




































BANGLADESH JOURNAL OF MULTIDISCIPLINARY SCIENTIFIC RESEARCH 7(1) (2023), 11-21 

11 

  

     MULTIDISCIPLINARY SCIENTIFIC RESEARCH 

 
        BJMSR VOL 7 NO 1 (2023)  P-ISSN 2687-850X  E-ISSN 2687-8518 

 
        Available online at https://www.cribfb.com 

     Journal homepage: https://www.cribfb.com/journal/index.php/BJMSR 

                                                                                                                                                                                                    Published by CRIBFB, USA 

                                                                                                                                            

MATERNAL NUTRITIONAL KNOWLEDGE AND DETERMINANTS OF 

THE CHILD NUTRITIONAL STATUS IN THE NORTHERN REGION OF 

BANGLADESH                
 

 Bilkish Banu (a)1   Sadika Haque (b)    Shamim Ara Shammi (c)    Md. Anowar Hossain (d) 
 

(a)Assistant Professor, Department of Economics, Faculty of Social Science and Humanities, Hajee Mohammad Danesh Science & Technology University,  

Dinajpur, Bangladesh; E-mail: bilkishbanuu@gmail.com 
(b)Professor, Department of Agricultural Economics, Faculty of Agricultural Economics & Rural Sociology, Bangladesh; E-mail: 

sadikahaque@yahoo.com 
(c) Assistant Manager (HR and Training), Service Solutions Pvt. Ltd., Bangladesh; E-mail: shamim.a.shammi@gmail.com 
(d) MSS Student, Department of Economics, Faculty of Social Science and Humanities, Hajee Mohammad Danesh Science & Technology University, 

Dinajpur, Bangladesh; E-mail: rajuhstu2@gmail.com 

 

 
A R T I C L E I N F O 

 
 

Article History: 
 

Received: 2nd March 2023  

Revised: 27th April 2023 

Accepted: 25th May 2023 

Published: 7th June 2023 

 
Keywords: 

 

Maternal Knowledge, Child Nutrition,  

Bivariate Analysis, Antenatal Care, 

Nutritional Knowledge 

 
JEL Classification Codes: 

 

C13, C25, C51, J13, I12, I15 

 

 
 

 

  

 
A B S T R A C T 

 
This present study investigates the factors that affect child nutrition and the status of maternal 
Knowledge in the northern region of Bangladesh. For this purpose, this study employs a cross-sectional 

data survey of two divisions in the northern region of Bangladesh, namely Rangpur and Rajshahi, from 

which three districts were chosen from each division using a simple random sampling process. This 

survey collected data from 527 respondents with face-to-face direct interview method. The questionnaire 

is in the native language for their understanding. This study applies Weight for Age, Height for Age, 

Weight for Height, and Weight for Height for the nutritional status of children. This study uses bivariate 

logistic analysis for factor analysis and descriptive analysis for mothers' nutritional Knowledge. The 
result shows that sanitation, mothers' Employment, maternal nutritional Knowledge, wealth index, 

maternal educational status, and antenatal care are the key significant determinants of child nutritional 

status. In addition, this study also reveals that only 30% of the total respondents were aware of the 

child's nutritional status while feeding their children, that is 158 out of 537 mothers. The findings of this 

study indicate that improvement in the rate of a child's dietary diversity, women's dietary diversity, and 

also self-esteem leads to an improvement in the child's nutritional status in a significant manner. It also 

indicates that moving towards an upward ceiling for cases including compulsory higher education for 

women, spreading awareness about child nutritional issues, and prohibiting child marriage and early 
premature pregnancy may enhance sustaining lives for them. 

 
 

© 2023 by the authors. Licensee CRIBFB, USA. This open-access article is distributed under the terms 
and conditions of the Creative Commons Attribution (CC BY) license 
(http://creativecommons.org/licenses/by/4.0/).  

            

 

INTRODUCTION 

Mothers are the primary caregivers for their children, and the quality of care they provide is heavily reliant on their 

understanding of nutrition and health-related behaviors. Early childhood malnutrition has a complicated, multivariate, and 

contextual etiology. The direct cause of childhood malnutrition is a lack of protein and energy; however, behind these 

deficiencies lurk many other factors that influence newborn feeding behaviors and, consequently, their nutritional status and 

health. The study of nutrition focuses on how food affects the body. The components of food that are good for our bodies 

include vitamins, protein, minerals, fats, and more. The total promotion of children's growth and development is called child 

nutrition. Children of today will be tomorrow's adults. We all hope these young adults will blossom into flowers in the 

future. Child malnutrition is the most important factor contributing to child morbidity and mortality, among other factors. 

According to UNICEF, inadequate dietary intake, infectious disease, or a combination of both is called malnutrition. 

Stunting, wasting, and underweight is the three common indicators of malnutrition. Based on the global nutrition report 

2020 and World Bank Group 2021 information 2000, the country had 51% of children stunted, 12.5% wasted, and 42.4% 

underweight. In 2005, stunting 45.9%, 11.8% were wasted, and 37.3% were underweight. However, stunting and 

                                                      
1Corresponding author: ORCID ID: 0009-0003-0579-8568 
© 2023 by the authors. Hosting by CRIBFB. Peer review under the responsibility of CRIBFB, USA.  

https://doi.org/10.46281/bjmsr.v7i1.2018 

 
To cite this article: Banu, B., Haque, S., Shammi, S. A., & Hossain, M. A. (2023). MATERNAL NUTRITIONAL KNOWLEDGE AND 

DETERMINANTS OF THE CHILD NUTRITIONAL STATUS IN THE NORTHERN REGION OF BANGLADESH. Bangladesh Journal of 

Multidisciplinary Scientific Research, 7(1), 11-21. https://doi.org/10.46281/bjmsr.v7i1.2018 

http://creativecommons.org/licenses/by/4.0/)
http://creativecommons.org/licenses/by/4.0/)
https://doi.org/10.46281/bjmsr.v7i1.2018
https://orcid.org/0009-0003-0579-8568
https://orcid.org/0000-0003-3675-275X
https://orcid.org/0009-0009-6922-0187
https://orcid.org/0009-0008-9848-1987


Banu et al., Bangladesh Journal of Multidisciplinary Scientific Research 7(1) (2023), 11-21 

 

12 

underweight fell slightly in 2011, 41.3% and 36.7%, respectively. The prevalence of wasting had increased by 15.7% in that 

year. However, a declining trend was found in 2014, where 36.2%, 14.4%, and 32.8% child were stunted, wasted, and 

underweight, respectively. Lastly 2018, 30.8% of children were found stunted, 8.4% were wasted, and 22.6% were 

underweight. In the first decade of this century, all three indicators of malnutrition have shown fluctuation (sometimes fall, 

sometimes rise). Still, a declining trend was found with less fluctuation in the last decade. Bangladesh has the biggest 

malnutrition problem in the world. Poverty, family instability, poor environmental sanitation, faulty weaning practice, 

illiteracy, family food insecurity, etc., are the main cause of this problem. Being underweight, malnutrition, Anaemia or 

Iron deficiency, dental issues, etc., are widespread problems for a developing country like Bangladesh. Good nutrition is 

essential for every child to achieve physical and developmental potential. In urban areas with working mothers, the children 

are more affected by malnutrition problems than others. Malnutrition makes children more vulnerable to morbidity and 

mortality. similarly, the effects of malnutrition are; poorer educational attainment, delayed mental development, and lower 

intellectual and physical abilities in adult life. Child malnutrition has been linked with demographic and environmental 

aspects, socio-economic aspects, parental characteristics, household possession, and geographical location. While there are 

various theories, facts, and arguments about child malnutrition but some basic factors that are completely consistent with 

malnutrition, like mothers' age, education, socio-economic status, household size, hygiene, sanitation, BMI, access to control 

over resources, exposure to media, empowerment, fathers' education, occupation, child age, birth order, feeding practice, 

sex, mothers' Knowledge, religion, region of residence, etc. If the mother does not have enough knowledge about nutrition 

and does not know how to take care of her children, then there is a lot of chance of facing malnutrition by the children, 

especially the infant. Poor nutritional status was higher in families with low socio-economic status, less maternal educational 

level, and not having exclusive breastfeeding. If the children of a country don't have good health conditions, the country's 

future will be dark. That's why every developing country tries hard to use the population as human capital. According to 

Bangladesh Demographic and Health Survey (BDHS), child mortality differs from region to region. If we want to minimize 

the problem of malnutrition in our country, we need proper nutritional Knowledge and behavior toward children. Women's 

nutritional Knowledge and child malnutrition are the usual phenomena for the people of Bangladesh. These two factors are 

interrelated and cannot be isolated from each other. These two phenomena can be analyzed systematically. Now, it's time 

to cover the above aspects and emphasize the present context of Bangladesh. This study tries to identify the significant 

factors that affect the child's nutritional status in accordance with the maternal Knowledge of child nutrition in the northern 

region of Bangladesh. This study also aims at identifying the present status of the mother's nutritional Knowledge for rearing 

children in the northern region of Bangladesh. This study uses a bivariate regression model to identify the factors affecting 

the child's nutritional Knowledge. The next sections of this study are organized as a literature review, which describes the 

prior research on this subject, and the third component, materials, and methods, discusses the analytical techniques used to 

achieve the study's goals. The study's results are revealed in the fourth and last section, which also discusses the findings. 

The study's conclusion section follows, summarizing the entire report and describing the potential for further research. 
 

LITERATURE REVIEW 

Özdoğan et al. (2012) conducted a study on mothers' nutrition knowledge with children aged between 0-24 months. In this 

study, it was observed that nutritional Knowledge declined with the increasing number of children. Mothers' educational 

status is a factor that influences the child's nutritional status and life expectancy. Female literacy is a non-health factor 

influencing child survival and better nourishment. Mothers included in the study had a good level of nutritional Knowledge. 

The knowledge scores increase in similarity with the educational level, which reveals the significance of education. Debela 

et al. (2017) have accomplished a study on maternal nutrition knowledge and child nutritional outcomes in urban Kenya. 

These findings imply that building broader awareness of the health risks of unsuitable dietary practices among mothers and 

caretakers is important for improving the nutrition and health of children and adolescents. The result shows that maternal 

nutrition knowledge – measured through an aggregate knowledge score – is positively associated with child stunting (HAZ), 

even after controlling for other influencing factors such as household living standards and general maternal education. 

However, disaggregation by type of Knowledge reveals essential differences. Maternal Knowledge about food ingredients 

has a weak positive association with child HAZ. For maternal Knowledge about specific dietary recommendations, no 

significant association is detected. The strongest positive association with child HAZ is found for maternal Knowledge 

about the health consequences of not following recommended nutritional practices. These findings have direct relevance for 

nutrition and health policies, especially for designing the contents of educational campaigns and training programs. 

Schooling as inputs to child nutrition. Many find that mothers lack formal education also. Akeredolu et al. (2014) have 

accomplished a study on mothers' nutritional Knowledge, infant feeding practice, and nutritional status of children in Lagos 

state, Nigeria. The result indicated that the mothers' nutritional Knowledge, as revealed by the test score, was moderately 

good. It is recommended that the period of maternity leave should be increased. Women of childbearing age should be 

knowledgeable by trained nutritionists on the types of locally accessible foods that help growth in children. The study 

provides the level of breastfeeding, mothers' nutrition knowledge, complementary feeding practices, and the nutritional 

status of children (0-24 months) in Lagos state. Shrestha et al. (2021) conducted a study investigating household food 

security and its influence on the nutritional status of children under five. It has been found from the survey that food 

insecurity and malnutrition among under-five-year-old children were high in the study areas; more than half of the 

households were facing food insecurity, and nearly one-third of children were suffering from malnutrition. The prevalence 

of malnutrition among under-five-year-old children was associated with exclusive breastfeeding, initiation time of 

complimentary food, and household food security status.  

Lestari and Setyawan (2021) carried out a study that aimed to determine factors associated with the nutritional 

status of children under five years using holistic-comprehensive approaches. The authors revealed that poor nutritional 



Banu et al., Bangladesh Journal of Multidisciplinary Scientific Research 7(1) (2023), 11-21 

 

13 

quality was higher in families with low socio-economic status, less maternal education, and no exclusive breastfeeding. This 

approach also appraised bio-psychosocial aspects of nutritional issues and could help physicians to determine all factors 

related to the nutritional status of children under five years old. Siregar (2020) conveyed a study to analyze the nexus 

between maternal characteristics and parenting factors for children and how these were related to malnutrition in children 

under five in the Deli Serdang Regency. The result revealed a relationship between maternal characteristics (education, 

income, Knowledge) and parenting factors (the practice of feeding, health practices) with the incidence of child malnutrition 

in those under five. The study showed that education, income, low Knowledge, poor diet, and health patterns were the 

primary causes of child malnutrition among those under five. Mondal and Paul (2020) conducted a study to know the current 

scenario of malnourished children through 3 indicators- stunting, underweight, and wasting across Indian states. 

However, the children whose mothers were fully exposed to mass media like newspapers/radio/television had a 

lower prevalence of undernutrition, and the children belonging to the poorest household were twice times undernourished 

than those from the richest. Similarly, anemic children were 1.4 times more likely to be malnourished than non-anemic. 

Here also estimated that male children were more malnourished than females. The children suffering from diarrhea were 

more malnourished than non-diarrheal. Likewise, mothers who have completed more than four ANC visits in the hospital 

their children were less undernourished. A study was conducted by Kehinde and Favour (2020) to evaluate the state of 

household food insecurity, dietary diversity of households, nutritional status of households, and, similarly, the relationship 

between food insecurity and nutritional indices of households in that region. From the result, it had been claimed that a large 

percentage of households suffered from food insecurity with moderate hunger and low diet diversity. 

Furthermore, stunting was the most dominant form of malnutrition among children. Here, Food insecurity was 

inversely and significantly associated with income and formal education. Also, food insecurity was correlated to nutritional 

status, household diet diversity, stunting, and wasting. 

Tesfa et al. (2022) assessed a study on nutritional Knowledge, practice, and its related factors of pregnant women 

in Addis Ababa, Ethiopia, where they conducted their study on 363 women and used multivariate logistic regression. They 

showed that maternal Knowledge was 73.9% and dietary practice was 63.9%. They also identified family size, monthly 

income, pregnancy interval, ANC visit and BMI, husband's occupational status, and educational level as the significant 

factors affecting women's nutritional Knowledge. Wahid et al. (2021) tried to identify the factors affecting the child's 

nutritional status in Bangladesh. They used data from Bangladesh Household Expenditure Survey and conducted a study on 

10780 students. They applied the Blinder Oaxaca decomposition approach to identify the factors and found that household 

diets and environmental factors were significant. Berhanu et al. (2023) conducted a study on the determinants of the child 

nutritional status of primary school students in Ethiopia. They surveyed a cross-sectional survey of 494 primary students 

and applied ordinary logistic regression analysis. The result showed that 27.94% of the primary students were 

undernourished consists of 7.29% were severely, and 20.65 were moderate. Mother's educational status was positively 

correlated with nutritional status, whereas large family size was detected as a negative influence on the child's nutritional 

status. 

Habiba et al. (2020) researched to determine the food and nutrition status among children in four selected slum 

areas of Khulna City. Household food security is categorized into mildly, moderately, and severely food insecure. The study 

found that approximately 34.5% of children were food secure, nearly 24.4% were found mildly food insecure, about 28.9% 

as moderately food insecure, and the rest were severely food insecure. The prevalence of wasting was 37.7%, whereas that 

of stunting and underweight was 28.9% and 40.7%. Girl children suffered from malnutrition, stunting, and wasting more 

than boys. Children's food security and nutrition status were stimulated by various socio-economic factors such as income 

level, expenditure on food, and parents' employment status. The morbidity status of the slum children was less, but the 

children had been suffering from various diseases. The above studies are concerned with the Western and Indian contexts. 

Still, this study was conducted in the southern region of Bangladesh, where the most vulnerable group was women, and this 

study also emphasized the socio-economic conditions. 

However, Several cross-sectional studies have been done in recent years, including Haq et al. (2021); Mengesha et 

al. (2021); Birhan and Belay (2021); Yisak et al. (2021); Berhanu et al. (2023) and Tesfa et al. (2022). None of them consider 

the district or rural level. In addition, in Bangladesh, rare studies have been found on the nutritional status, although the 

malnutrition problem is increasing daily. Moreover, the literature mentioned above did not reveal the details on the maternal 

nutritional status of the study areas. In this case, this study tries to cover up the gaps by conducting the study in the northern 

region of Bangladesh, which is also known for its higher poverty level in Bangladesh. 

  

MATERIALS AND METHODS 
Conceptual Framework 

The conceptual framework establishes how factors affect a child's nutrition. Maternal factors such as age, education, time 

allocation, age of first marriage, and age of first baby bore effect and women's empowerment and caregiver's status, affecting 

the child's nutritional status (Figure 1). Similarly, socio-economic status also influences the mothers' nutritional Knowledge, 

determining the child's health status level. Conversely, general awareness of hygiene, such as wash status, affects the 

nutritional quality of the mother, which again influences the child's nutritional status.  



Banu et al., Bangladesh Journal of Multidisciplinary Scientific Research 7(1) (2023), 11-21 

 

14 

 

Figure 1. Conceptual framework of the study 

 

Selection of the study area 

 

Figure 2. Selection of the study area 

 

We have selected eight districts of the northwest region (Naogaon et al.) for this study. 

 

Sampling Technique 

Due to time and resource constraints, it was impossible to conduct a women empowerment and child nutritional status-

related survey covering all households. Thus, in selecting samples for a study, two things need to be considered. The sample 

size should be as large as possible for adequate degrees of freedom in the statistical analysis. In other words, the 

administration of field research, processing, and data analysis should be manageable within the limits imposed by physical, 

human, and financial resources. A reasonable size of the sample to achieve the study's objectives was considered. A simple 

random sampling technique was used to obtain the sample size. The sample size was divided into two groups. One was 

taken from Rangpur district, and another from Rajshahi district. 291 samples were randomly collected from the Rajshahi 

district, whereas 246 were collected from the Rangpur district. This aggregate collection was also subdivided according to 

districts which are as follows: 

 

Table 1. Distribution of sample 

 
Division District Selected sample Percentage of the total sample 

Rajshahi Naogaon 43 9% 

Rajshahi 89 17% 

Sirajganj 74 14% 

Bogura 85 16% 

Rangpur Rangpur 72 13% 

Dinajpur 59 11% 

Gaibandha 60 11% 

Panchagarh 55 10% 

Total 537 100% 

 



Banu et al., Bangladesh Journal of Multidisciplinary Scientific Research 7(1) (2023), 11-21 

 

15 

Data Collection Procedure 
This study aims to find out the factors which affect children's nutritional status, the degree of women's empowerment, and 

its association with women from the northwest region of Bangladesh. To achieve the goal, data is being collected from 

mothers with children between 6 months to 5 years old. The data were collected from the female household members 

(generally the wives of the household heads). The interviews were conducted one by one and face-to-face with the 

respondents. Anthropometric measurements of the child and mother were recorded simultaneously. We have used tools and 

equipment like Questionnaire, Weight measurement machine, Height measurement wooden scale, steel tape, MUAC tape, 

Apron, One-time face masks, Hand gloves, Hand sanitizer, Liquid disinfectants, paper, pen, pencil, scale, and more. We 

maintained some criteria while collecting data which are as follows:  

 Only the mothers are interviewed as Biological children, not the foster children. 

 Single tone outcome child. 

 The women did not allow measuring their height, weight, and MUAC. 

 Child aged between 6-59 months. 

 We did not consider the families who lost their jobs during COVID-19 and were affected directly, as this year 

would be an abnormal year in their life. 

 Did not consider currently pregnant women. 

 

Data Processing 
After completing the data collection process, the data cleaning was started immediately. This cleaning process is slightly 

longer as the rest of the analysis mainly depends on the cleaned and adequately processed data. Most of the mistakes were 

made because of typing errors, information gaps, and incorrect formatting. All the data were corrected one by one. 

Afterward, all the data were stored in a separate EXCEL file, and made some copies so that those could be the backup. All 

the data were kept in a password-protected computer, which ensures the data's strong security. 

 

Analytical Techniques 

 To achieve the study's objectives and get a meaningful result, collected data were analyzed carefully. Descriptive statistic 

was used to analyze the socio-economic characteristics of the respondents. Different regression models were used to 

determine the relationship between women's empowerment and child nutritional status and identify factors affecting 

women's empowerment. 

 

Variable Specification 
Once the data cleaning and processing were done, variable specification and preparation were started, one of the most 

important parts of the research. Different types of composite variables were prepared which have relevance to this study, 

such as: 

 Household Food Variety (HFV) 

 Women's Dietary Diversity (WDD) 

 Child Dietary Diversity (CDD) 

 Women Empowerment Index 

Child Nutritional Status/ Anthropometry 

Among the several child anthropometries, we used weight-for-height, height-for-age, weight-for-age, Mid Upper Arm 

Circumference (MUAC). To collect all the required data, we used available WHO standard tools. Weight was measured in 

Kg, and height and MUAC were in cm. As we needed to standardize the analysis with WHO, we took the help of WHO 

Anthro software version 3.2.2, available on the WHO website. The advantage of this software is that it automatically counts 

the child's age at the interview date. So, the result is always accurate. 

On top of that, we changed the country of that software to Bangladesh to get accurate reference data, as the database depends 

on the geographic location. The Z score is the most common way to calculate the distance between the observed value and 

the value of the reference population. In other words, the Z score measures the dispersion of the data. We can calculate the 

Z score by the following formulas. Hence, we used software so we didn't need to calculate all the Z scores manually. 

Equation1: Z scores calculation 

 

 

Z Score = 
(Observed value−Expected value of Reference Population)

Standard Deviation
 

 

 

Standard Deviation = 
(50th percentile−5th percentile)

1.82
 

 

Malnutrition status can be categorized into different types considering different standards. 



Banu et al., Bangladesh Journal of Multidisciplinary Scientific Research 7(1) (2023), 11-21 

 

16 

Table 1. Categorization of Z-Score 

Underweight Weight for Age < –2 standard deviations (SD) of the WHO Child Growth Standards 

median 

Stunting Height for Age < –2 SD of the WHO Child Growth Standards median 

Wasting Weight for height < –2 SD of the WHO Child Growth Standards median 

Overweight Weight for height> +2 SD of the WHO Child Growth Standards median 

 

Calculation procedure of Women's Dietary Diversity (WDD) 

To calculate Women's Dietary Diversity (WDD), we have used mothers' 24-hour food recall data. The condition like, if a 

mother consumes a specific food of any group, we marked that 1 and 0 otherwise. We have avoided a score of more than 1 

to avoid overestimating dietary diversity. So, the score range will be 0 to 9 as there is a total of 9 food groups, and the cut-

off for this score is as follows: 

 

Table 3. Measurement of Dietary Diversity 

Low Dietary Diversity <= 4 

Medium Dietary Diversity 5 to 6 

High Dietary Diversity >= 7 

 

Calculation procedure of Child Dietary Diversity (WDD) 

To calculate Child Dietary Diversity (WDD), we have used the child's 24-hour food recall data. The condition like, if a child 

consumes a specific food of any group, we marked that 1 and 0 otherwise. We have avoided a score of more than 1 to avoid 

overestimating dietary diversity. So, the score range will be 0 to 7 as there is a total of 7 food groups, and the cut-off for this 

score is as follows: 

 

Table 4. Measurement of Dietary Diversity 

Low Dietary Diversity <4 

Minimum Dietary Diversity 4 

High Dietary Diversity >4 

 

Women Empowerment Index (WEI) 

We have also estimated dimension-wise empowerment by using the same factor analysis method. The grouped variables 

loaded in this analysis in one factor named a dimension. We then use these dimensions' variables in factor analysis and 

predict the score index. After predicting the value, we formed a binary following the similar method mentioned earlier. We 

repeated this for all dimensions and got all the dimension-wise women empowerment status which is binary.  

Mother’s Nutrition Knowledge, Attitude, and Practice 

Three indexes were developed initially and then combined into one index named mother's knowledge attitude and practice 

(KAP) to assess the mother's nutrition knowledge attitude and practice. Three separate indexes are the mother's knowledge 

index, the mother's attitude index, and the mother's practice index. All the variables have binary responses and assigned 

values of 1 for "yes" and 0 for "no." All the scores were summed up for each category and then categorized into three groups; 

poor, fair, and reasonable. The poor category is defined as the 0 % to 50 % range; the appropriate category lies in the 51 % 

to 75 % range, and the rest, 76 % to 100 %, ranges defined as good (Sangra & Nowreen, 2019). For calculating the KAP, 

all three individual index score has been merged into one index and then categorized into the three groups mentioned above. 

 

Bivariate Association 

The bivariate association is generally developed for identifying the normal relationship between two variables, say, x and 

y, and it was applied in this study due to its simplicity in nature (Babbie, 2009). If the relationship is perfect, then the relation 

is shown in a linear function as: 

𝑦 = 𝑎 + 𝑏𝑥 

Here, y is the dependent variable, and x is independent with a slope intercept of b and acts as a constant. For this analysis, 

this study used Pearson correlation coefficients that can be measured as below: 

𝑟 =
∑ 𝑥𝑦

√∑ 𝑥2 + ∑ 𝑦2
 

Where ∑ 𝑥 is the sum of x scores,  ∑ 𝑦  is the sum of y scores,  ∑ 𝑥𝑦 is the sum of the products of scores, ∑ 𝑥2 is the sum of 

squared x scores, and ∑ 𝑦2 is the sum of squared y scores, Its value ranges from -1, which means a perfect negative linear 

relationship, to +1, which means a perfect positive linear relationship. On the contrary, a 0 value means no relationship 

existed between the two variables. 

 



Banu et al., Bangladesh Journal of Multidisciplinary Scientific Research 7(1) (2023), 11-21 

 

17 

RESULTS 

Child care & Feeding Practice 

Regarding child care and feeding, the study found that around three-fourths of the mothers bought food for the baby and 

played different activities while feeding the child, and the baby was fed meals and snacks 4-5 times a day. Half of the 

mothers consulted with a doctor about child care and feeding. Around 66% of the mothers got angry when their children 

did not want to eat food.  

 

Table 5. Child care and feeding practices of the respondents 

 
Care and feeding practice No Yes Total 

Buy food yourself from the market for baby 125 (23.28) 412 (76.72) 537 (100) 

 You/ Care Giver Play Different Activities while feeding the child 137 (25.51) 400 (74.49) 537 (100) 

Baby-fed meals and snacks 4-5 times a day 122 (22.72) 415 (77.28) 537 (100) 

Have any sessions with a doctor/health about child feeding 271 (50.47) 266 (49.53) 537 (100) 

Get angry with the child when food is refused 183 (34.08) 354 (65.92) 537 (100) 

Source: Field Survey 2020; Figures within the parentheses indicate percentages of the number of the respondents 
 

Mothers' nutrition knowledge is important for a child's growth. The following table 6 shows mothers' nutrition 

knowledge. About 62% of the respondents agreed positively that they try to take at least five colors of food every day, 41% 

agreed that they add sugar to child milk, 73% stated yes that they change the food menu frequently for their child, 41% 

agreed that think that a baby can be healthy even if s/he is not fat. Nearly 97% agree that feeding colostrums to your baby 

is important. 88% said that it is right to introduce semi-solid foods into a child's diet. 87% asserted that they give a child 

who suffers from diarrhea. About 66% agreed that they know what food children consume daily. Nearly 73% said yes that 

their children consume fast food. Almost 50% agreed that they regularly visit doctors for medication. These questions and 

their corresponding replies imply that mothers who had a significantly higher level of nutritional Knowledge fed their 

children more with vegetable tables, fruit, legumes, and less sugared drinks such as pops, juice, and fast foods than the 

mothers who had a significantly lower level of nutritional Knowledge. Also, mothers with higher nutritional knowledge 

levels avoided giving foods that contained artificial to their children and believed in more Knowledge about nutrition-health. 

Mothers' nutrition knowledge level affects children's eating habits, mother knowledge, attitude, and practice. 

 

Table 6. Mothers' Knowledge, attitude, and practice 

Knowledge, attitude, and practice Yes (%) 

Try to take at least five colors of food every day 334 (62) 

Add sugar to the child's milk 221 (41) 

Change the food menu frequently for your child 389 (73) 

Think that a baby can be healthy even if s/he is not fat 221 (41) 

Think that feeding colostrums to your baby is important 523 (97) 

At what age is it right to introduce semi-solid foods into a child's diet 474 (88) 

What should one give a child who suffers from diarrhea 466 (87) 

Types of food children should consume every day 354 (66) 

Regularly should fast foods be consumed 73 (14) 

Do you/your caregiver have any sessions with a doctor/health worker to have enough Knowledge about the baby's care/ 

food 

267 (50) 

Source: Field Survey 2020; Figures within the parentheses indicate percentages of the number of respondents. 

 

 

 
 

Figure 3. Mothers’ nutrition knowledge 

Nearly about 7% of the mothers had good nutrition knowledge. On the other hand, 56% and 37% had fair and poor 

nutritional Knowledge, respectively (Figure 3). This may be due to the need for proper communication with the health 

facility providers engaged in the locality and the lack of adequate awareness spread through mass communication. Nearly 

58% of the caregivers have no institutional education, whereas 7% for incomplete primary education, 11 % for complete 

primary education, 11% for incomplete secondary education, and 14% for secondary complete or higher are identified 

(Figure 4). 

 



Banu et al., Bangladesh Journal of Multidisciplinary Scientific Research 7(1) (2023), 11-21 

 

18 

 
Figure 4. Education of caregivers 

 

Table 7. Caregivers’ qualification 

 
Caregivers’ qualification Yes (% of the total sample) 

caregivers have Knowledge about preparing baby's meal 255 (48) 

know about child nutrition 158 (30) 

know about dietary diversity 160 (30) 

capable of following your instructions properly in lieu stead of you 293 (55) 

Source: Field Survey 2020; Figures within the parentheses indicate percentages of the number of respondents. 

Table 7 shows that several questions were asked, and the respondents answered those questions. From 537 

respondents, 255 respondents answered "Yes" to the question "Do you think that caregivers have Knowledge know about 

preparing the baby's meal? This indicates that 48% are aware and have Knowledge about preparing the baby's meal which 

is nutritious to be healthy. 158 respondents answered "Yes" when asked whether the caregiver knew about child nutrition, 

and 160 respondents answered "Yes" to this question, "Does she know about dietary diversity? Lastly, 55% of the 

respondents answered "Yes" when we asked whether the caregiver can follow your instructions properly instead of the 

mother, indicating that most of the caregivers are playing a better role as a supplementary to the child's mother. The study 

also found that more than half of the children get childcare support from their family families Caregivers' qualifications. 

 

Table 8. Bivariate association 

 
Variables LAZ WAZ WHZ Women 

Empowerment 

Self 

Esteem 

Access to 

and control 

over 

resources 

Attitude 

and 

Behavior 

of 

Husband  

Decisions 

related to 

household 

Mobility CDD WDD 

Sanitation 4.27NS 38.25*** 11.07** 2.08NS 3.01* 4.49** 0.026NS 3.37* 1.98NS 
  

Mother’s 

Employment 

4.60NS 6.1* 11.42** 2.58NS 26.22*** 44.76*** 0.108NS 5.66** 2.94* 1.6NS 1.3NS 

Education 14.62NS 33.72** 38.95*** 15.74*** 74.74*** 66.2*** 61.16*** 50.39*** 21.03*** 75.3*** 48.75*** 

WDD 1.63NS 8.24NS 8.47NS 1.83NS 0.581NS 96.53*** 2.83* 11.31*** 3.64* 
  

CDD 10.14NS 4.12NS 13.75NS 6.18** 3.65NS 37.21*** 22.57*** 6.84** 7.68** 
  

ANC 6.4NS 23.52*** 7.82NS 9.28*** 47.47*** 36.53*** 20.71*** 64.49*** 14.52*** 19.56*** 17.59*** 

Nutritional 

Knowledge 

3.96NS 0.91NS 27.08*** 12.35*** 47.51*** 77.78*** 59.51*** 75.26*** 17.44*** 64.94*** 7.8*** 

Wealth 

Index 

11.85NS 51.29*** 43.47*** 15.68*** 59.01*** 92.42*** 55.61*** 62.61*** 21.41*** 71.93*** 3.66** 

Stunting 
   

3.69NS 1.35NS 7.09* 5.21NS 3.54NS 3.11NS 
  

Wasting 
   

11.54** 9.1NS 15.05*** 5.64NS 6.82NS 12.55** 
  

Underweight 
   

8.37** 4.29NS 18.8*** 3.55NS 1.57NS 8.57** 
  

NS refers to Not Significant; *,**,*** stands for significant at p<0.1, p<0.05 and p<0.01 respectively 

 

Table 8 shows the bivariate association between categorical outcome variables and explanatory variables with 

different significant levels. Sanitation is significantly associated with WAZ, WHZ, self-esteem, access to and control over 

resources, and decisions related to the household. Mother's Employment is highly significant with self-esteem and access to 

and control over resources. This is similar to that finding by Nankinga et al. (2019). The education and wealth index is 

significant with all variables except LAZ. This finding is also consistent with those of Sherman and Muehlhoff (2007), 

Miller and Rodgers (2009), and Makoka and Masibo (2015), who found that maternal education had a highly positive effect 

on child nutrition. Women's dietary and child dietary diversity are significantly associated with access to and control over 

resources, attitude and behavior of husband; decisions related to household and mobility variables, while child dietary 

diversity is also significant with women's empowerment. Antenatal care is significantly associated with all variables except 

LAZ and WHZ. Nutritional Knowledge is also significantly associated with all variables except LAZ and WAZ.  

 

DISCUSSIONS 
In this study, Fair maternal nutritional Knowledge was about 56% (Figure 4) in the study areas, whereas poor Knowledge 

was 37%, and very sound Knowledge was identified as only 7%. These findings were similar to those of Tesfa et al. (2022), 

Mahmoud and Ghaly (2019), Koppmair et al. (2017), and Masuku and Lan (2014) where all of them found that about half 



Banu et al., Bangladesh Journal of Multidisciplinary Scientific Research 7(1) (2023), 11-21 

 

19 

the sampled mothers had general or fair Knowledge about maternal and child nutrition and about 40% had very poor 

Knowledge about the nutritional issues. These results also show the lower condition, and the percentage is higher than 61.4% 

(Demissie et al., 2020), 63.9% (Nana & Zema, 2018), and 81.6% (Misgna et al., 2016). 80.6% (Thomas et al., 2015). This 

finding is higher than about 40% (Owais et al., 2019), Hoddinott et al. (2018), and 47.5% (Abdirahman, 2019). On the 

contrary,  This deviation may occur due to the existence of the lower living standard, low family income, lack of proper 

policy-making based on vulnerable groups at the national level, management protocol of child and maternal nutritional 

condition, and lack of spreading information among the local or root level citizens. This study also found that maternal 

Employment, maternal nutritional Knowledge, antenatal cares, maternal education, and wealth index were the key 

significant indicators for the child's nutritional status in the study areas. These results were also consistent with the findings 

of Nguyen et al. (2017), Fakir and Khan (2015), Owais et al. (2019), Choudhury (2011), Negash et al. (2015), Anwar et al. 

(2013), Nankinga et al. (2019), Berhanu et al. (2023), Wahid et al. (2021) and Mengesha et al. (2021). Several studies also 

observe women's employment status as one of the influential ingredients affecting child nutrition, such as Appoh and 

Krekling (2005), Saaka (2014), Negash et al. (2015), Nankinga et al. (2019) and Fadare et al. (2019). There is a low 

significant relationship between stunting and access to and control over resources while wasting and underweight is highly 

significant with access to and control over resources. Therefore, to ensure better child nutritional status, policymakers can 

improve the healthcare factors that determine the nutritional status, such as the mother's education level, sanitation facility, 

wealth index, and mothers' employment status. For this, mass media communication can play a vital role. However, this 

study did not consider the environmental attributes and communicable diseases in the analysis, which are also important 

factors for determining the child's nutritional status. 

 

CONCLUSIONS 

According to this study, maternal Knowledge is strongly related to the dietary diversity of mothers, children, and self-

esteem. However, it is also noted that the mother's educational level, employment situation, level of nutritional 

understanding, and wealth index are important factors in determining the children's nutritional status. The survey also 

showed that maternal average nutritional awareness is low. The outcomes of this study add to the notion that maternal 

nutrition education is critical in the fight against childhood malnutrition. It also demonstrates that, while female schooling 

is vital for both mother and child health, formal education with explicit dietary Knowledge may be effective. Maternal 

nutritional Knowledge and child nutritional status can be improved by facilitating with the help of village maternal clinical 

and village nutritional nurses. Children may suffer from severe malnutrition as a result of mothers' lack of basic 

understanding about nutrition and infant nourishment. The causes of malnutrition, particularly in children, include 

inadequate maternal understanding about feeding low-quality foods, the timing of changes in children's eating habits, health 

care, sanitation, and differences between eating prepared food from the market and eating homemade cuisine. Some 

important gaps in our understanding of the relationship between parental mental health and children's nutritional status and 

well-being remain unexplored in this study. Multiple income levels, geographic regions, or the entire country can be 

analyzed more deeply. More research may be done to compare the nutritional status of children in different regions, between 

urban and rural residents, between different socio-economic groups (for example, working women and stay-at-home 

mothers), and between different socio-economic groups.   

 
 
Author Contributions: Conceptualization, B.B., S.H., S.A.S. and M.A.H.; Data Curation, B.B.; Methodology, B.B.; Validation, B.B., S.H., S.A.S. 

and M.A.H.; Visualization, B.B., S.H., S.A.S. and M.A.H.; Formal Analysis, B.B., S.H., S.A.S. and M.A.H.; Investigation, B.B.; Resources, B.B., 

S.H., S.A.S. and M.A.H.; Writing - Original Draft, B.B., S.H., S.A.S. and M.A.H.; Writing - Review & Editing, B.B., S.H., S.A.S. and M.A.H.; 
Supervision, S.H.; Software, B.B.; Project Administration, B.B. and S.H.; Funding Acquisition, B.B., S.H., S.A.S. and M.A.H. All authors have read 

and agreed to the published version of the manuscript. 

Institutional Review Board Statement: Ethical review and approval were waived for this study because the research does not deal with vulnerable 
groups or sensitive issues. 

Funding: The authors received no direct funding for this research. 
Acknowledgment: Not applicable.  
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. 

Data Availability Statement: The data presented in this study are available on request from the corresponding author. The data are not publicly 

available due to restrictions. 

Conflicts of Interest: The authors declare no conflict of interest. 

 

REFERENCES 

Abdirahman, M. K. (2019). Nutrition knowledge, dietary practices, and nutrition status of pregnant adolescents in Mandera 

County, Kenya (Doctoral dissertation, PhD Dissertation, Kenya University, Kenya). 

Akeredolu, I. A., Osisanya, J. O., Seriki-Mosadolorun, J. S., & Okorafor, U. (2014). Mothers' nutritional Knowledge, infant 

feeding practices, and nutritional status of children (0-24 months) in Lagos State, Nigeria. European Journal of 

Nutrition and Food Safety, 4(4), 364-374. https://doi.org/10.9734/ejnfs/2014/7604 

Anwar, S., Nasreen, S., Batool, Z., & Husain, Z. (2013). Maternal education and child nutritional status in Bangladesh: 

Evidence from demographic and health survey data. Pakistan Journal of Life and Social Sciences, 11(1), 77-84. 

Appoh, L. Y., & Krekling, S. (2005). Maternal nutritional Knowledge and child nutritional status in the Volta region of 

Ghana. Maternal & child nutrition, 1(2), 100-110. https://doi.org/10.1111/j.1740-8709.2005.00016.x 

Babbie, E. R. (2009). The Practice of Social Research Twelfth (12th) Edition. Wadsworth: Cengage Learning. 

Berhanu, G., Dessalegn, B., Ali, H., & Animut, K. (2023). Determinants of nutritional status among primary school students 

in Dilla Town; Application of an ordinal logistic regression model. Heliyon, 9(3), 1-11. 



Banu et al., Bangladesh Journal of Multidisciplinary Scientific Research 7(1) (2023), 11-21 

 

20 

https://doi.org/10.1016/j.heliyon.2023.e13928 

Birhan, N. A., & Belay, D. B. (2021). Associated risk factors of underweight among under-five children in Ethiopia using 

a multilevel ordinal logistic regression model. African Health Sciences, 21(1), 362-72. 
https://doi.org/10.4314/ahs.v21i1.46 

Choudhury, N., & Ahmed, S. M. (2011). Maternal care practices among the ultra poor households in rural Bangladesh: a 

qualitative exploratory study. BMC Pregnancy and Childbirth, 11(1), 1–8. https://doi.org/10.1186/1471-2393-11-

15 

Debela, B. L., Demmler, K. M., Rischke, R., & Qaim, M. (2017). Maternal nutrition knowledge and child nutritional 

outcomes in urban Kenya. Appetite, 116, 518-526. https://doi.org/10.1016/j.appet.2017.05.042 

Demissie, D. B., Erena, T., & Kolola, T. (2020). Dietary Practice and Associated Factors among Pregnant Women in Nono 

Woreda west shoa, Oromia, Ethiopia. medRxiv, 11, 1-21. https://doi.org/10.1101/2020.11.27.20239624 

Fadare, O., Amare, M., Mavrotas, G., Akerele, D., & Ogunniyi, A. (2019). Mother’s nutrition-related knowledge and child 

nutrition outcomes: Empirical evidence from Nigeria. PloS one, 14(2), e0212775. 
https://doi.org/10.1371/journal.pone.0212775 

Fakir, A., & Khan, M. (2015). Determinants of malnutrition among urban slum children in Bangladesh. Health economics 

review, 5(1), 1-11. https://doi.org/10.1186/s13561-015-0059-1 

Habiba, U., Jui, F., Sultana, A., & Hasan, K. (2020). Household food security and nutrition assessment among children: a 

study on some selected slum areas of Khulna City. International Journal of Business, Management, and Social 

Research, 9(1), 500-507. https://doi.org/10.18801/ijbmsr.090120.51 

Hoddinott, J., Ahmed, A., Karachiwalla, N. I., & Roy, S. (2018). Nutrition behavior changes communication causes 

sustained effects on IYCN knowledge in two cluster-randomized trials in Bangladesh. Maternal & Child Nutrition, 

14(1), e12498. https://doi.org/10.1111/mcn.12498 

Kehinde, T., & Favour, E. (2020). Food Insecurity and Nutrition Status of Farm Households in Northwestern Nigeria. 

J. Food Sec, 8(3), 98–104. https://doi.org/10.12691/jfs-8-3-3 

Koppmair, S., Kassie, M., & Qaim, M. (2017). Farm production, market access and dietary diversity in Malawi. Public 

health nutrition, 20(2), 325-335. https://doi.org/10.1017/S1368980016002135 

Lestari, R., & Setyawan, F. E. B. (2021). Mental health policy: protecting community mental health during the COVID-19 

pandemic. Journal of Public Health Research, 10(2), 2231. https://doi.org/10.4081/jphr.2021.2231 

Mahmoud, N. M., & Ghaly, A. S. (2019). Dietary Knowledge, Practices and Adequacy among Bedouin Pregnant Women. 

International Journal of Nursing, 6(2), 68-83. https://doi.org/DOI: 10.15640/ijn.v6n2a7 

Makoka, D., & Masibo, P. K. (2015). Is there a threshold level of maternal education sufficient to reduce child 

undernutrition? Evidence from Malawi, Tanzania, and Zimbabwe. BMC Pediatrics, 15(1), 1-10. 
https://doi.org/10.1186/s12887-015-0406-8 

Masuku, S. K., & Lan, S. J. J. (2014). Nutritional Knowledge, attitude, and practices among pregnant and lactating women 

living with HIV in the Manzini region of Swaziland. Journal of Health, population, and Nutrition, 32(2), 261. 

Haq, I. U., Mehmood, Z., Afzal, T., Khan, N., Ahmed, B., Nawsherwan, Ali, L., Khan, A., Muhammad, J., Khan, E. A., 

Khan, J., Z., S. A., Xu, J., & Shu, Y. (2021). Prevalence and determinants of stunting among preschool and school-

going children in the flood-affected areas of Pakistan. Brazilian Journal of Biology, 82, e249971. 

https://doi.org/10.1590/1519-6984.249971 

Mengesha, A., Hailu, S., Birhane, M., & Belay, M. M. (2021). The prevalence of stunting and associated factors among 

children under five years of age in southern Ethiopia: community-based cross-sectional study. Annals of Global 

Health, 87(1), 111. https://doi.org/10.5334/aogh.3432 

Miller, J. E., & Rodgers, Y. V. (2009). Mother’s education and children’s nutritional status: new evidence from 

Cambodia. Asian Development Review, 26(1), 131–165. https://doi.org/10.7282/t3wq05w4 

Misgna, H. G., Gebru, H. B., & Birhanu, M. M. (2016). Knowledge, practice and associated factors of essential newborn 

care at home among mothers in Gulomekada District, Eastern Tigray, Ethiopia, 2014. BMC Pregnancy and 

Childbirth, 16(1), 1-8. https://doi.org/10.1186/s12884-016-0931-y 

Mondal, D., & Paul, P. (2020). Association between intimate partner violence and child nutrition in India: Findings from 

recent National Family Health Survey. Children and Youth Services Review, 119, 105493. 
https://doi.org/10.1016/j.childyouth.2020.105493 

Nana, A., & Zema, T. (2018). Dietary practices and associated factors during pregnancy in northwestern Ethiopia. BMC 

Pregnancy and Childbirth, 18(1), 1-8. https://doi.org/10.1186/s12884-018-1822-1 

Nankinga, O., Kwagala, B., & Walakira, E. J. (2019). Maternal employment and child nutritional status in Uganda. PloS 

one, 14(12), e0226720. https://doi.org/10.1371/journal.pone.0226720 

Negash, C., Whiting, S. J., Henry, C. J., Belachew, T., & Hailemariam, T. G. (2015). Association between maternal and 

child nutritional status in Hula, rural Southern Ethiopia: A cross-sectional study. PloS one, 10(11), e0142301. 
https://doi.org/10.1371/journal.pone.0142301 

Nguyen, P. H., Sanghvi, T., Kim, S. S., Tran, L. M., Afsana, K., Mahmud, Z., Aktar, B., & Menon, P. (2017). Factors 

influencing maternal nutrition practices in a large scale maternal, newborn, and child health program in Bangladesh. 

PloS one, 12(7), e0179873. https://doi.org/10.1371/journal.pone.0179873 

Owais, A., Suchdev, P. S., Schwartz, B., Kleinbaum, D. G., Faruque, A. S. G., Das, S. K., & Stein, A. D. (2019). Maternal 

Knowledge and attitudes towards complementary feeding in relation to the timing of its initiation in rural 

Bangladesh. BMC Nutrition, 5(1), 1-8. https://doi.org/10.1186/s40795-019-0272-0 

Özdoğan, Y., Uçar, A., Akan, L. S., Yılmaz, M. V., Sürücüoğlu, M. S., Pınar, F., & Özçelik, A. Ö. (2012). Nutritional 



Banu et al., Bangladesh Journal of Multidisciplinary Scientific Research 7(1) (2023), 11-21 

 

21 

Knowledge of mothers with children aged between 0-24 months. Journal of Food, Agriculture & Environment, 

10(1), 173-175. https://doi.org/10.1234/4.2012.2585 

Saaka, M. (2014). Relationship between mothers' nutritional Knowledge in childcare practices and the growth of children 

living in impoverished rural communities. Journal of health, population, and nutrition, 32(2), 237. 

Sangra, S., & Nowreen, N. (2019). Knowledge, attitude, and practice of mothers regarding nutrition of under-five children: 

a cross-sectional study in rural settings, International Journal of Medical Science and Public Health, 8(5), 392–

394. 

Sherman, J., & Muehlhoff, E. (2007). Developing a nutrition and health education program for primary schools in 

Zambia. Journal of nutrition education and behavior, 39(6), 335-342. https://doi.org/10.1016/j.jneb.2007.07.011 

Shrestha, V., Paudel, R., Sunuwar, D. R., Lyman, A. L. T., Manohar, S., & Amatya, A. (2021). Factors associated with 

dietary diversity among pregnant women in the western hill region of Nepal: A community-based cross-sectional 

study. PloS one, 16(4), e0247085. https://doi.org/10.1371/journal.pone.0247085 

Siregar, S. G. (2020). Factors Related to the Incidence of Nutritional Deficiencies in Children Under Five. Jurnal Ilmiah 

PANNMED (Pharmacist, Analyst, Nurse, Nutrition, Midwifery, Environment, Dentist), 15(1), 13–21. 

Tesfa, S., Aderaw, Z., Tesfaye, A., Abebe, H., & Tsehay, T. (2022). Maternal nutritional Knowledge, practice and their 

associated factors during pregnancy in Addis sub-city health centers, Addis Ababa, Ethiopia. International Journal 

of Africa Nursing Sciences, 17, 100482. https://doi.org/10.1016/j.ijans.2022.100482 

Thomas, J. S., Yu, E. A., Tirmizi, N., Owais, A., Das, S. K., Rahman, S., Faruque, A. S. G., Schwartz, B., & Stein, A. D. 

(2014). Maternal Knowledge, Attitudes and Self-efficacy in Relation to Intention to Exclusively Breastfeed Among 

Pregnant Women in Rural Bangladesh. Maternal and Child Health Journal, 19(1), 49–57. 

https://doi.org/10.1007/s10995-014-1494-z 

Wahid, J. L., Sinharoy, S. S., Ali, M., Alam, M. M., Wendt, A. S., & Gabrysch, S. (2021). What Were the Drivers of 

Improving Child Nutritional Status in Bangladesh? An Analysis of National Household Data from 1992 to 2005 

Guided by the UNICEF Framework. The Journal of Nutrition, 151(4), 987-998. https://doi.org/10.1093/jn/nxaa425 

Yisak, H., Tadege, M., Ambaw, B., & Ewunetei, A. (2021). Prevalence and determinants of stunting, wasting, and 

underweight among school-age children aged 6–12 years in South Gondar Zone, Ethiopia. Pediatric Health, 

Medicine and Therapeutics, 12(1), 23-33. https://doi.org/10.2147/PHMT.S287815 
 

 

 

Publisher’s Note: CRIBFB stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. 

 

 
© 2023 by the authors. Licensee CRIBFB, USA. This article is an open-access article distributed under the terms and conditions of the Creative 

Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). 

Bangladesh Journal of Multidisciplinary Scientific Research (P-ISSN 2687-850X   E-ISSN 2687-8518) by CRIBFB is licensed under a Creative 

Commons Attribution 4.0 International License. 

http://creativecommons.org/licenses/by/4.0/)
http://creativecommons.org/licenses/by/4.0/
http://creativecommons.org/licenses/by/4.0/
http://creativecommons.org/licenses/by/4.0/

