The prevalence of malnutrition based on anthropometry among primary schoolchildren in Binh Dinh province, Vietnam in 2016

Dat, Truong Quang; Giang, Le Nguyen Huong; Loan, Nguyen Thi Tuong; Toan, Vo Van

doi:10.3934/publichealth.2018.3.203

Cited by 8 publications

(7 citation statements)

References 16 publications

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“…A randomized controlled trial [ 29 ] in India to determine impact of nutritional education/ counselling proved that counselling provided by health care workers through existing primary healthcare services was effective in improving anthropometry, reducing illness episodes and increasing daily calorie intake in all groups enrolled. Which was also observed in a Vietnamese study by Pachon [ 19 ] 105 children with mild malnutrition at inclusion, reduced to 82 while 4 entered the normal category. Their mean daily calorie, protein intake increased.…”

Section: Discussionsupporting

confidence: 69%

“…Socioeconomic inequality in malnutrition among children has been documented by various studies from India [ 16 ], South Africa [ 17 ], China [ 18 ] and Ghana [ 8 ]. A Vietnamese study, reported highest prevalence of adverse nutritional status in socio economically deprived mountainous, midland areas [ 19 ]. A Nigerian study reported that childhood malnutrition was associated with poor socioeconomic status, defined by poor maternal income and their dwelling type was in a 1-bedroom household [ 20 ].…”

Section: Discussionmentioning

confidence: 99%

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Effect of nutritional counselling for using anthropometric indices among Indians

Chavan¹

2022

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Malnutrition in children under 5 years is a major public health problem in developing countries. Malnutrition complex comprises of under-nutrition including multiple conditions like acute, chronic malnutrition, micronutrient deficiencies and nutrition related to obesity. Therefore, it is of interest to report data on the individualized nutritional counselling on nutritional status among mild to moderately malnourished children aged 2 – 5 years at one, three and six month follow up. Their dietary habits will help to determine the aetiology of mild/moderate malnutrition.150 Children attending outpatient department of the Department of Paediatrics of D Y Patil Medical College and admitted with mild/moderate malnutrition were included in the study after taking informed consent from their parents. The children were randomly allocated into 4 groups (group 1 – 4). The groups consisted of children where dedicated nutritional counselling was provided at 1 month, 1 and 3 month follow up and where-in no dedicated counselling was provided. A diet chart was provided with counselling. Group 4 followed up with routine care without any dietary intervention. Detailed dietary, socio economic history, clinical examination with anthropometry was done followed-up at 1, 3, 6 months from date of inclusion. Majority (57.3%) belonged to lower socio-economic class according to Kuppuswamy scale. The mean birth weight was 2.4 kg, age 34.5 months and age of weaning 7.6 months. Data shows that 70% children had mild malnutrition and 30% moderate malnutrition. At 6 month follow up amongst 105 children with mild malnutrition, 82 still had mild malnutrition, 4 normal, 19 had moderate malnutrition. Under-five childhood malnutrition is highly prevalent in poor socioeconomic strata of the society. Nutritional counselling provided by trained healthcare providers in existing settings are effective in improving nutritional status, daily calorie/protein intake, prevention of malnutrition. Prevention/treatment of co-existing illness bears equal importance.

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Section: Discussionsupporting

confidence: 69%

Section: Discussionmentioning

confidence: 99%

Effect of nutritional counselling for using anthropometric indices among Indians

Chavan¹

2022

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“…Malnutrition is a general term that refers to two distinct conditions as under-nutrition and overweight. Undernutrition includes stunting, wasting, and being underweight, whereas overweight/obesity is associated with a number of non-communicable diseases (diabetes, cancer, stroke, and heart disease) [ 1 – 3 ]. According to the WHO, approximately 1.9 billion adults worldwide were overweight, while 462 million were underweight.…”

Section: Introductionmentioning

confidence: 99%

“…There were lots of studies about U5 malnutrition around the world. In previous studies, they focused only on the identification of the risk factors of malnutrition using classical model like logistic regression [ 1 – 3 , 11 – 21 ]. Therefore, it is necessary to propose a predictive model on the identified the significant risk factors for predicting malnutrition.…”

Section: Introductionmentioning

confidence: 99%

Investigate the risk factors of stunting, wasting, and underweight among under-five Bangladeshi children and its prediction based on machine learning approach

et al. 2021

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Aims Malnutrition is a major health issue among Bangladeshi under-five (U5) children. Children are malnourished if the calories and proteins they take through their diet are not sufficient for their growth and maintenance. The goal of the research was to use machine learning (ML) algorithms to detect the risk factors of malnutrition (stunted, wasted, and underweight) as well as their prediction. Methods This work utilized malnutrition data that was derived from Bangladesh Demographic and Health Survey which was conducted in 2014. The selected dataset consisted of 7079 children with 13 factors. The potential risks of malnutrition have been identified by logistic regression (LR). Moreover, 3 ML classifiers (support vector machine (SVM), random forest (RF), and LR) have been implemented for predicting malnutrition and the performance of these ML algorithms were assessed on the basis of accuracy. Results The average prevalence of stunted, wasted, and underweight was 35.4%, 15.4%, and 32.8%, respectively. It was noted that LR identified five risk factors for stunting and underweight, as well as four factors for wasting. Results illustrated that RF can be accurately classified as stunted, wasted, and underweight children and obtained the highest accuracy of 88.3% for stunted, 87.7% for wasted, and 85.7% for underweight. Conclusion This research focused on the identification and prediction of major risk factors for stunting, wasting, and underweight using ML algorithms which will aid policymakers in reducing malnutrition among Bangladesh’s U5 children.

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“…The stunting malnutrition prevalence has also declined from 29.3% to 24.2% (2010)(2011)(2012)(2013)(2014)(2015). While underweight has dropped rapidly (> 60%) compared to 1990, the obesity prevalence in children (< age 5) is growing rapidly [6].…”

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confidence: 99%

Family-Centered Care - A Tool to Decrease Malnutrition among Children in Vietnam

Anna¹,

Hedvig²,

Rosengren³

2019

Int Arch Nurs Health Care

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five years are underweighted, 24.6% of them suffered from "stunting" (reduced median length to age), and 6.4% had "wasting" (reduced median weight to the length). Though nurses has an important role to prevent malnutrition and/or alleviate suffering, current study aims to broaden knowledge regarding malnutrition among children by adding forthcoming nurses (nursing student's) perspective. BackgroundMalnutrition is a worldwide problem [1] due to underweighted (lack of food, beverages) as well as over weighted (cheap food, beverages with fat, salt, sugar). United Nations Millennium Development Goal 1 declare to fight poverty in which hunger and malnutrition are included [2]. Malnutrition among children is described in relation to weight and length. "Wasting" are described as a child's median weight deviates to length with two standard deviations, stunting are median length deviates with two standard deviations in relation to age [3,4]. Huong, et al. [5] described that 13.9% of all Vietnam children in hospital suffered from "stunting" and 19.0% of "wasting". Moreover, Truong Quang Dat, et al. [6] show downward trend regarding prevalence of malnutrition from 17.5% in 2010 to 14.1% in 2015 with expectancy to decline even more. The stunting malnutrition prevalence has also declined from 29.3% to 24.2% (2010)(2011)(2012)(2013)(2014)(2015). While underweight has dropped rapidly (> 60%) compared to 1990, the obesity prevalence in children (< age 5) is growing rapidly [6].

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The prevalence of malnutrition based on anthropometry among primary schoolchildren in Binh Dinh province, Vietnam in 2016

Cited by 8 publications

References 16 publications

Effect of nutritional counselling for using anthropometric indices among Indians

Effect of nutritional counselling for using anthropometric indices among Indians

Investigate the risk factors of stunting, wasting, and underweight among under-five Bangladeshi children and its prediction based on machine learning approach

Family-Centered Care - A Tool to Decrease Malnutrition among Children in Vietnam

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