing countries. Curr Opin Infect Dis. 2011;24(5):496–502.

    Article  Google Scholar 

  23. Karunaratne R, Sturgeon JP, Patel R, Prendergast AJ. Predictors of inpatient mortality among children hospitalized for severe acute malnutrition: a systematic review and meta-analysis. Am J Clin Nutr. 2020;112(4):1069–79.

    Article  Google Scholar 

  24. Zabihullah R, Dhoubhadel BG, Rauf FA, Shafiq SA, Suzuki M, Watanabe K, et al. Risk for death among children with Pneumonia, Afghanistan. Emerg Infect Dis. 2017;23(8):1404–8.

    Article  Google Scholar 

  25. Chisti MJ, Tebruegge M, La Vincente S, Graham SM, Duke T. Pneumonia in severely malnourished children in developing countries—mortality risk, aetiology and validity of WHO clinical signs: a systematic review. Trop Med Int Health. 2009;14(10):1173–89.

    Article  Google Scholar 

  26. IPCC, 2012: Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK, and New York, NY, USA; 2012.

  27. Dong C, Ge P, Ren X, Zhao X, Wang J, Fan H, et al. The micronutrient status of children aged 24–60 months living in rural disaster areas one year after the Wenchuan Earthquake. PLoS ONE. 2014;9(2): e88444.

    Article  Google Scholar 

  28. Phalkey RK, Aranda-Jan C, Marx S, Höfle B, Sauerborn R. Systematic review of current efforts to quantify the impacts of climate change on undernutrition. Proc Natl Acad Sci USA. 2015;112(33):E4522–9.

    Article  CAS  Google Scholar 

  29. Pradhan PM, Dhital R, Subhani H. Nutrition interventions for children aged less than 5 years following natural disasters: a systematic review protocol. BMJ Open. 2015;5(11): e009525.

    Article  Google Scholar 

  30. Gout BS, Barker LA, Crowe TC. Malnutrition identification, diagnosis and dietetic referrals: are we doing a good enough job? Nutr Diet. 2009;66:206–11.

    Article  Google Scholar 

  31. Lazarus CHJ. Prevalence and documentation of malnutrition in hospitals: a case study in a large private hospital setting. Nutr Diet. 2005;62:41–7.

    Article  Google Scholar 

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Acknowledgements

We would like to thank the children and their parents who participated in this study. We are grateful to Mr. Shyam S Dhaubhadel for the permission to conduct this study in the hospital, and to Ms. Sarmista Jakibanjar, Ms. Suruchi Dhoubhadel, and Raj Shrestha for their help in the data collection and data entry.

Funding

This study was funded by the School of Tropical Medicine and Global Health (TMGH), Nagasaki University, Nagasaki, Japan, and partly by the Kakenhi Grant (22K15924) from Japan Society for the Promotion of Science (JSPS).

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Authors

Contributions

SEC and BGD designed the study. AI, DS, GBR, and SS collected the data and administered the study. AI, BGD, and TE did the data analysis and AI prepared the first draft of the manuscript. YH, SEC, CMP, and KA reviewed the manuscript. All authors contributed to the writing of the final manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Bhim Gopal Dhoubhadel.

Ethics declarations

Ethics approval and consent to participate

Ethical approvals were obtained to conduct this study from Nepal Health Research Council, Kathmandu, Nepal (Reg. no. 265/2016), and School of Tropical Medicine and Global Health (Approval Ref no. 4). Informed written consent was obtained from the parents of the children, and if children were more than 10 years old, a written assent was obtained to enrol the children in the study.

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Not applicable.

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The authors declare that they have no competing interests.

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Inoue, A., Dhoubhadel, B.G., Shrestha, D. et al. Risk factors for wasting among hospitalised children in Nepal. Trop Med Health 50, 68 (2022). https://doi.org/10.1186/s41182-022-00461-0

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