Influence of Maternal Lifestyle and Child Health Practices on the Health and Nutrition of Children Under Five Years Old: A Cross‐Sectional Study

ABSTRACT

Background and Aims

Child nutrition is crucial for a country's economic development. In Bangladesh, nearly half of the children under five suffer from malnutrition, with higher rates in rural areas. This study aims to identify factors linked to malnutrition in children in a rural area of the Mymensingh district, Bangladesh.

Methods

This cross‐sectional study involved face‐to‐face interviews with 500 mothers using a questionnaire. Data were organized in an Excel spreadsheet for bivariate and multivariate analysis.

Results

We found that 27% of children were malnourished. Bivariate analysis (Chi‐square test) showed that age, mode of delivery, intake of vitamin A capsules, and mothers' educational status significantly impacted malnutrition (p < 0.05). Multivariate binary logistic analysis using WHZ, HAZ, and WAZ scores revealed that male children were more prone to malnutrition than females, and mother's education played a major role in child nutrition. As children age, their susceptibility to malnutrition increases. Factors such as C‐section delivery, timely intake of vitamin A capsules, family income, mother's employment status, and regular consumption of nutritional foods significantly influence child malnutrition.

Conclusion

The Bangladesh government must take proactive measures to address child malnutrition by prioritizing female education and well‐being. Effective interventions can help eradicate malnutrition, improving children's health, education, and livelihoods.

1. Introduction

The growth performance of children is often used as an indicator of the overall nutritional health of a community. This is because children under the age of five are the most susceptible to nutritional deficiencies. Commonly used anthropometric measurements include height‐for‐age (HAZ), which primarily indicates long‐term growth issues; weight‐for‐height (WHZ), which shows body proportion and is sensitive to short‐term growth disruptions; and weight‐for‐age (WAZ), which provides a useful combination of both linear growth and body proportion [1]. The United Nations Sustainable Development Goals (SDGs) are a set of 17 global goals with specific targets for the world to meet by 2030 to end poverty, protect the planet and ensure prosperity for all. Among them the second goal is “end hunger, achieve food security and improved nutrition, and promote sustainable agriculture.”

Based on a comprehensive study conducted by UNICEF, WHO, and the World Bank in 2012, it was demonstrated that malnutrition exhibits a higher prevalence in Africa and Asia. Specifically, findings indicated that out of 162 million children experiencing stunted growth, 56% were situated in Asia. Moreover, the incidence of underweight children in South Asia, although displaying gradual improvement, remains the highest globally, with over half of the world's underweight children residing in this region [2]. The repercussions of malnutrition extend beyond childhood, as affected individuals are predisposed to diminished productivity in adulthood due to impaired physical and cognitive development. Various research studies have established a compelling correlation between malnutrition and adverse outcomes such as poor academic performance, increased school absenteeism, reduced intellectual attainment, delayed cognitive progress, and heightened susceptibility to diseases, underscoring the critical importance of addressing malnutrition in children under the age of five [3].

A recent FAO study by Arcand highlights the positive correlation between nutrition and economic growth. Increasing daily per capita calorie intake to 2770 kcal in countries below this threshold could boost their GDP growth rate by 0.34 to 1.48 percentage points annually [4]. Moreover, reducing malnutrition in Africa and Asia could enhance a country's economic productivity by 11%, as indicated by GDP per capita [5].

Kalu and Etim (2018) [6] highlighted in their review paper that numerous factors, both concerning children and maternal aspects, are linked to child malnutrition in developing nations like Asia and Africa. These factors encompass dietary patterns (including protein, carbohydrate, water, vitamins, and minerals), the child's age and gender, maternal educational and employment status, family size, income, sociodemographic elements, and environmental conditions.

Previous studies have shown that children's age and sex are associated with malnutrition risk [7, 8, 9]. In sub‐Saharan Africa, males receive more attention due to their future family care role, while females' nutritional status is affected as they leave their families after marriage [8]. Mothers' educational attainment is positively linked with their children's nutritional status, including wasting and stunting, as evidenced by various studies [10, 11, 12]. Hosen et al. (2023) and Ukwuani & Suchindran (2003) proposed that increased female labor force participation could divert attention from household responsibilities, thereby placing younger children at malnutrition risk [13, 14]. Several studies have found that younger maternal age is associated with higher malnutrition prevalence, while children of older mothers are less likely to be malnourished [8]. A Tanzanian study further supported this, indicating that children of older mothers have lower malnutrition rates [8].

In a recent 2020 study by Ahmed et al. [15], conducted in a rural area of Pakistan, malnutrition among children was found to be prevalent due to several socio‐economic factors. These include family size, maternal education level, wealth quintile, access to sanitation facilities, food scarcity, incomplete immunization, and inadequate access to safe drinking water.

Rayhan and Khan's 2006 study in Bangladesh revealed that 45% of children suffered from chronic malnutrition, 10.5% were acutely malnourished, and 48% were underweight [16]. In this analysis, contributing factors included previous birth interval, birth size, maternal BMI, and parental education. In our study, we systematically structured the questionnaire into two sections to capture a holistic view of the nutritional status and health determinants for children. This approach helps in understanding the interconnections between maternal health, lifestyle, and child‐specific factors contributing to children's malnutrition, providing valuable insights for targeted interventions. For this purpose, a rural area of Atharabari union, Mymensingh district, Bangladesh, was chosen as a model. Therefore, this study aims to understand malnutrition in this area to inform policies and programs that can improve nutrition and health in similar rural communities in Bangladesh.

2. Methods

2.1. Study Area and Participants

This was a cross‐sectional study conducted in three units of the Atharabari union in Ishwargonj upazila, Mymensingh district. This area was chosen because it is agriculture‐based and faces high levels of food insecurity and illiteracy. Nearby areas show that about 58% of people struggle with food insecurity [17]. Additionally, many pregnant women are malnourished and anemic, worsening the health of their newborns [18]. Most residents rely on farming, and their low socioeconomic status limits their access to nutritious food, healthcare, and education. There is also a lack of data on the nutritional status of children and mothers.

2.2. Population and Sampling

The required sample size was determined based on an assumed 50% prevalence of malnutrition, a 5% margin of error, and a 95% confidence level. Accounting for a 10% non‐response rate, the target sample size was calculated to be 474 participants. To ensure the study's success and meet this requirement, 510 individuals were approached. To attain the desired sample size, a total of 510 participants were approached from the designated areas, resulting in an overall response rate of about 93%. Incomplete data led to the exclusion of 10 respondents from the final sample size, bringing the total to 500.

2.2.1. The Inclusion and Exclusion Criteria

The inclusion criterion for this study was children aged 5 years or younger, whose parents were present on the visiting day and provided verbal agreement for the child's participation. The majority of the inquiries pertained to the nutritional state of the children and mothers, as well as their health conditions. Therefore, consent was obtained solely from the parents during the interview. Children over the age of 5 years or those lacking parental consent were excluded from this study.

2.3. Data Collection

Data were collected by trained interviewers (two) who conducted face‐to‐face interviews and the data was collected over 4 months period from June to October, 2024. Initially, interviewers encountered challenges in effectively engaging with the children or their mothers. However, as the study progressed, they gained the necessary skills and experience to interact and communicate more effectively. By the final phase of data collection, the research team was fully prepared and equipped to gather data appropriately.

The nutritional status (malnourished or not malnourished) served as the dependent variable in the current research. The interviewer inquired directly with the child's mothers regarding their immunization status, food intake patterns, and socio‐economic conditions. This information was subsequently incorporated into the questionnaire. Anthropometric measurements were carried out following standard WHO guidelines‐ weight was measured using a calibrated digital scale to the nearest 0.1 kg, with children wearing minimal clothing and no shoes; height/length was measured using a stadiometer or an infantometer (for children under 2 years) and mid‐upper arm circumference (MUAC) was measured on the left arm, at the midpoint between the acromion and olecranon, using a non‐stretchable measuring tape, recorded to the nearest millimeter. BMI‐for‐age, HAZ, WHZ, and WAZ Z‐scores were calculated using WHO Anthro software (version 3.2) based on the 2006 WHO Child Growth Standards. All measurements were conducted by a pharmacy graduate student with prior experience. They received additional training before the study to ensure standardization and inter‐observer reliability. Measurements were taken in duplicate, and a third measurement was conducted in case of significant discrepancies between the first two.

2.4. Ethical Considerations

The participants were informed that their enrollment in this study was voluntary and they were required to provide written consent. Since the study did not involve any medical or surgical procedures conducted on people, verbal consent was obtained from the parents, predominantly mothers, of the participating children. The study methodology received approval from the ethical committee of Noakhali Science and Technology University and the reference number is NSTU/SCI/EC/2024/246.

2.5. Formulation of the Questionnaire

2.5.1. Content and Structure of the Questionnaire

The preliminary questionnaire contained a total 36 of questions including both open and close ended questions. The questionnaire was structured into two sections‐ Section I (Mothers) which included data on sociodemographic characteristics (name, residence, age, education, wealth index, profession), anthropometric measurements (height, weight, MUAC), health and nutritional practices (dietary intake, vaccination, deworming, current health condition). Section II (Children under 5 years) which included data on birth order, anthropometric parameters (height, weight, MUAC), vaccination and supplementation history, breastfeeding duration, delivery‐related factors, dietary habits, postnatal care, health complications, and access to child healthcare services.

2.5.2. Language Used

The original questionnaire was prepared in English and then translated into Bangla (Bengali), the native language of participants, for data collection. The translation process involved forward translation by a bilingual expert and back‐translation into English by another independent expert. Discrepancies were reconciled by the research team to ensure semantic and conceptual equivalence. The Bangla version was used during interviews with participants.

2.5.3. Validity and Reliability

The translated questionnaire was reviewed for content validity by three academic experts. A pilot test was conducted with 15 participants from a similar demographic to assess clarity, comprehensibility, and reliability. Based on feedback, minor wording adjustments were made before final data collection.

2.5.4. Categorization Details

Categorization of variables such as residence (rural/urban), eating habits which is frequency‐based (daily, most days, sometimes); employment status (housewife/job holder); current health status (self‐reported in an open‐ended response); birth order which is recorded numerically (1st, 2nd, 3rd, etc.); breastfeeding practices (0–6 months, 7–24 months, 25+ months); dietary habits of protein and vegetable intake recorded by frequency categories (daily, most days, sometimes); vaccination history (fully vaccinated, partially vaccinated, or not vaccinated) and prevalent health issues which was open‐ended (mother and child health conditions) was guided by findings from previous literature.

2.6. Statistical Analysis

Before statistical analysis, the original data obtained was preprocessed using Microsoft Excel. The initial dataset was subjected to exploratory data analysis to thoroughly investigate the occurrence of outliers and missing data. Subsequently, the data was encoded and inputted into the Statistical Package for the Social Sciences (SPSS) version 20.0 in order to enable later analysis.

The dataset was summarized using descriptive analysis within the framework of univariate analysis. A frequency distribution table was constructed to analyses the attributes of the variables, as the data exhibited a discrete nature. Considering that the dataset comprised of categorical variables, non‐parametric tests were employed for the comprehensive analysis of the research. The study employed bivariate analysis to examine the correlation between nutrition‐related factors and explanatory variables. This analysis involved the utilization of cross‐tabulation and Pearson's Chi‐square test (χ ²) to discover any statistically significant connections between the variables. Variables with a p‐value less than 0.05 were considered to be statistically significant. Following this, a statistical study was performed using multivariate binary logistic regression to ascertain the impact of the independent variables on the probability of experiencing difficulties linked to malnutrition. The Goodness of Fit Test developed by Hosmer and Lemeshow was employed to assess the appropriateness of the binary logistic regression model in accurately representing the dataset. A larger p‐value indicated that the model was suitably fitted.

3. Results

3.1. Anthropometric, Socioeconomic, Clinical Conditions and Dietary Patterns of the Children

Table 1 represents a general frequency distribution table that has been constructed in order to comprehend the characteristics of the explanatory variables in this investigation. Our study included a sample size of 500 children under 5 years of age, living in the rural area of the Mymensingh district of Bangladesh, among which more than 51% of the children were female (Table 1). The majority of the participants fell within the age range of 11 to 36 months (about 63%) and surprisingly 92.8% of them were underweight (BMI < 14.5). 77.0% of the children were born by cesarean delivery method and 69.6% of them received all the vaccines like BCG and measles vaccines at the early stage of life.

Table 1.

Frequency distributions of the anthropometric, socioeconomic, clinical conditions and dietary patterns of the children.

Variables	Categories	Frequency	Percentage (%)
Gender	Female	259	51.80
	Male	241	48.20
Birth order	1st Birth	241	48.20
	2nd Birth	152	30.40
	3rd Birth	83	16.60
	4th Birth	19	3.80
	5th Birth	5	1.00
Age	≤ 10 Months	45	9.00
	11–24 Months	174	34.80
	25–36 Months	143	28.60
	37–48 Months	62	12.40
	49–60 Months	76	15.20
BMI	Underweight (< 14.5)	464	92.80
	Normal Weight (14.5–18.0)	36	7.20
	Overweight (> 18.0)	0	0
MUAC	Healthy (> 125 mm)	477	95.4
	Moderate acute malnutrition (115 mm–125 mm)	20	4
	Severe acute malnutrition (Below 115 mm)	3	0.6
Mode of delivery	Normal	115	23.00
	Cesarean	385	77.00
Any postnatal complication	Yes	115	23.00
	No	385	77.00
Vaccination status of child	Completed	348	69.60
	Not completed	152	30.40
Intake of Albendazole within last 3 months	No	172	34.40
	Yes	328	65.60
Intake of vitamin A capsule within last 6 months	No	346	69.20
	Yes	154	30.80
Intake of protein containing foods protein foods	Daily	131	26.20
	Most days	283	56.60
	Sometimes	86	17.20
Intake of vegetables daily	Daily	192	38.40
	Most days	172	34.40
	Sometimes	136	27.20
Family wealth index	Lower income	224	44.80
	Middle income	181	36.20
	Higher income	95	19.00
Education status of mother	No education	63	12.6
	Primary education	178	35.6
	Secondary education	216	43.2
	Higher education	43	8.6
Employment status of mother	Housewife	430	86.00
	Job holder	70	14.00

About 65.6% of the study subjects had taken albendazole within the past 3 months while a significant proportion (69.2%) of the participants did not intake vitamin A capsule within the last 6 months. Our study also revealed that about 56.6% of the children had protein‐containing food almost every day, while about 38.4% of them had vegetables regularly in their food menu. Additionally, it was also found that the majority (44.8%) of the children belonged to lower‐income families, 35.6% and 43.2% mothers had primary and secondary education respectively and 86.0% mothers of the participants were housewives.

3.2. Bivariate Analysis of the Factors Associated With Nutritional Status of the Children

The level of malnutrition was determined in this study based on Z‐score value and classified as severe acute malnutrition (z‐score of WH, WA and HA < −3; MAUC < 11.5 cm), Moderate acute malnutrition (−3≤ z‐score of WH, WA and HA ≤ −2; 11.5 cm < MUAC < 12.5 cm), nourished (−2 ≤ z‐score of WH, WA and HA ≤ 2; MUAC > 12.5 cm) and overweight (z‐ score of WH, WA > 2). Table 2 summarizes the outcomes of a bivariate analysis conducted to investigate the nutritional status and several categories of explanatory variables. Malnutrition's are significantly associated with the age of the children (χ ² = 15.04, p = 0.01), process of childbirth (χ ² = 4.27, p = 0.04) and intake of vitamin A capsule within the last 6 months period (χ ² = 27.77, p = 0.00).

Table 2.

Cross‐tabulation and Chi‐square test of association of nutritional status with different anthropometric, socioeconomic, clinical conditions and dietary patterns of the children.

Variables	Categories	Nutritional status		Chi‐square	p‐value
		Healthy (367)	Malnourished (133)
Gender	Female	183	76	2.07	0.15
	Male	184	57
Birth order	1st Birth	171	70	2.94	0.57
	2nd Birth	118	34
	3rd Birth	60	23
	4th Birth	15	4
	5th Birth	3	2
Age	≤ 10 Months	37	8	15.04	0.01*
	11–24 Months	136	38
	25–36 Months	93	50
	37–48 Months	39	23
	49–60 Months	62	14
BMI	Underweight ( < 14.5)	29	7	1.02	0.31
	Normal Weight (14.5–18.0)	338	126
	Overweight ( > 18.0)	0	0
Vaccination status of child	Completed	251	97	0.95	0.33
	Not completed	116	36
Mode of delivery	Normal	274	111	4.27	0.04*
	Cesarean	93	22
Any postnatal complication	Yes	85	30	0.02	0.89
	No	282	103
Intake of Albendazole within last 3 months	No	234	94	2.07	0.15
	Yes	133	39
Intake of vitamin A capsule within last 6 months	No	89	65	27.77	0.00*
	Yes	278	68
Intake of protein containing foods protein foods	Daily	101	30	1.55	0.46
	Most days	206	77
	Sometimes	60	26
Intake of vegetables daily	Daily	156	36	19.82	0.46
	Most days	130	42
	Sometimes	81	55
Family wealth index	Lower income	163	61	3.87	0.15
	Middle income	127	54
	Higher income	77	18
Education status of mother	No education	43	55	32.46	0.00*
	Primary education	90	41
	Secondary education	94	32
	Higher education	140	5
Employment status of mother	Housewife	313	117	0.58	0.45
	Job holder	54	16

^* p‐value < 0.05 is considered significant.

In addition, the variables of gender (χ ² = 2.07), birth order (χ ² = 2.94), BMI (χ ² = 1.02), albendazole intake within the last 3 months (χ ² = 2.07), intake and protein and vegetable‐containing foods regularly (χ ² = 1,55 and 19.82 respectively) and family wealth index (χ ² = 3.87) were found to be associated with the nutritional status of the children. In addition, mother's educational status significantly impacted (χ ² = 32.46, p = 0.00) the nutritional status of the children under 5.

3.3. Factors Influencing Wasting/WHZ Score in Children With Malnutrition

The findings presented in Table 3 illustrate the outcomes of binary logistic regression analysis, a type of multivariate statistical analysis used to determine the variables that exhibit a statistically significant (p < 0.05) impact on wasting/WHZ score in children with malnutrition. The odds ratio of 1.15 indicates that there is a greater probability of malnutrition among boys in comparison to girls. Children between the ages of 11–24 months had a significantly increased probability of being wasted compared to the reference group (≤ 10 months), with an odds ratio of 3.64. The odds of being underweight and incomplete vaccination of children were found to be 3.98 and 1.25 times higher, respectively, compared with the reference groups. Furthermore, children born by cesarean delivery and having birth complications had 1.66‐ and 1.01‐times higher odds, respectively, of being wasted compared with their other counterparts.

Table 3.

Binary logistic regression analysis model for wasting/WHZ score.

Variables	Categories	B	S.E.	Exp (B)	95% C.I. for Exp (B)		p‐value
					Lower	Upper
Gender	Female	—	—	—	—	—	—
	Male	0.14	0.28	1.15	0.66	2.00	0.61
Birth order	1st Birth	—	—	—	—	—	—
	2nd Birth	−0.60	1.53	0.55	0.03	11.10	0.70
	3rd Birth	−1.14	1.54	0.32	0.02	6.63	0.46
	4th Birth	−0.60	1.56	0.55	0.03	11.72	0.70
	5th Birth	−1.20	1.69	0.30	0.01	8.22	0.48
Age	≤ 10 Months	—	—	—	—	—	—
	11–24 Months	1.29	1.27	3.64	0.30	43.92	0.30
	25–36 Months	−1.58	0.61	0.21	0.06	0.68	0.01*
	37–48 Months	−1.67	0.56	0.19	0.06	0.56	0.00*
	49–60 Months	−0.64	0.65	0.52	0.15	1.86	0.32
BMI	Normal weight	—	—	—	—	—	—
	Underweight	1.38	0.79	3.98	0.85	18.67	0.08
Vaccination status of child	Completed	—	—	—	—	—	—
	Not completed	0.23	0.41	1.25	0.56	2.82	0.58
Mode of delivery	Normal	—	—	—	—	—	—
	Cesarean	0.51	0.37	1.66	0.80	3.46	0.17
Any postnatal complication	No	—	—	—	—	—	—
	Yes	0.01	0.34	1.01	0.52	1.97	0.97
Intake of Albendazole within last 3 months	No	—	—	—	—	—	—
	Yes	−0.72	0.31	0.49	0.26	0.90	0.02*
Intake of vitamin A capsule within last 6 months	No	—	—	—	—	—	—
	Yes	−1.90	0.29	0.15	0.08	0.26	0.00*
Intake of protein containing foods protein foods	Daily	—	—	—	—	—	—
	Most days	0.06	0.46	1.06	0.43	2.62	0.89
	Sometimes	−0.25	0.39	0.78	0.36	1.67	0.52
Intake of vegetables daily	Daily	—	—	—	—	—	—
	Most days	0.93	0.35	2.54	1.28	5.04	0.01*
	Sometimes	1.19	0.34	3.29	1.67	6.45	0.00*
Family wealth index	Lower income	—	—	—	—	—	—
	Middle income	−0.13	0.24	0.88	0.55	1.41	0.59
	Higher income	0.43	0.33	0.54	0.80	2.95	0.20
Education status of mother	No education	—	—	—	—	—	—
	Primary education	0.42	0.67	1.53	0.41	5.63	0.52
	Secondary education	−1.25	0.50	0.64	0.11	0.77	0.01*
	Higher education	−0.45	0.51	0.29	0.23	1.73	0.37
Employment status of mother	Housewife	—	—	—	—	—	—
	Job holder	−0.21	0.46	0.81	0.33	1.99	0.64
Hosmer and Lemeshow goodness of fit test		Chi‐square = 9.24			p‐value = 0.32

^* p‐value < 0.05 is considered significant.

The findings of our study revealed that the intake of albendazole tablets and vitamin A capsules had a significant (p < 0.05) influence on wasting. The likelihood of waste among children who have consumed albendazole within the last 3 months and vitamin A during the past 6 months was shown to be 0.49 and 0.15 times lower, respectively, in comparison to those who had not taken these medications. Consumption of protein‐rich foods and vegetables regularly serves as an effective indicator of a child's nutritional state. Based on our data, children who have consumed protein‐rich foods on an occasional basis, but not daily, had a 1.06‐fold higher likelihood of experiencing malnutrition compared to children who have consumed protein‐rich foods on a daily basis. Daily consumption of vegetables significantly (p < 0.05) affected the nutritional status of the respondents as our study results showed that the risk of malnutrition was 2.54 and 3.29 times higher for children who ate vegetables occasionally or sometimes on an as‐needed, respectively, compared to those who ate vegetables daily.

The findings derived from the investigation suggest a negative correlation between the household wealth index and the likelihood of children experiencing malnutrition. The odds of wasting in children were found to be 0.88 and 0.53 times lower for children from homes with middle and higher wealth indexes, respectively, compared to those from households with the lowest wealth index. Again, the likelihood of being wasted decreased as the mother's level of education increased. The odds of being wasted were found to be 1.53 times greater for children of mothers with primary education, and 0.64 and 0.29 times lower for children of mothers with secondary and higher education, respectively, compared to those of mothers with no education. Finally, the occupational status of the mother significantly impacted the occurrence of child wasting, specifically acute malnutrition. Children who had moms engaged in employment were 0.81 times less prone to experiencing wasting compared to those who were housewives.

We performed the Hosmer‐Lemeshow goodness of fit test to evaluate the suitability of the binary logistic regression model for accurately representing the data. The Chi‐square test yielded a statistic of 9.24 and a p‐value of 0.32. The findings of this study indicate that the binary logistic regression model demonstrates a strong alignment with the dataset and yields more appropriate results.

3.4. Factors Influencing Stunting/HAZ Score in Children With Malnutrition

The results of multivariate binary logistic regression, which was used to identify the variables with a statistically significant (p < 0.05) influence on the stunting status or HAZ score among children with malnutrition, are displayed in Table 4. Our study has found a higher likelihood of malnutrition among boys than girls as indicated by the odds ratio of 1.14. Children who were the 5th child of their parents had a higher probability of being stunted compared to the reference group (1st birth), with an odds ratio of 1.56. The results indicate that children aged between 25 and 36, 37–48 and 49–60 months significantly (p < 0.05) had 3.93, 6.50‐ and 6.86‐times higher odds of being stunted, respectively, in comparison with children aged ≤ 10 months. Our study also revealed a 1.25 and 1.16‐fold increase in the likelihood of malnutrition among children with inadequate immunization and having birth complications, respectively, when compared to the reference groups. The consumption of vitamin A capsules was found to have a statistically significant impact (p < 0.05) on stunting. Specifically, children who had ingested vitamin A over the previous 6 months exhibited a 0.76‐fold reduction in stunting compared to those who had not received the medication.

Table 4.

Binary logistic regression analysis model for stunting status/HAZ score.

Variables	Categories	B	S.E.	Exp (B)	95% C.I. for Exp (B)		p‐value
					Lower	Upper
Gender	Female	—	—	—	—	—	—
	Male	0.13	0.20	1.14	0.76	1.71	0.52
Birth order	1st Birth	—	—	—	—	—	—
	2nd Birth	−0.27	0.24	0.76	0.48	1.22	0.25
	3rd Birth	−0.04	0.20	0.96	0.54	1.68	0.87
	4th Birth	−1.14	0.62	0.32	0.09	1.08	0.07
	5th Birth	0.45	1.08	1.56	0.19	12.95	0.68
Age	≤ 10 Months	—	—	—	—	—	—
	11–24 Months	0.75	0.44	2.12	0.90	5.02	0.09
	25–36 Months	1.37	0.54	3.93	1.36	11.35	0.01*
	37–48 Months	1.87	0.58	6.50	2.07	20.36	0.00*
	49–60 Months	1.93	0.57	6.86	2.24	20.97	0.00*
BMI	Normal weight	—	—	—	—	—	—
	Underweight	−0.26	0.40	0.77	0.35	1.68	0.51
Vaccination status of child	Completed	—	—	—	—	—	—
	Not completed	0.15	0.34	1.16	0.59	2.28	0.66
Mode of delivery	Normal	—	—	—	—	—	—
	Cesarean	−0.02	0.24	0.98	0.61	1.59	0.95
Any postnatal complication	No	—	—	—	—	—	—
	Yes	0.08	0.24	1.08	0.67	1.74	0.76
Intake of Albendazole within last 3 months	No	—	—	—	—	—	—
	Yes	−0.12	0.21	0.89	0.58	1.36	0.59
Intake of vitamin A capsule within last 6 months	No	—	—	—	—	—	—
	Yes	−1.02	0.24	0.76	0.73	1.41	0.00*
Intake of protein containing foods protein foods	Daily	—	—	—	—	—	—
	Most days	−0.13	0.24	0.87	0.54	1.40	0.57
	Sometimes	−0.21	0.32	0.81	0.43	1.52	0.51
Intake of vegetables daily	Daily	—	—	—	—	—	—
	Most days	−0.51	0.24	0.60	0.38	0.95	0.03*
	Sometimes	−0.57	0.27	0.57	0.33	0.96	0.03*
Family wealth index	Lower income	—	—	—	—	—	—
	Middle income	−0.16	0.23	0.85	0.54	1.34	0.49
	Higher income	−0.55	0.28	0.73	0.47	1.01	0.05*
Education status of mother	No education	—	—	—	—	—	—
	Primary education	0.30	0.49	1.34	0.51	3.52	0.55
	Secondary education	0.17	0.41	1.18	0.53	2.65	0.68
	Higher education	−0.26	0.44	0.77	0.32	1.84	0.56
Employment status of mother	Housewife	—	—	—	—	—	—
	Job holder	0.29	0.32	1.34	0.71	2.50	0.36
Hosmer and Lemeshow goodness of fit test		Chi‐square = 9.19			p‐value = 0.33

^* p‐value < 0.05 is considered significant.

The results obtained from our study indicate an overall decrease in the household wealth index and an increased probability of children suffering from malnutrition. Children from households with intermediate and higher wealth indexes had 0.85‐ and 0.73‐times reduced risks of stunting, respectively, compared to children from households with the lowest wealth index. Once more, the probability of experiencing stunted growth diminished as the mother's educational attainment increased. The study results showed that children of mothers with primary and secondary education had 1.34‐ and 1.18‐times higher odds of being wasted, respectively. Conversely, children of mothers with higher education had 0.77 times lower odds of being wasted compared to children of mothers with no education. Regarding the occupation of the mother, the findings indicate a contrasting relationship between stunting and wasting. Specifically, it was observed that infants whose mothers were employed in various occupations were 1.34 times more susceptible to stunting in comparison to those whose mothers were homemakers.

We tested the binary logistic regression model's data representation accuracy using the Hosmer‐Lemeshow goodness of fit test. Chi‐square test results and p‐value were 9.24 and 0.32 respectively. This study found that the binary logistic regression model matches the dataset and produces better results.

3.5. Factors Influencing Underweight/WAZ Score in Children With Malnutrition

The statistical analysis conducted using a two‐level random intercept binary logistic regression model revealed some significant predictors of underweight (child chronic malnutrition) (Table 5). In comparison to the reference group (age ≤ 10 months), male children had a 1.09‐fold higher likelihood of being underweight. The findings indicate that children in the age categories of 37–48 and 48–60 months had odds of being underweight that were 1.16 and 1.57 times greater, respectively, when compared to the reference group. Just like wasting and stunting, there exists a positive correlation between postnatal problems and underweight. This correlation is evident in the findings that children who have delivery issues have a 1.11‐fold increased likelihood of being malnourished compared to the reference group.

Table 5.

Binary logistic regression analysis model for underweight/WAZ score.

Variables	Categories	B	S.E.	Exp (B)	95% C.I. for EXP (B)		p‐value
					Lower	Upper
Gender	Female	—	—	—	—	—	—
	Male	0.09	0.21	1.09	0.73	1.64	0.67
Birth order	1st Birth	—	—	—	—	—	—
	2nd Birth	−0.33	0.24	0.72	0.45	1.15	0.17
	3rd Birth	0.17	0.30	1.19	0.66	2.12	0.56
	4th Birth	−0.37	0.57	0.69	0.23	2.09	0.51
	5th Birth	0.01	1.10	1.01	0.12	8.83	0.99
Age	≤ 10 Months	—	—	—	—	—	—
	11–24 Months	−0.12	0.39	0.88	0.41	1.92	0.76
	25–36 Months	−0.35	0.50	0.71	0.26	1.90	0.49
	37–48 Months	0.15	0.56	1.16	0.39	3.47	0.79
	49–60 Months	0.45	0.55	1.57	0.54	4.57	0.41
BMI	Normal weight	—	—	—	—	—	—
	Underweight	−0.99	0.46	0.37	0.15	0.91	0.03*
Vaccination status of child	Completed	—	—	—	—	—	—
	Not completed	−0.25	0.34	0.78	0.40	1.51	0.46
Mode of delivery	Normal	—	—	—	—	—	—
	Cesarean	−0.31	0.25	0.73	0.45	1.20	0.22
Any postnatal complication	No	—	—	—	—	—	—
	Yes	0.10	0.25	1.11	0.68	1.82	0.68
Intake of Albendazole within last 3 months	No	—	—	—	—	—	—
	Yes	−0.33	0.22	0.81	0.51	1.75	0.03*
Intake of vitamin A capsule within last 6 months	No	—	—	—	—	—	—
	Yes	−0.40	0.26	0.67	0.40	1.10	0.00*
Intake of protein containing foods protein foods	Daily	—	—	—	—	—	—
	Most days	−0.12	0.33	0.89	0.47	1.68	0.71
	Sometimes	0.09	0.24	1.09	0.68	1.77	0.72
Intake of vegetables daily	Daily	—	—	—	—	—	—
	Most days	−0.53	0.24	0.59	0.36	0.95	0.03*
	Sometimes	0.14	0.29	1.15	0.66	2.02	0.62
Family wealth index	Lower income	—	—	—	—	—	—
	Middle income	−0.14	0.23	0.87	0.55	1.37	0.55
	Higher income	−0.78	0.27	0.45	0.27	0.78	0.00*
Education status of mother	No education	—	—	—	—	—	—
	Primary education	0.09	0.28	0.97	0.63	1.91	0.45
	Secondary education	−0.29	0.27	0.75	0.44	1.27	0.29
	Higher education	−0.46	0.26	0.63	0.38	1.05	0.07*
Employment status of mother	Housewife	—	—	—	—	—	—
	Job holder	0.10	0.33	1.10	0.58	2.10	0.76
Hosmer and Lemeshow goodness of fit test		Chi‐square = 29.12			p‐value = 0.00

^* p‐value < 0.05 is considered significant.

The consumption pattern of albendazole and vitamin A has considerable impacts on the prevalence of chronic malnutrition in children. The likelihood of being underweight significantly decreased among children who consumed albendazole tablets and vitamin A capsules during the preceding 3 and 6‐month intervals, respectively (odds ratio of 0.81 and 0.67, respectively). Furthermore, children who consumed protein‐rich foods and vegetables occasionally, but not daily, had a 1.09 and 1.15‐fold higher likelihood of experiencing malnutrition compared to children who have consumed protein and vegetables‐containing foods regularly.

The influence of household income determinants on child nutrition status is substantial. The findings of our study indicate that children from higher‐income households exhibit better nutritional status compared to those from lower‐income households. Specifically, children from households with middle and higher income were 0.87 and 0.45 times less prone to being underweight, respectively, in comparison to children from low‐income households. The educational level of mothers has been identified as an important variable influencing child malnutrition in our research. The model reveals that children from mothers with primary, secondary, and higher levels of education were 0.97, 0.75, and 0.63 times less likely, respectively, to be underweight compared to children from mothers with no education. The occupation of the mother is an additional major factor influencing underweight. The regression analysis indicates that children had a 1.10‐fold higher likelihood of experiencing malnutrition (underweight) when their moms were employed as workers, as opposed to being housewives.

4. Discussion

This study presents the prevalence of malnutrition among children under the age of 5 in the Atharabari union of Ishwargonj Upazila, situated in the Mymensingh district of Bangladesh. To evaluate the overall nutritional condition of children under the age of 5 and track their progress towards global nutrition goals, it is essential to comprehend the occurrence rates of stunting, wasting, and underweight status in this age group.

Our study highlights that undernutrition remains a major public health challenge among children under five in rural Bangladesh, with stunting emerging as the most prevalent form of malnutrition. This finding is consistent with national surveys and regional studies that report persistent high rates of chronic undernutrition despite overall improvements in child health indicators over recent decades [19, 20]. The disproportionately higher burden observed in our study area may reflect the combined effects of poverty, food insecurity, and limited maternal education, factors that have been repeatedly linked to child malnutrition in Bangladesh and other South Asian countries [21, 22]. These results emphasize the urgent need for targeted interventions addressing both immediate dietary practices and broader socioeconomic determinants of health.

Our study identified several factors that strongly influence the nutritional status of children, including gender, age, vaccination status, birth delivery method, post‐birth complications, intake of albendazole and vitamin A, consumption of protein and vegetable‐rich foods, maternal education and occupation, and wealth index.

Malnutrition for stunting, wasting and underweight is relatively higher in male children. Multiple studies have shown that being male increases the risk of malnutrition, and our results corroborate those findings [23, 24], showing that the prevalence of malnutrition in boys is slightly higher than in girls. However, there was no significant association between gender and stunting, wasting, or underweight. Additional key risk factors for experiencing several forms of malnutrition include children who are in the older age category (36 months and above). The prevalence of stunted or underweight children has a sudden and significant increase once the child reaches 24 months of age, as demonstrated in Tables 4 and 5. Malnutrition reaches its peak between the ages of 49 and 60 months for both measurements. Following the initial 6 months, when children are often introduced to solid foods in addition to breast milk, there is a progressive increase in the proportion of children who are stunted or underweight [25, 26]. The maximum prevalence of stunted and underweight children occurs between the ages of 37 and 60 months [9, 27].

There could be multiple factors contributing to this issue, such as inadequate implementation of supplementary feeding techniques that are crucial for the cognitive and physical growth of children in these age groups. Research undertaken in rural areas of Bangladesh and India, focusing on children under the age of 2, indicates that a lack of understanding of the appropriate timing to introduce complementary feeding, insufficient dietary variety, and limited nutritional awareness contribute to an increased likelihood of stunting and underweight [28, 29]. Additional research carried out in rural Uganda, Vietnam, and Ethiopia has also found that mothers and caregivers with limited or insufficient understanding of appropriate infant and young child feeding (IYCF) practices ultimately contribute to the development of stunting in their children [30, 31]. Another factor is that older children experience reduced protection during periods of unfavourable nutritional outcomes due to inequitable food allocation within large homes. In such cases, they often receive insufficient food to meet their energy requirements based on their age [32, 33]. Thus, it may be concluded that stunting and being underweight are risks for children between the ages of 37 and 60 months due to negligent child‐feeding habits.

Incomplete immunization or no immunization was associated with an increased risk of stunting and wasting, as per our study's multivariate analysis. According to earlier research, infants who do not receive all of the recommended vaccines are more likely to have inadequate nutrition [34, 35]. Multiple studies have shown a correlation between a child's immunization status and the educational level of their mother, as it was found that children of educated mothers are more likely to be fully immunized compared to children of non‐educated mothers [36, 37]. Again, family size was found to be a significant factor in determining the number of children who were fully immunized. Children from larger families were more prone to being unimmunized. Several analogous investigations were carried out in Indonesia, Greece, and Angola, demonstrating that children from larger families had a lower likelihood of being fully immunized [38].

Poor nutrition and insufficient immunization in children can signify greater family issues, including parental neglect. Multiple studies have shown that these outcomes can indicate systemic problems within the caregiving environment, especially when parents encounter constraints in knowledge, mental health, or socioeconomic stability [39, 40, 41]. Negligent parenting, defined by insufficient attention to a child's fundamental health requirements, may arise from several parental traits, including low educational achievement, substance use, or ignored psychological disorders [42]. Such factors may impair a caregiver's ability to make informed decisions regarding child health, including nutrition and adherence to immunization schedules [43]. Thus, while poor nutrition and incomplete immunization may appear as separate issues, they can both be symptomatic of deeper caregiving deficits that warrant holistic public health interventions.

Our study suggests that children who experienced postnatal problems had a higher likelihood of being wasted, stunted, and underweight compared to children who did not have any delivery complications. Typically, children who experience birth difficulties, especially those with a low birth weight, may have stunted growth and be undernourished if they do not receive sufficient nutritional care [44]. There is evidence suggesting that there is a connection between small birth size, frequent infections, insufficient mother care, and unfavourable living situations with postnatal growth faltering [45]. Impoverished parents frequently lack access to healthcare facilities for postnatal care, as well as the means to provide their infants with a sufficient diet and competent postnatal care [46]. This considerably heightens the likelihood of malnutrition and problems in newborns.

The current investigation demonstrated a substantial correlation between intestinal helminth infection and undernutrition. Our study identified a notable decrease in the odds of being wasted, stunted, and underweight among children who received deworming treatment (albendazole tablet) every 3 months compared to their counterparts. The findings of our study align with earlier research, indicating that children infected with helminths are especially prone to having a low body mass [47]. Intestinal helminths can induce anorexia, emesis, diarrhea, and luminal blockage, resulting in decreased food consumption and impaired nutrient assimilation from ingested substances [48]. Nevertheless, other researchers have documented improvements in weight following deworming [49]. Likewise, there was a gradual decrease in the number of malnourished children (wasted, stunted and underweight) who consumed vitamin A supplementation compared to those who did not receive the supplementation. Other studies conducted in various regions of Bangladesh have also shown similar findings, demonstrating the role of vitamin A supplementation as an additional factor in undernutrition [50].

The dietary pattern of the rural people in Bangladesh is characterized by a low intake of protein and vegetables and a high consumption of carbohydrates [51]. Children who do not regularly consume protein and vegetable‐rich foods are at a higher risk of experiencing malnutrition, which can lead to being wasted and underweight, compared to their peers, as demonstrated in our study. Protein is essential for muscle growth and tissue repair [52], whereas fruits and vegetables provide macronutrients and micronutrients, including dietary fiber, which are crucial for maintaining proper intestinal function and promoting child development [53]. Hence, our research aligns with earlier studies conducted on Bangladeshi, Indian and Pakistani children, which have shown that a diet heavy in carbohydrates and low in protein‐rich foods, fruits, and vegetables has a significant negative effect on child nutrition and growth [54, 55, 56].

In addition, multiple regression analysis of our study reveals a substantial association between single or multiple concurrent forms of undernutrition and family wealth index, parental education, and income (especially the mother's). The degree of parental education and economic adversity significantly contributes to the prevalence of a specific type of malnutrition in children under the age of 5 [28, 33]. Prior research conducted in Bangladesh and other South Asian nations has emphasized that parental education and wealth index are significant risk factors for child undernutrition, regardless of whether many contemporaneous forms or a single form of undernutrition is present [19]. Women with poor socioeconomic status and minimal educational attainment have less impact on household decision‐making processes that could potentially affect the nutritional health of children [20, 33].

In contrast, parents with higher levels of education are likely to have higher incomes, better access to food within their households, allocate a greater proportion of their resources towards their children's welfare, and have an improved standard of living. These factors ultimately contribute to their ability to offer better care for their children [28]. However, a significant portion of the population in Bangladesh is still worried about more extensive problems related to persistent poverty, and this would not indicate progress in reducing malnutrition at a community level [33]. In order to decrease malnutrition among children under the age of 5, it is advised to enhance the involvement of women in education and work, particularly in rural regions. This can be achieved by reducing socioeconomic disparities through the development of income‐generating industries and by reinforcing health programs that specifically target nutrition.

5. Conclusion

A considerable proportion of children under the age of 5 in the Atharabari union of Ishwargonj Upazila in Bangladesh are experiencing one or more concurrent forms of undernutrition. Male infants aged 36 months and older who were born in the lowest socioeconomic quintile have been recognized as significant risk factors for the co‐occurrence of multiple forms of malnutrition. The primary factors that differentiate multiple concurrent forms of undernutrition from a single form include incomplete or zero vaccination, postnatal complications, irregular intake of albendazole and vitamin A capsules, inadequate consumption of protein and vegetable‐containing foods, and the mother's level of education and occupation. To reduce the prevalence of wasting, stunting and underweight and to formulate an evidence‐based strategy to reduce undernutrition among under 5‐year‐old children in Bangladesh, policies should be implemented that focus on the risk factors determined by the study. To further improve nutritional status, it is crucial for several sectors, including government, non‐government, educational, social, cultural, and religious institutions, to work together firmly. Possible long‐term effective interventions to reduce child malnutrition include increasing parental education and decreasing socio‐economic inequality.

Author Contributions

Mukul Sarker Ashim: conceptualization, writing – original draft, methodology, data curation. Abhijit Das: formal analysis, writing – original draft, writing – review and editing, visualization. Rita Bhatta: supervision, writing – original draft, review and editing, validation, resources, project administration, methodology, conceptualization.

Conflicts of Interest

The authors declare no conflicts of interest.

Transparency Statement

The lead author Rita Bhatta affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.

Data Availability Statement

Data sharing is not applicable to this article as the article describes entirely theoretical research.