Malnutrition status of children aged under-5 years in Bangladesh: evidence from BDHS 2017-2018

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M. Arifur Rahman, Abu Sayed Md. Al Mamun, Md. Mobarak Hossain Khan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4274697/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Malnutrition is a major risk factor to create permanent, widespread damage to child's growth, development and well-being. This study aimed to determine the risk factors of malnutrition status of below five-years aged children in Bangladesh. Methods Analysis was conducted using data from Bangladesh Demographic & Health Survey (BDHS, 2017-18). A total number of 8402 under five-year old children’s data from BDHS 2017-18 were included in this study. Descriptive statistics, chi-square test and binary logistic regression models were implemented to examine the prevalence of malnutrition status and its association with the different selected socio-demographic factors in this study. Results The study found that the prevalence of stunting, wasting, underweight, and overweight of under-5 children were 31.0%, 8.8%, 22.0% and 2.4% respectively. Current age of children, division, mothers’ educational level, mothers’ height and BMI were found to be significant predictors for stunting and underweight children. Whereas, sex of child, mothers’ educational level and mothers’ BMI significantly impacted wasting. Furthermore, children’s overweight status was significantly associated with sex of child, current age of children, division, wealth index, mothers’ height and BMI. Conclusions Several geographical and socio-demographic factors significantly impacted on malnutrition status of Bangladeshi under-five children. Therefore, government of Bangladesh and other health authorities should focus on the findings of this study to develop and implement concrete policies in the aim to reduce complications arising from under-five child malnutrition in Bangladesh. Bangladesh Malnutrition DHS Determinants Public Health. Figures Figure 1 Background Child malnutrition issue has taken a great attention in global health problem. Because, the evidence shows that the malnutrition has a negative effect on child health, economic and educational performance [1]. Moreover, child malnutrition is a serious cause of mortality and morbidity worldwide [2,3]. WHO defines four anthropometric indicators of malnutrition such as, stunting (low height-for-age), wasting (low weight-for-height), underweight (low weight-for-age), and overweight (high weight-for-height). According to WHO Child Growth Standards, a child aged below 5-years is identified as under nutrition (stunting, wasting, underweight), if the corresponding Z-score is less than (-2) standard deviations from the median of the WHO reference population. Conversely, overweight identified for a child whose weight-for-height Z-score is in excess of two standard deviations (+2 SD) above the median of the reference population. Several studies show that the chronic and persistent malnutrition and disease infections are known to cause stunting in children [4,5]. Stunted child may face severe irreparable physical and cognitive damage, and pass this trait to his/her next generation child. In addition to the stunted child, a wasted child has higher chance of death than a non-wasted child. Underweight in child, on the other hand, may lead to low physical and mental growth, and overweight in child may cause non-communicable diseases later, at young or old ages [6,7]. In 2020, among about 678.2 million under-5 years aged child worldwide, 149.2 million (22%) are estimated to be stunted, while 45.4 million (6.7%) are estimated as wasted, 85.4 million (12.6%) are estimated to be underweight and 38.9 million child (5.7%) are estimated as overweight (7) . Since 2000, all these indicators have seen significant decline in percentages around the world, except overweight which has increased overall. According to 2020 estimates, majority of the stunted child live in Asia (especially Southern Asia and South-Eastern Asia) and Africa. Prevalence of child wasting is higher in Southern Asia, South-Eastern Asia, Western Asia and Northern Africa. Underweight is prevalent highly in Southern Asia and Africa, while overweight is highly prevalent in Australia and some part of northern Africa and Europe. Southern-Asian countries facing three of these four children health issues severely [7]. Among the 17 Sustainable Development Goals (SDG) to be achieved by 2030, goal-2 aimed for zero hunger, achieving food security and improving nutrition- will not be achieved, unless bringing down the prevalence of stunting, wasting, and underweight significantly. Although the percentage of stunted, wasted, and underweight child in Bangladesh reduced about 10% - 20% over the last decade, their current prevalence are still alarming. According to Bangladesh Demographic and Health Survey 2017-18 [8], in Bangladesh, one in every about 3 children aged below 5 years are stunted, 1 in about 11 are wasted, 1 in about 5 are underweight and 1 in about 40 are overweight. There are also numerous studies that have been done over the years around different regions of the world to identify demographic and economic factors influencing the prevalence of malnutrition of under-5 years aged children. Most of the studies were done in or based on the data of low- and middle-income countries in Southern Asia (e.g., Bangladesh, India, Pakistan, Afghanistan, Nepal, Maldives, and Indonesia etc.) and Eastern Africa (e.g., Ethiopia, Rwanda & Tanzania etc.). Studies on overweight were mostly focused in Europe and America. There are a good number of studies found that child’s age, parental education, household wealth, and child’s sex are the prime factors associated with stunting [9-12]. There are also other factors such as, short preceding birth interval, smaller size of child at birth, child delivered at home, unimproved toilet facility, shorter paternal heights, low dietary diversity and low number of antenatal care visits etc., associated with child stunting significantly. Mother’s BMI is found to be a common factor in majority of the studies covering wasting of child [11, 13-15]. Moreover, smaller sized child at birth, child of non or low educated mother, male child, and child from lower-wealth households have higher odds of being wasted. Child whose mothers are non-educated or have very low-level of education are more likely to have higher odds of being underweight and this is the most common factor found in the various studies [10, 11, 14, 16, 17]. Short preceding birth interval, smaller size of child at birth, low BMI of mothers, lack of clean water sources, and child’s recent illness are found to increase the odds of child being underweight too. Contrary to other three child health indicators, overweight occurs due to over nutrition and/or physical inactivity. Child from overweight or obese parents are commonly more likely to be overweight [18, 19, 20]. Larger weight at birth of child, smoking near to child, missing breakfast by child, child’s less quality sleep are some other factors identified to increase the odds of childhood overweight. Although there are a number of studies worked on to identify the demographic, economic and behavioral factors that are associated with the under-five child’s malnutrition. Our study extends that knowledge based on the latest BDHS (2017-18) data that is available. The results also describe any changes from the previous studies, and compares with other countries’ or region’s study outcomes. Data & Methods Source of the data and sample selection The Bangladesh Demographic and Health Survey (BDHS) 2017-2018 was considered for this study. This nationally representative cross-sectional survey was conducted under the National Institute for Population Research and Training (NIPORT) of the Ministry of Health and Family Welfare, Bangladesh. In this survey households were selected based on a two-stage stratified sampling. A detailed discussion of the survey methodology can be found in the report of BDHS 2017-2018 [8]. However, we considered the data of less than 5 years aged children of interviewed women, stored in KR file of BDHS 2017-2018 datasets. The following Figure 1 shows how cases are selected from the data. Dependent variable: In this study, the outcome variables were chosen based on the growth standards of World Health Organization (WHO). According to WHO, there are four anthropometric indicators such as stunting, wasting, underweight, and overweight. Child who is short for his or her age, underweight for his or her height, underweight for his or her age, and overweight for his or her height are treated as stunting, wasting, underweight, and overweight respectively. Independent variables: The socio-economic, demographic and anthropometric variables were selected as independent variables based on the previous studies [10, 24] to assess the effect on malnutrition status (stunting, wasting, underweight, and overweight). The independent variables with their indicator codes are given below: preceding birth interval (months) (< 24 = 1, 24 - 59 = 2, 60 =3), sex of child (Male = 1, Female = 2), age of child (months) (3 visits =3), divisions (Barisal = 1, Chittagong = 2, Dhaka = 3, Khulna = 4, Mymensingh = 5, Rajshahi = 6, Rangpur = 7, Sylhet = 8), type of place of residence (Urban = 1, Rural = 2), educational levels (No education = 1, Primary = 2, Secondary = 3, Higher = 4), wealth index (Poor = 1, Middle = 2, Rich = 3), Parity ( 1-4 = 1, ≥5 = 2), access to information (No = 1, Yes = 2), mother’s height (cm) (<145 = 1, ≥145 = 2), mother’s BMI (Underweight = 1, Normal = 2, Overweight = 3, Obese = 4), age at first cohabitation (years) (<18 = 1, ≥18 = 2), currently working (No = 1, Yes =2). Statistical analysis: In this study, Chi-squares tests were conducted to assess the primary significant association between socio-economic, demographic and anthropometric variables with malnutrition status of under 5 years children. The significant variables were taken based on the p-value of Chi-squares tests (p< 0.05) for constructing the logistic regression model [21]. The logistic regression models for each malnutrition status then fitted using the Maximum Likelihood Method to examine the type of the relationship with socio-economic, demographic and anthropometric variables. All analyses were conducted using SPSS 26 version and the sampling weights are used to minimize the sampling errors so that these results can enunciate the national scenario [8, 12]. Results A total of 8402 under-5 children were considered in this study. Among them, 31.0%, 8.8%, 22.0% and 2.4% suffered from stunting, wasting, underweight, and overweight, respectively. The prevalence of these nutritional statuses for different socio-demographic factors is given in Table 1. (Table 1) Preceding birth interval of a child was found to be significantly associated with both stunting and underweight of a child. Child with lower preceding birth interval were more likely to be stunted and underweight. Frequency of antenatal visits, mother’s age at first cohabitation and birth parity were also found associated at 5% significance level with child stunting and underweight. Mothers who paid lower number of visits for antenatal care and mothers who made their first cohabitation before 18 years of age were more likely to have their child to be stunted and/or overweight. Higher birth parity (>4) was associated with higher percentage of stunting and underweight in child. Sex of a child was identified to be associated with both wasting and overweight. Interestingly, male children were more likely to be wasted as well as overweight than their female counterparts. In other words, since wasting and overweight are two opposite indicators calculated from the same weight-for-height data, one may say that male children were less likely to be normal weighted than female children. Significant associations were also exhibited between the factors- age of child, administrative division where a child lived, type of place of residence, wealth status of the child’s family, mother’s access to information and mother’s height with three of the malnutrition types- stunting, underweight and overweight. A higher percentage of middle-aged children are found to be stunted, a higher fraction of older children was found as underweight and a higher proportion of younger children was found as overweight. A much higher percentage of children in Sylhet division were found to be stunted as well as underweight, while a higher percentage of children residing in Dhaka division found to be overweight compared to other administrative divisions. Children residing in rural residence were in higher percentages to be stunted and underweight than those in urban residence, who again in turn were found in higher percentages to be overweight than their rural counterparts. Children from less wealthy family were found associated with more stunting and underweight and those from much wealthy family were associated with more overweight problems. Mothers who had no access to information about maternal and child care, mothers who were shorter (<145cm) and mothers who were working (in time of the survey) had higher percentages of children to be stunted and underweight. On the other hand, mothers having access to information, tall stature and not working had higher percentages of overweight child. Both of mother’s educational attainment and mother’s BMI were found associated with all of the four malnutrition indicators. Lower educational achievement and lower BMI of mothers were associated with higher percentage of stunted, wasted and underweight children, whereas for the opposite scenarios, there were more overweight children. (Table 1). (Table 2) Determinants of stunting Table 2 demonstrated that odds of being stunted at age 12-23 months and 24-35 months were 2.53 (OR: 2.53, CI: 1.99-3.21, p< 0.001) and 3.51 (OR: 3.52, CI: 2.73-4.51, p<0.01) times to the children aged <12 months. The children residing in Dhaka were 34% (OR: 0.66, CI: 0.46-0.95, p<0.05) less likely to being stunted as compared to the children from Sylhet division. Odds of being stunted were 39% (OR: 0.61, CI: 0.42-0.88, p<0.01) lower for children living in Rangpur division when compared to children from Sylhet division. Children with primary and secondary educated mothers had 75% (OR: 1.75, CI: 1.13-2.73, p<0.01), and 67% (OR: 1.67, CI: 1.10-2.53, p<0.01) higher odds of stunting as compared to children whose mothers had higher education. Children whose mother had height less than 145 cm were 3.68 (OR: 3.68, CI: 2.84-4.77, p<0.001) times likely to be stunted as compared to their counterparts from taller mothers. Similarly, children from underweight mother had 31% (OR: 1.31, CI: 1.00-1.71, p<0.05) higher risk of stunting than children from normal weight mother. Determinants of wasting The odds of wasting were 1.24 (OR: 1.24, CI: 1.03-1.48, p<0.05) times for male children as compared to females. Children with uneducated, primary and secondary educated mothers had 87% (OR: 1.87, CI: 1.28-2.75, p<0.01), 41% (OR: 1.41, CI: 1.04-1.91, p<0.05) and 34% (OR: 1.34, CI: 1.01-1.79, p<0.05) higher odds of wasting as compared to children whose mothers had higher education. Similarly, children from underweight mother had 2.99 (OR: 2.99, CI: 1.62-5.50, p<0.001) times risk of wasting than children from normal weight mother. Determinants of underweight The odds of being underweight in age 12-23 months, 24-35 months were 1.46 (OR: 1.46, CI: 1.13-1.89, p<0.01) and 2.46 (OR: 2.46, CI: 1.90-3.18, p<0.01) times as compared to age <12 months children. For the underweight case, the odds were 0.63 (OR: 0.63, CI: 0.41-0.95, p<0.05), 0.56 (OR: 0.56, CI: 0.38-0.86, p<0.01), 0.56 (OR: 0.56, CI: 0.37-0.88, p<0.05) and 0.59 (OR: 0.59, CI: 0.39-0.90, p<0.05) times in children living in Barisal, Dhaka, Rajshahi and Rangpur division respectively as compared to children from Sylhet division. Odds of being underweight for children whose mother were uneducated (OR: 2.52, CI: 1.37-4.62, p<0.01), primary (OR: 1.76, CI: 1.01-3.05, p<0.05) and secondary educated (OR: 1.74, CI: 1.02-2.98, p<0.05) were higher as compared to higher educated mother. The other important significant variables to underweight were mothers’ height and mothers’ BMI. Children whose mother had height less than 145 cm were 2.41 (OR: 2.41, CI: 1.88-3.09, p<0.001) times likely to be stunted as compared to their counterpart. Similarly, children from underweight mother had 87% (OR: 1.87, CI: 1.41-2.45, p<0.001) times odds of underweight than children from normal weight mother. Children with obese mother had 41% (OR: 0.59, CI: 0.38-0.99, p<0.05) lower risk of being underweight than normal weight mother. Determinants of overweight The odds of overweight were 55% (OR: 1.55, CI: 1.06-2.25, p<0.05) higher for male children as compared to females. The odds of being overweight in age 12-23 months, 24-35 months, 36-47 months and 48-59 months were 0.57 (OR: 0.57, CI: 0.34-0.95, p<0.01), 0.39 (OR: 0.39, CI: 0.23-0.64, p<0.001), 0.38 (OR: 0.38, CI: 0.21-0.72, p<0.01) and 0.48 (OR: 0.48, CI: 0.28-0.84, p<0.05) times as compared to age <12 months children. Children living in Dhaka had 3.31 (OR: 3.31, CI: 1.04-10.55, p<0.05) times odds of being overweight as compared to Sylhet. For overweight cases, the odds were 0.57 (OR: 0.57, CI: 0.33-0.98, p<0.05) times in children from the middle-income family as compared to those from the rich family. Children whose mother had height less than 145 cm were 50% (OR: 0.50, CI: 0.26-0.97, p<0.05) less likely to be overweight as compared to their counterpart. Similarly, children from overweight and obese mother had 1.83 (OR: 1.83, CI: 1.25-2.70, p<0.001) and 2.74 (OR 2.74, CI: 1.50-5.03, p<0.001) times odds of being overweight than those children from normal-weight mother. Discussion In this study, the predictor variables current age of children, sex of child, division, mothers’ educational level, mothers’ height and BMI were found as significantly related to the under-nutrition status, whereas the predictor variables sex of child, current age of children, division, wealth index, mothers’ height and BMI were significantly associated with child over-nutrition status. This finding suggested that sex of child was an important risk factor for wasting and overweight. Other studies [10, 22] on Bangladesh demographic and health survey also found that female children were less likely to be wasted and over-weight than male children. The male children are more vulnerable to develop malnutrition because they require comparatively more calories for growth and development [23]. Although the overweight of under five years children is not that much concerning issue in Bangladesh as the percentage is only 2.4%, despite this fact, it was found that the male children have higher chance to be over-weight than female. This probably due to the gender bias in the family where parents are more concerned about the male child than female which is very common in the Indian subcontinent [3]. This study found that childhood stunting and underweight significantly increased with child’s age. Children within the age group of 12–59 months were more likely to be stunted and underweight compared to the younger children (less than 12 months). A comparable finding was also reported by other studies for developing nations [10, 14, 24]. The increase in child stunting and underweight with age can be prevented by giving the supplementary food along with breast feeding. However, the hygiene of supplementary foods is another factor as the other study [25] shows that when the immune protective impacts of breast milk diminish, children are exposed to contaminated supplementary foods and the spread of infectious disease which expands the supplement prerequisites. The odds of being overweight were lower in age 1-4 years (12 months-59 months) as compared to 0 (<12 months) years children. The results show that high percentage of mothers provide formula milk to the children in their early stages which lead to overweight in their later infancy [26]. In Bangladesh 98% women expressed a strong desire to breastfeed exclusively [27]. However, they are influenced by the advertisements about the feeding of the formula milk to children. The advertises claim brain development, nutrition, and other benefits to the babies, which make mothers think that if they feed these to their babies then their babies will be healthy. WHO and UNICEF [27] states that nearly 60% of post-partum women had received a recommendation from a health professional to feed a formula product. Thus, awareness among the mothers and health professionals is needed about feeding formula milk. The prevalence of stunting and underweight in Sylhet was higher than the other divisions. However, significantly lower wasting were found in Dhaka and Rangpur division and lower underweight were found in Barishal compared to Sylhet division. This is due to the fact that educational status and economic solvency in the Sylhet division, in general, is lower compared to the capital, Dhaka [28]. On the other hand, the prevalence of being overweight was higher in the Dhaka division compared to Sylhet division. Two reasons could be playing role behind this. A recent report shows that only 2 percent children of the capital have the access to playgrounds. Thus, the lack of sports or physical activities creates a huge setback in children's physical and mental growth and it seems to be one of the major reasons behind the current uptrend graph of obesity of the children who lives in Dhaka. Another reason is the growing fast-food restaurants in Dhaka city, which are the spots for recreational family gatherings [10]. In developing countries, rural–urban inequality in child malnutrition remained unchanged over the last decades due to economic hardship, inadequate health facilities, and insufficient education [24, 29]. However, the results of this study were consistent with the literatures in the case of higher overweight prevalence in urban areas [10, 30]. In the present setting of Bangladesh, fast food restaurants and super shops are gaining popularity in the urban areas, filling in as spots for a leisure family gathering [31]. Furthermore, with extended urban relocation towards already overcrowded cities, expanded housing and foundations have thinned the open spaces and consequently it reduces the spaces for physical activities [32, 33] resulting in higher indoor recreational activities and increased sitting time [34]. Our study also found that children who lived in rural areas of Bangladesh were more vulnerable to become stunted and underweighted. These results are consistent with some previous studies conducted and identified that children settled in rural areas are at higher risk to be undernourished [29, 35]. The present study showed that children of mothers with no formal education were more prone to be acutely malnourished (wasted and underweight) as compared to children of higher educated mothers. This association is found, in this study, between maternal education and all form of malnutrition. Result from the present study consistent with several previous studies [14, 36]. Educated mothers are well informed about the health needs and nutritional facts of their children and prefer to use better hygiene and sanitation facilities. Moreover, they make comparative choices from available health services for improved healthcare of their children [37]. The wealth index was not significantly associated with undernourishment but the odds of being overweight were significantly higher with the richest family compared to poorest. This result is consistent with the other literatures [10, 38]. Wealthy women get higher intake of nutrients than poor women [39] and wealthy families takes higher amount of processed food, which in turns rises the weights of children of those mothers in general [40, 41]. In this study, children of short stature mothers (height = < 145 cm) were found more likely to be stunted and underweight. Our result was in line with another study [14]. Our study also found that, children of short stature mothers (height = < 145 cm) were found less likely to be overweight than the taller mother. The reason may be the lower health stock of short height mothers [42]. Because of the lower health stock, the short height mothers have insufficient nutrients to the fetus which reduce the fetal growth of infants. This could result the low birth weight and influencing babies’ health [43]. Previous evidence had also shown several adverse health related consequences, including the nutritional outcomes, in children of mothers of low height (or short stature) [44, 45]. Body mass index (BMI) is one of the key factors to access the Mother’s nutritional status and it is associated with child’s nutritional status [46]. The risk of being malnourished for a child (stunting, wasting and underweight) was higher, whose mother’s BMI was below normal (<18.5 kg/m2). It can be also noted that the higher risk of having overweight child belongs to overweight mothers and it’s chance is almost double if the mother is in obesity category. These findings are parallel to the previous studies [44, 46, 47], which shows that there is an adverse effect of mothers’ BMI on children malnutrition status. Since the mother’s BMI is one of the key factors of having malnourished and over nutation child, a great management of BMI should be taken by clinical management and counseling the pregnant mothers to reduce the risk of overweight child. On the other hand, mother’s nutritional status should be considered when making policies for reducing the child malnutrition. Strengths and Limitations The strength of our study is that the current Bangladesh Demographic and Health Survey data, i.e., BDHS 2017-2018 data was used. In BDHS data, the overall probability of selection of each household is not a constant. Thus, all analysis was done using appropriate sampling weights in order to reduce the biasness of our findings. Thus, the results of this research can be used nationally. Moreover, the survey had a very small percentage of missing responses (4.08%) which leads to large sample sizes. This study also comes with limitations. Because of the cross-sectional design of the study, it is very difficult to say the exact causal relationships of the variables with malnutrition. The socioeconomic status of the households may be changed at present as the data are collected few years back. Conclusion & Recommendations In this article, our objective was to determine the socio-demographic factors which are significantly related to malnutrition of less than five-years aged children in Bangladesh. This study reveals that mothers’ education level and BMI are two common influencing factors for malnutrition of child. No or less educated mothers and mothers with low BMI are tend to have child with malnutrition. Furthermore, the age of child also impacts child’s nutrition. Higher aged children are more likely to be stunted or underweight, and conversely less likely to be overweight overall. This study also reveals that the male children are more likely to be overweight as well as wasted than female children. Children from the greater income households tend to have overweight than the lower income households. Most of the overweight children belong to the Dhaka division; however, children from Sylhet division are mostly suffering from malnutrition. This study also shows that overweight and taller mothers tend to have overweight children. Moreover, shorter heighted mothers tend to have child with malnutrition. Food habit of children of Dhaka and Sylhet needed to be studied to identify clearly why children from Dhaka tend to be overweight and those from Sylhet tend to be malnourished. Women’s education is again needed to be strongly taken care of, as educated mothers can take educated decisions regarding her and her child’s wellbeing. Mothers’ weight should be kept at check at a normal BMI, to avoid both malnutrition as well as overweight problem in their offspring. Proper food intake and nutritional balance should be maintained even if a child gets older, because this study found that at higher ages children tend to be more malnourished. Though Bangladesh had declining child malnutrition over the past years, however, the results shows that the percentage of stunting (31%) and underweight (22%) are still distressing. Thus, to achieve the Sustainable Development Goal (SDG) of 2030- improving nutrition (goal-2), we need to focus on to the key factors behind malnutrition to effectively control their prevalence. Government’s clear directives along with private initiatives in these aspects can bring about a healthy young generation. Abbreviations BDHS: Bangladesh Demographic and Health Survey BMI: Body mass index CI: Confidence Interval NIPORT: National Institute of Population Research and Training OR: Odds ratio SDG: Sustainable Development Goal WHO: World Health Organization Declarations Acknowledgements The authors acknowledge the National Institute of Population Research and Training (NIPORT), and ICF for providing the BDHS 2017-2018 dataset. Funding There is no funding source for this research. Availability of data and materials The data is available in the Demographic and Health Survey website (https://dhsprogram.com/data/dataset/Bangladesh_Standard-DHS_2017.cfm?flag=0). Contributions Sohel Rana- Conceptualization, Formal Analysis, Validation, Writing-original draft, Writing-review & editing. F. M. Arifur Rahman- Data curation, Formal Analysis, Validation, Visualization, Writing-original draft, Writing-review & editing. Abu Sayed Md. Al Mamun- Conceptualization, Formal Analysis, Writing-original draft. Md. Mobarak Hossain Khan- Writing-review & editing. Corresponding author Correspondence to Sohel Rana. Ethics declarations Ethics approval and consent to participate National Institute of Population Research and Training (NIPORT), and ICF is responsible for ethics approval and consent to participate. Because, the BDHS 2017-2018 datasetwas collected under the National Institute for Population Research and Training (NIPORT) of the Ministry of Health and Family Welfare, Bangladesh and ICF. Competing interests The authors declare that they have no competing interests. References Zerga AA, Tadesse SE, Ayele FY et al . Impact of malnutrition on the academic performance of school children in Ethiopia: A systematic review and meta-analysis. SAGE Open Med 10:20503121221122398.2022; DOI: 10.1177/20503121221122398. Caulfield LE, de Onis M. Blössner M et al . Undernutrition as an underlying cause of child deaths associated with diarrhea, pneumonia, malaria, and measles. Am J Clin Nutr. 2004; 80 (1), 193-198. DOI: 10.1093/ajcn/80.1.193. De P, Chattopadhyay N. Effects of malnutrition on child development: Evidence from a backward district of India. Clin Epidemiol Glob Health. 2019; 7 (3), 439-445. DOI: 10.1016/j.cegh.2019.01.014. Vonaesch P, Tondeur L, Breurec S et al . Factors associated with stunting in healthy children aged 5 years and less living in Bangui (RCA). PLoS One. 2017; 12(8):e0182363. DOI: 10.1371/journal.pone.0182363. Brennhofer S, Reifsnider E, Bruening M. Malnutrition coupled with diarrheal and respiratory infections among children in Asia: A systematic review. Public Health Nurs. 2017; 34(4), 401-409. DOI: 10.1111/phn.12273. De Sanctis V, Soliman A, Alaaraj N et al . Early and Long-term Consequences of Nutritional Stunting: From Childhood to Adulthood. Acta bio-medica : Atenei Parmensis. 2021; 92(1), e2021168. DOI: 10.23750/abm.v92i1.11346. United Nations Children’s Fund (UNICEF), World Health Organization, International Bank for Reconstruction and Development/The World Bank. Levels and trends in child malnutrition: key findings of the 2021 edition of the joint child malnutrition estimates. New York: United Nations Children’s Fund. 2021; License: CC BY-NC-SA 3.0 IGO. ISBN (WHO) 978-92-4-002525-7 (electronic version). National Institute of Population Research and Training (NIPORT), and ICF. Bangladesh Demographic and Health Survey 2017-18: Key Indicators. Dhaka, Bangladesh, and Rockville, Maryland, USA: NIPORT, and ICF. 2019. Habimana S, Biracyaza E. Risk Factors of Stunting Among Children Under 5 Years Of Age In The Eastern And Western Provinces Of Rwanda: Analysis Of Rwanda Demographic And Health Survey 2014/2015. Pediatric Health Med Ther. 2019; 10, 115-130. DOI: 10.2147/PHMT.S222198. Hossain S, Chowdhury PB, Biswas RK et al . Malnutrition status of children under 5 years in Bangladesh: A sociodemographic assessment. Child Youth Serv Rev. 2020; 117:105291 DOI: 10.1016/j.childyouth.2020.105291. Li Z, Kim R, Vollmer S et al . Factors Associated with Child Stunting, Wasting, and Underweight in 35 Low- and Middle-Income Countries. JAMA Netw Open. 2020; 3(4):e203386. DOI: 10.1001/jamanetworkopen.2020.3386. Chowdhury TR., Chakrabarty S, Rakib M et al . Risk factors for child stunting in Bangladesh: an analysis using MICS 2019 data. Arch Pub Health. 2022; 80:126. DOI: 10.1186/s13690-022-00870-x. Harding KL, Aguayo VM, and Webb P. Factors associated with wasting among children under five years old in South Asia: Implications for action. PLoS ONE. 2018; 13 (7): e0198749. DOI: 10.1371/journal.pone.0198749. Khan S, Zaheer S, Safdar NF. Determinants of stunting, underweight and wasting among children < 5 years of age: evidence from 2012-2013 Pakistan demographic and health survey. BMC Public Health. 2019; 19 (1):358. DOI: 10.1186/s12889-019-6688-2. Wali N, Agho KE, Renzaho AMN Wasting and Associated Factors among Children under 5 Years in Five South Asian Countries (2014–2018): Analysis of Demographic Health Surveys. Int J Environ Res Public Health. 2021; 18:4578. DOI: 10.3390/ijerph18094578. Tosheno D, Adinew YM, Thangavel T et al . Risk Factors of Underweight in Children Aged 6–59 Months in Ethiopia. J Nutr Metab. 2017; 2017:6368746. DOI: 10.1155/2017/6368746. Moshi CC, Sebastian PJ, Mushumbusi DG et al . Determinants of underweight among children aged 0–23 months in Tanzania. Food Sci. Nutr. 2021; 10, 1167-1174. DOI: 10.1002/fsn3.2748. Brophy S, Cooksey R, Gravenor, MB et al . Risk factors for childhood obesity at age 5: Analysis of the Millennium Cohort Study. BMC Public Health. 2009; 9:467. DOI:10.1186/1471-2458-9-467. Dev DA, McBride BA, Fiese BH et al . Risk factors for overweight/obesity in preschool children: an ecological approach. Child Obes. 2013; 9(5), 399–408. DOI: 10.1089/CHI.2012.0150. Saha J, Chouhan P, Ahmed F et al . Overweight/Obesity Prevalence among Under-Five Children and Risk Factors in India: A Cross-Sectional Study Using the National Family Health Survey (2015–2016). Nutrients. 2022; 14:3621. DOI: 10.3390/nu14173621. Gortmaker SL, Hosmer DW, Lemeshow S. Applied logistic regression. Contemp Sociol. 1994; 23(1), 159. DOI:10.2307/2074954. Fakir AMS, Khan MWR. Determinants of malnutrition among urban slum children in Bangladesh. Health Econ Rev. 2015; 5, 22. DOI: 10.1186/S13561-015-0059-1. Kavosi E, Hassanzadeh Rostami Z, Kavosi Z et al . Prevalence and Determinants of Under-Nutrition Among Children Under Six: A Cross-Sectional Survey in Fars Province, Iran. Int J Health Policy Manag. 2014; 3(2), 71-76. DOI: 10.15171/ijhpm.2014.63. Das S, Gulshan J. Different forms of malnutrition among under five children in Bangladesh: A cross sectional study on prevalence and determinants. BMC Nutrition. 2017; 3(1). DOI: 10.1186/s40795-016-0122-2. Shrimpton R, Victora CG, de Onis et al . Worldwide timing of growth faltering: implications for nutritional interventions. Pediatrics. 2001; 107(5), E75. DOI: 10.1542/peds.107.5.e75. Taveras EM, Rifas-Shiman SL, Belfort MB et al . Weight status in the first 6 months of life and obesity at 3 years of age. Pediatrics. 2009; 123(4), 1177–1183. DOI: 10.1542/peds.2008-1149. WHO, UNICEF. Progress on breastfeeding in Bangladesh undermined by aggressive, Press release, 23 February, 2022. Tareque MI, Begum S, Saito Y. Inequality in disability in Bangladesh. PLoS ONE. 2014; DOI: 10.1371/journal.pone.0103681. Srinivasan CS, Zanello G, Shankar B. Rural-urban disparities in child nutrition in Bangladesh and Nepal. BMC Public Health. 2013; 13(1):581. DOI: 10.1186/1471- 2458-13-581 Pirgon Ö, Aslan N. The role of urbanization in childhood obesity. JCRPE J. Clin. Res. Pediatr. 2015; DOI: 10.4274/jcrpe. 1984. Islam N, Ullah GMS. Factors Affecting Consumers Preferences On Fast Food Items In Bangladesh. J Appl Bus Res. 2010; 26(4). DOI: 10.19030/jabr.v26i4.313. Melby CL, Orozco F, Ochoa D et al . Nutrition and physical activity transitions in the Ecuadorian Andes: Differences among urban and rural-dwelling women. American journal of human biology : Hum Biol. 2017; 29(4), DOI: 10.1002/ajhb.22986. Reardon, Hernandez, Ricardo et al . Urbanization, diet change, and the transformation of the downstream and midstream of the agrifood system: Effects on the poor in Africa and Asia. Econ J. 2015; 66: 43 - 63. Goryakin Y, Suhrcke M. Economic development, urbanization, technological change and overweight: What do we learn from 244 Demographic and Health Surveys? Econ Hum Biol. 2014; 14, 109-127. DOI: 10.1016/j.ehb.2013.11.003. Van de Poel E, O'Donnell O, Van Doorslaer E. Are urban children really healthier? Evidence from 47 developing countries. Soc sc. Med. 2007; 65(10), 1986–2003. DOI: 10.1016/j.socscimed.2007.06.032 Mishra K, Kumar P, Basu S et al . Risk factors for severe acute malnutrition in children below 5 y of age in India: a case-control study. Indian J Pediatr. 2014; 81(8):762–5. DOI:10.1007/s12098-013-1127-3 Tariq J, Sajjad A, Zakar R et al . Factors Associated with Undernutrition in Children under the Age of Two Years: Secondary Data Analysis Based on the Pakistan Demographic and Health Survey 2012-2013. Nutrients. 2018; 10(6), 676. DOI: 10.3390/nu10060676 Navalpotro L, Regidor E, Ortega P et al . Area-based socioeconomic environment, obesity risk behaviours, area facilities and childhood overweight and obesity: socioeconomic environment and childhood overweight. Prev. Med. 2012; 55(2), 102–107. DOI: 10.1016/j.ypmed.2012.05.012. Das S, Fahim S, Islam M et al . Prevalence and sociodemographic determinants of household-level double burden of malnutrition in Bangladesh. Public Health Nutr. 2019; 22(8), 1425-1432. DOI:10.1017/S1368980018003580. Morgan K, Sonnino R. The urban foodscape: World cities and the new food equation. Cambridge J. Reg. Econ. Soc. 2010. DOI: 10. 1093/cjres/rsq007 Rahman S. Obesity in junk food generation in Asia: A health time bomb that needs early defusing! South East Asia J Public Health. 2013; 3(1):1-2. DOI: 10.3329/seajph.v3i1.17703. Jananthan R, Wijesinghe D, Sivananthewerl T. Maternal Anthropometry as a Predictor of Birth Weight. J Trop Agric. 2009; 21(1), 89-98. DOI: 10.4038/tar.v21i1.2590. Hart, N. Famine, Maternal Nutrition and Infant Mortality: A Re-Examination of the Dutch Hunger Winter. Popul Stud. 1993; 47(1), 27–46. http://www.jstor.org/stable/2175224. Subramanian SV, Ackerson LK, Smith GD et al . Association of maternal height with child mortality, anthropometric failure, and anemia in India. JAMA. 2009; 301(16):1691–1701. DOI:10.1001/jama.2009.548. Addo OY, Stein AD, Fall CH et al . Maternal height and child growth patterns. J Pediatr. 2013; 163(2), 549–54. DOI: 10.1016/j.jpeds.2013.02.002. Akombi BJ, Agho KE, Merom D et al . Multilevel analysis of factors associated with wasting and underweight among children under five years in Nigeria. Nutrients. 2017; 9(1): 44. DOI: 10.3390/nu9010044. Hasan MT, Soares Magalhães, Williams GM et al . Long-term changes in childhood malnutrition are associated with long-term changes in maternal BMI: evidence from Bangladesh, 1996-2011. The American journal of Clin Nutr. 2016; 104(4), 1121–1127. DOI: 10.3945/ajcn.115.111773 Tables Tables 1 to 2 are available in the Supplementary Files section Additional Declarations No competing interests reported. Supplementary Files Tables.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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M. Arifur Rahman","email":"","orcid":"","institution":"East West University","correspondingAuthor":false,"prefix":"","firstName":"F.","middleName":"M. Arifur","lastName":"Rahman","suffix":""},{"id":293972498,"identity":"53811353-96e5-4279-a033-79b8e8516c76","order_by":2,"name":"Abu Sayed Md. Al Mamun","email":"","orcid":"","institution":"University of Rajshahi","correspondingAuthor":false,"prefix":"","firstName":"Abu","middleName":"Sayed Md. Al","lastName":"M","suffix":"Md."},{"id":293972499,"identity":"6185cc50-a6c6-4130-a9d1-049ee665c4fe","order_by":3,"name":"Md. Mobarak Hossain Khan","email":"","orcid":"","institution":"East West University","correspondingAuthor":false,"prefix":"","firstName":"Md.","middleName":"Mobarak Hossain","lastName":"Khan","suffix":""}],"badges":[],"createdAt":"2024-04-16 09:02:39","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4274697/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4274697/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":55517666,"identity":"3b91237f-4ea7-41d2-af2e-bdd3750732a3","added_by":"auto","created_at":"2024-04-29 13:26:31","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":81950,"visible":true,"origin":"","legend":"\u003cp\u003eCase selection overview\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4274697/v1/cbb05073326a6e913e3409e7.png"},{"id":57845567,"identity":"92b5ab69-5cf7-4f1e-8be9-7b9bca5ee2ad","added_by":"auto","created_at":"2024-06-06 10:40:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":490486,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4274697/v1/c719031f-dd2d-49f9-bd86-9be17b5c8365.pdf"},{"id":55517665,"identity":"d2a8ba0c-1799-4f9f-afeb-94c92e440c4c","added_by":"auto","created_at":"2024-04-29 13:26:30","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":42952,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-4274697/v1/1bf46b76664c469739a6cedb.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Malnutrition status of children aged under-5 years in Bangladesh: evidence from BDHS 2017-2018","fulltext":[{"header":"Background","content":"\u003cp\u003eChild malnutrition issue has taken a great attention in global health problem. Because, the evidence shows that the malnutrition has a negative effect on child health, economic and educational performance\u0026nbsp;[1].\u0026nbsp;Moreover, child malnutrition is a serious cause of mortality and morbidity worldwide [2,3].\u0026nbsp;WHO defines four anthropometric indicators of malnutrition such as, stunting (low height-for-age), wasting (low weight-for-height), underweight (low weight-for-age), and overweight (high weight-for-height). According to WHO Child Growth Standards, a child aged below 5-years is identified as under nutrition (stunting, wasting, underweight), if the corresponding Z-score is less than (-2) standard deviations from the median of the WHO reference population. Conversely, overweight identified for a child whose weight-for-height Z-score is in excess of two standard deviations (+2 SD) above the median of the reference population.\u003c/p\u003e\n\u003cp\u003eSeveral studies show that the chronic and persistent malnutrition and disease infections are known to cause stunting in children\u0026nbsp;[4,5].\u0026nbsp;Stunted child may face severe irreparable physical and cognitive damage, and pass this trait to his/her next generation child. \u0026nbsp;In addition to the stunted child, a wasted child has higher chance of death than a non-wasted child. Underweight in child, on the other hand, may lead to low physical and mental growth, and overweight in child may cause non-communicable diseases later, at young or old ages [6,7].\u003c/p\u003e\n\u003cp\u003eIn 2020, among about 678.2 million under-5 years aged child worldwide, 149.2 million (22%) are estimated to be stunted, while 45.4 million (6.7%) are estimated as wasted, 85.4 million (12.6%) are estimated to be underweight and 38.9 million child (5.7%) are estimated as overweight\u003csup\u003e(7)\u003c/sup\u003e. Since 2000, all these indicators have seen significant decline in percentages around the world, except overweight which has increased overall. According to 2020 estimates, majority of the stunted child live in Asia (especially Southern Asia and South-Eastern Asia) and Africa. Prevalence of child wasting is higher in Southern Asia, South-Eastern Asia, Western Asia and Northern Africa. Underweight is prevalent highly in Southern Asia and Africa, while overweight is highly prevalent in Australia and some part of northern Africa and Europe. Southern-Asian countries facing three of these four children health issues severely [7].\u003c/p\u003e\n\u003cp\u003eAmong the 17 Sustainable Development Goals (SDG) to be achieved by 2030, goal-2 aimed for zero hunger, achieving food security and improving nutrition- will not be achieved, unless bringing down the prevalence of stunting, wasting, and underweight significantly. Although the percentage of stunted, wasted, and underweight child in Bangladesh reduced about 10% - 20% over the last decade, their current prevalence are still alarming. According to Bangladesh Demographic and Health Survey 2017-18\u0026nbsp;[8],\u0026nbsp;in Bangladesh, one in every about 3 children aged below 5 years are stunted, 1 in about 11 are wasted, 1 in about 5 are underweight and 1 in about 40 are overweight.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThere are also numerous studies that have been done over the years around different regions of the world to identify demographic and economic factors influencing the prevalence of malnutrition of under-5 years aged children. Most of the studies were done in or based on the data of low- and middle-income countries in Southern Asia (e.g., Bangladesh, India, Pakistan, Afghanistan, Nepal, Maldives, and Indonesia etc.) and Eastern Africa (e.g., Ethiopia, Rwanda \u0026amp; Tanzania etc.). Studies on overweight were mostly focused in Europe and America.\u003c/p\u003e\n\u003cp\u003eThere are a good number of studies found that child’s age, parental education, household wealth, and child’s sex are the prime factors associated with stunting\u0026nbsp;[9-12].\u0026nbsp;There are also other factors such as, short preceding birth interval, smaller size of child at birth, child delivered at home, unimproved toilet facility, shorter paternal heights, low dietary diversity and low number of antenatal care visits etc., associated with child stunting significantly. Mother’s BMI is found to be a common factor in majority of the studies covering wasting of child [11, 13-15].\u0026nbsp; \u0026nbsp;Moreover, smaller sized child at birth, child of non or low educated mother, male child, and child from lower-wealth households have higher odds of being wasted. Child whose mothers are non-educated or have very low-level of education are more likely to have higher odds of being underweight and this is the most common factor found in the various studies\u0026nbsp;[10, 11, 14, 16, 17].\u0026nbsp;Short preceding birth interval, smaller size of child at birth, low BMI of mothers, lack of clean water sources, and child’s recent illness are found to increase the odds of child being underweight too. Contrary to other three child health indicators, overweight occurs due to over nutrition and/or physical inactivity. Child from overweight or obese parents are commonly more likely to be overweight [18, 19, 20].\u0026nbsp; Larger weight at birth of child, smoking near to child, missing breakfast by child, child’s less quality sleep are some other factors identified to increase the odds of childhood overweight.\u003c/p\u003e\n\u003cp\u003eAlthough there are a number of studies worked on to identify the demographic, economic and behavioral factors that are associated with the under-five child’s malnutrition. Our study extends that knowledge based on the latest BDHS (2017-18) data that is available. The results also describe any changes from the previous studies, and compares with other countries’ or region’s study outcomes.\u003c/p\u003e"},{"header":"Data \u0026 Methods","content":"\u003cp\u003e\u003cstrong\u003eSource of the data and sample selection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Bangladesh Demographic and Health Survey (BDHS) 2017-2018 was considered for this study. This nationally representative cross-sectional survey was conducted under the National Institute for Population Research and Training (NIPORT) of the Ministry of Health and Family Welfare, Bangladesh. In this survey households were selected based on a two-stage stratified sampling. A detailed discussion of the survey methodology can be found in the report of BDHS 2017-2018 [8]. However, we considered the data of less than 5 years aged children of interviewed women, stored in KR file of BDHS 2017-2018 datasets. \u0026nbsp;The following Figure 1 shows how cases are selected from the data. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDependent variable:\u003c/strong\u003e In this study, the outcome variables were chosen based on the growth standards of World Health Organization (WHO). According to WHO, there are four anthropometric indicators such as stunting, wasting, underweight, and overweight. Child who is short for his or her age, underweight for his or her height, underweight for his or her age, and overweight for his or her height are treated as stunting, wasting, underweight, and overweight respectively. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIndependent variables:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe socio-economic, demographic and anthropometric variables were selected as independent variables based on the previous studies\u0026nbsp;[10, 24] to assess the effect on malnutrition status (stunting, wasting, underweight, and overweight). The independent variables with their indicator codes are given below: preceding birth interval (months) (\u0026lt; 24 = 1, 24 - 59 = 2, \u0026nbsp;60 =3), sex of child (Male = 1, Female = 2), \u0026nbsp;age of child (months) \u0026nbsp;(\u0026lt;12 =1, 12-23= 2, 24-35 = 3, 36-47= 4, 48-59 = 5), had diarrhea recently (No = 1, Yes =2), ever breastfed (No = 1, Yes =2), frequency of antenatal visits (No visit =1, 1-3 visits = 2, \u0026gt;3 visits =3), divisions (Barisal = 1, Chittagong = 2, Dhaka = 3, Khulna = 4, Mymensingh = 5, Rajshahi = 6, Rangpur = 7, Sylhet = 8), type of place of residence (Urban = 1, Rural = 2), educational levels (No education = 1, Primary = 2, Secondary = 3, \u0026nbsp;Higher = 4), wealth index (Poor = 1, Middle = 2, \u0026nbsp;Rich = 3), Parity ( 1-4 = 1, ≥5 = 2), access to information (No = 1, Yes = 2), mother’s height \u0026nbsp;(cm) (\u0026lt;145 = 1, \u0026nbsp;≥145 = 2), mother’s BMI (Underweight = 1, Normal = 2, Overweight = 3, \u0026nbsp;Obese = 4), age at first cohabitation (years) \u0026nbsp; (\u0026lt;18 \u0026nbsp;= 1, \u0026nbsp;≥18 = 2), currently working (No = 1, Yes =2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis:\u003c/strong\u003e In this study, Chi-squares tests were conducted to assess the primary significant association between socio-economic, demographic and anthropometric variables with malnutrition status of under 5 years children. The significant variables were taken based on the p-value of Chi-squares tests (p\u0026lt; 0.05) for constructing the logistic regression model [21]. \u0026nbsp; The logistic regression models for each malnutrition status then fitted using the Maximum Likelihood Method to examine the type of the relationship with socio-economic, demographic and anthropometric variables. All analyses were conducted using SPSS 26 version and the sampling weights are used to minimize the sampling errors so that these results can enunciate the national scenario [8, 12].\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 8402 under-5 children were considered in this study. Among them, 31.0%, 8.8%, 22.0% and 2.4% suffered from stunting, wasting, underweight, and overweight, respectively. The prevalence of these nutritional statuses for different socio-demographic factors is given in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(Table 1)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePreceding birth interval of a child was found to be significantly associated with both stunting and underweight of a child. Child with lower preceding birth interval were more likely to be stunted and underweight. Frequency of antenatal visits, mother’s age at first cohabitation and birth parity were also found associated at 5% significance level with child stunting and underweight. Mothers who paid lower number of visits for antenatal care and mothers who made their first cohabitation before 18 years of age were more likely to have their child to be stunted and/or overweight. Higher birth parity (\u0026gt;4) was associated with higher percentage of stunting and underweight in child.\u003c/p\u003e\n\u003cp\u003eSex of a child was identified to be associated with both wasting and overweight. Interestingly, male children were more likely to be wasted as well as overweight than their female counterparts. In other words, since wasting and overweight are two opposite indicators calculated from the same weight-for-height data, one may say that male children were less likely to be normal weighted than female children.\u003c/p\u003e\n\u003cp\u003eSignificant associations were also exhibited between the factors- age of child, administrative division where a child lived, type of place of residence, wealth status of the child’s family, mother’s access to information and mother’s height with three of the malnutrition types- stunting, underweight and overweight. A higher percentage of middle-aged children are found to be stunted, a higher fraction of older children was found as underweight and a higher proportion of younger children was found as overweight. A much higher percentage of children in Sylhet division were found to be stunted as well as underweight, while a higher percentage of children residing in Dhaka division found to be overweight compared to other administrative divisions. Children residing in rural residence were in higher percentages to be stunted and underweight than those in urban residence, who again in turn were found in higher percentages to be overweight than their rural counterparts. Children from less wealthy family were found associated with more stunting and underweight and those from much wealthy family were associated with more overweight problems. Mothers who had no access to information about maternal and child care, mothers who were shorter (\u0026lt;145cm) and mothers who were working (in time of the survey) had higher percentages of children to be stunted and underweight. On the other hand, mothers having access to information, tall stature and not working had higher percentages of overweight child.\u003c/p\u003e\n\u003cp\u003eBoth of mother’s educational attainment and mother’s BMI were found associated with all of the four malnutrition indicators. Lower educational achievement and lower BMI of mothers were associated with higher percentage of stunted, wasted and underweight children, whereas for the opposite scenarios, there were more overweight children. (Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(Table 2)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeterminants of stunting\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 2 demonstrated that odds of being stunted at age 12-23 months and 24-35 months were 2.53 (OR: 2.53, CI: 1.99-3.21, p\u0026lt; 0.001) and 3.51 (OR: 3.52, CI: 2.73-4.51, p\u0026lt;0.01) times to the children aged \u0026lt;12 months. The children residing in Dhaka were 34% (OR: 0.66, CI: 0.46-0.95, p\u0026lt;0.05) less likely to being stunted as compared to the children from Sylhet division. Odds of being stunted were 39% (OR: 0.61, CI: 0.42-0.88, p\u0026lt;0.01) lower for children living in Rangpur division when compared to children from Sylhet division. Children with primary and secondary educated mothers had 75% (OR: 1.75, CI: 1.13-2.73, p\u0026lt;0.01), and 67% (OR: 1.67, CI: 1.10-2.53, p\u0026lt;0.01) higher odds of stunting as compared to children whose mothers had higher education. Children whose mother had height less than 145 cm were 3.68 (OR: 3.68, CI: 2.84-4.77, p\u0026lt;0.001) times likely to be stunted as compared to their counterparts from taller mothers. Similarly, children from underweight mother had 31% (OR: 1.31, CI: 1.00-1.71, p\u0026lt;0.05) higher risk of stunting than children from normal weight mother.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeterminants of wasting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe odds of wasting were 1.24 (OR: 1.24, CI: 1.03-1.48, p\u0026lt;0.05) times for male children as compared to females. Children with uneducated, primary and secondary educated mothers had 87% (OR: 1.87, CI: 1.28-2.75, p\u0026lt;0.01), 41% (OR: 1.41, CI: 1.04-1.91, p\u0026lt;0.05) and 34% (OR: 1.34, CI: 1.01-1.79, p\u0026lt;0.05) higher odds of wasting as compared to children whose mothers had higher education. Similarly, children from underweight mother had 2.99 (OR: 2.99, CI: 1.62-5.50, p\u0026lt;0.001) times risk of wasting than children from normal weight mother.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeterminants of underweight\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe odds of being underweight in age 12-23 months, 24-35 months were 1.46 (OR: 1.46, CI: 1.13-1.89, p\u0026lt;0.01) and 2.46 (OR: 2.46, CI: 1.90-3.18, p\u0026lt;0.01) times as compared to age \u0026lt;12 months children. For the underweight case, the odds were 0.63 (OR: 0.63, CI: 0.41-0.95, p\u0026lt;0.05), 0.56 (OR: 0.56, CI: 0.38-0.86, p\u0026lt;0.01), 0.56 (OR: 0.56, CI: 0.37-0.88, p\u0026lt;0.05) and 0.59 (OR: 0.59, CI: 0.39-0.90, p\u0026lt;0.05) times in children living in Barisal, Dhaka, Rajshahi and Rangpur division respectively as compared to children from Sylhet division. Odds of being underweight for children whose mother were uneducated (OR: 2.52, CI: 1.37-4.62, p\u0026lt;0.01), primary (OR: 1.76, CI: 1.01-3.05, p\u0026lt;0.05) and secondary educated (OR: 1.74, CI: 1.02-2.98, p\u0026lt;0.05) were higher as compared to higher educated mother. The other important significant variables to underweight were mothers’ height and mothers’ BMI. Children whose mother had height less than 145 cm were 2.41 (OR: 2.41, CI: 1.88-3.09, p\u0026lt;0.001) times likely to be stunted as compared to their counterpart. Similarly, children from underweight mother had 87% (OR: 1.87, CI: 1.41-2.45, p\u0026lt;0.001) times odds of underweight than children from normal weight mother. Children with obese mother had 41% (OR: 0.59, CI: 0.38-0.99, p\u0026lt;0.05) lower risk of being underweight than normal weight mother. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeterminants of overweight\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe odds of overweight were 55% (OR: 1.55, CI: 1.06-2.25, p\u0026lt;0.05) higher for male children as compared to females. The odds of being overweight in age 12-23 months, 24-35 months, 36-47 months and 48-59 months were 0.57 (OR: 0.57, CI: 0.34-0.95, p\u0026lt;0.01), 0.39 (OR: 0.39, CI: 0.23-0.64, p\u0026lt;0.001), 0.38 (OR: 0.38, CI: 0.21-0.72, p\u0026lt;0.01) and 0.48 (OR: 0.48, CI: 0.28-0.84, p\u0026lt;0.05) times as compared to age \u0026lt;12 months children. Children living in Dhaka had 3.31 (OR: 3.31, CI: 1.04-10.55, p\u0026lt;0.05) times odds of being overweight as compared to Sylhet. For overweight cases, the odds were 0.57 (OR: 0.57, CI: 0.33-0.98, p\u0026lt;0.05) times in children from the middle-income family as compared to those from the rich family. Children whose mother had height less than 145 cm were 50% (OR: 0.50, CI: 0.26-0.97, p\u0026lt;0.05) less likely to be overweight as compared to their counterpart. Similarly, children from overweight and obese mother had 1.83 (OR: 1.83, CI: 1.25-2.70, p\u0026lt;0.001) and 2.74 (OR 2.74, CI: 1.50-5.03, p\u0026lt;0.001) times odds of being overweight than those children from normal-weight mother.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, the predictor variables current age of children, sex of child, division, mothers’ educational level, mothers’ height and BMI were found as significantly related to the under-nutrition status, whereas the predictor variables sex of child, current age of children, division, wealth index, mothers’ height and BMI were significantly associated with child over-nutrition status.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis finding suggested that sex of child was an important risk factor for wasting and overweight. Other studies\u0026nbsp;[10, 22]\u0026nbsp;on Bangladesh demographic and health survey also found that female children were less likely to be wasted and over-weight than male children. The\u0026nbsp;male children are more vulnerable to develop malnutrition because they require comparatively more calories for growth and development [23].\u0026nbsp;Although the overweight of under five years children is not that much concerning issue in Bangladesh as the percentage is only 2.4%, despite this fact, it was found that the male children have higher chance to be over-weight than female. \u0026nbsp;This probably due to the gender bias in the family where parents are more concerned about the male child than female which is very common in the Indian subcontinent\u0026nbsp;[3].\u003c/p\u003e\n\u003cp\u003eThis study found that childhood stunting and underweight significantly increased with child’s age. Children within the age group of 12–59 months were more likely to be stunted and underweight compared to the younger children (less than 12 months). A comparable finding was also reported by other studies for developing nations\u0026nbsp;[10, 14, 24]. The increase in child stunting and underweight with age can be prevented by giving the supplementary food along with breast feeding. \u0026nbsp;However, the hygiene of supplementary foods is another factor as the other study [25]\u0026nbsp;shows that when the immune protective impacts of breast milk diminish, children are exposed to contaminated supplementary foods and the spread of infectious disease which expands the supplement prerequisites.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe odds of being overweight were lower in age 1-4 years (12 months-59 months) as compared to 0 (\u0026lt;12 months) years children. The results show that high percentage of mothers provide formula milk to the children in their early stages which lead to overweight in their later infancy\u0026nbsp;[26].\u0026nbsp;In Bangladesh 98% women expressed a strong desire to breastfeed exclusively [27]. However, they are influenced by the advertisements about the feeding of the formula milk to children. The advertises claim brain development, nutrition, and other benefits to the babies, which make mothers think that if they feed these to their babies then their babies will be healthy. WHO and UNICEF [27]\u0026nbsp;states that nearly 60% of post-partum women had received a recommendation from a health professional to feed a formula product. Thus, awareness among the mothers and health professionals is needed about feeding formula milk. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe prevalence of stunting and underweight in Sylhet was higher than the other divisions. However, significantly lower wasting were found in Dhaka and Rangpur division and lower underweight were found in Barishal compared to Sylhet division. \u0026nbsp;This is due to the fact that educational status and economic solvency in the Sylhet division, in general, is lower compared to the capital, Dhaka\u0026nbsp;[28].\u0026nbsp;On the other hand, the prevalence of being overweight was higher in the Dhaka division compared to Sylhet division. Two reasons could be playing role behind this. A recent report shows that only 2 percent children of the capital have the access to playgrounds. Thus, the lack of sports or physical activities creates a huge setback in children's physical and mental growth and it seems to be one of the major reasons behind the current uptrend graph of obesity of the children who lives in Dhaka. Another reason is the growing fast-food restaurants in Dhaka city, which are the spots for recreational family gatherings [10].\u003c/p\u003e\n\u003cp\u003eIn developing countries, rural–urban inequality in child malnutrition remained unchanged over the last decades due to economic hardship, inadequate health facilities, and insufficient education\u0026nbsp;[24, 29]. However, the results of this study were consistent with the literatures in the case of higher overweight prevalence in urban areas [10, 30].\u0026nbsp;In the present setting of Bangladesh, fast food restaurants and super shops are gaining popularity in the urban areas, filling in as spots for a leisure family gathering [31].\u0026nbsp;Furthermore, with extended urban relocation towards already overcrowded cities, expanded housing and foundations have thinned the open spaces and consequently it reduces the spaces for physical activities [32, 33]\u0026nbsp;resulting in higher indoor recreational activities and increased sitting time [34].\u0026nbsp;Our study also found that children who lived in rural areas of Bangladesh were more vulnerable to become stunted and underweighted. These results are consistent with some previous studies conducted and identified that children settled in rural areas are at higher risk to be undernourished [29, 35].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe present study showed that children of mothers with no formal education were more prone to be acutely malnourished (wasted and underweight) as compared to children of higher educated mothers. This association is found, in this study, between maternal education and all form of malnutrition. Result from the present study consistent with several previous studies\u0026nbsp;[14, 36].\u0026nbsp;Educated mothers are well informed about the health needs and nutritional facts of their children and prefer to use better hygiene and sanitation facilities. Moreover, they make comparative choices from available health services for improved healthcare of their children [37].\u003c/p\u003e\n\u003cp\u003eThe wealth index was not significantly associated with undernourishment but the odds of being overweight were significantly higher with the richest family compared to poorest. This result is consistent with the other literatures [10, 38].\u0026nbsp;Wealthy women get higher intake of nutrients than poor women [39]\u0026nbsp;and wealthy families takes higher amount of processed food, which in turns rises the weights of children of those mothers in general [40, 41].\u003c/p\u003e\n\u003cp\u003eIn this study, children of short stature mothers (height = \u0026lt; 145 cm) were found more likely to be stunted and underweight. Our result was in line with another study\u0026nbsp;[14].\u0026nbsp; Our study also found that, children of short stature mothers (height = \u0026lt; 145 cm) were found less likely to be overweight than the taller mother. The reason may be the lower health stock of short height mothers [42].\u0026nbsp;Because of the lower health stock, the short height mothers have insufficient nutrients to the fetus which reduce the fetal growth of infants. \u0026nbsp;This could result the low birth weight and influencing babies’ health [43].\u0026nbsp;Previous evidence had also shown several adverse health related consequences, including the nutritional outcomes, in children of mothers of low height (or short stature) \u0026nbsp; [44, 45].\u003c/p\u003e\n\u003cp\u003eBody mass index (BMI) is one of the key factors to access the Mother’s nutritional status and it is associated with child’s nutritional status\u0026nbsp;[46].\u0026nbsp;The risk of being malnourished for a child (stunting, wasting and underweight) was higher, whose mother’s BMI was below normal (\u0026lt;18.5 kg/m2). It can be also noted that the higher risk of having overweight child belongs to\u0026nbsp;overweight mothers and it’s chance is almost double if the mother is in obesity category. These findings are parallel to the previous studies [44, 46, 47],\u0026nbsp;which shows that there is an adverse effect of mothers’ BMI on children malnutrition status. Since the mother’s BMI is one of the key factors of having malnourished\u0026nbsp;and over nutation child, a great management of BMI should be taken by clinical management and counseling the pregnant mothers to reduce the risk of overweight child. On the other hand, mother’s nutritional status should be considered when making policies for reducing the child malnutrition.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStrengths and Limitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe strength of our study is that the current Bangladesh Demographic and Health Survey data, i.e., BDHS 2017-2018 data was used. \u0026nbsp;In BDHS data, the overall probability of selection of each household is not a constant. Thus, all analysis was done using appropriate sampling weights in order to reduce the biasness of our findings. Thus, the results of this research can be used nationally. \u0026nbsp;Moreover, the survey had a very small percentage of missing responses (4.08%) which leads to large sample sizes.\u003c/p\u003e\n\u003cp\u003eThis study also comes with limitations. \u0026nbsp;Because of the cross-sectional design of the study, it is very difficult to say the exact causal relationships of the variables with malnutrition. The socioeconomic status of the households may be changed at present as the data are collected few years back.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion \u0026 Recommendations","content":"\u003cp\u003eIn this article, our objective was to determine the socio-demographic factors which are significantly related to malnutrition of less than five-years aged children in Bangladesh. This study reveals that mothers’ education level and BMI are two common influencing factors for malnutrition of child. No or less educated mothers and mothers with low BMI are tend to have child with malnutrition. Furthermore, the age of child also impacts child’s nutrition. Higher aged children are more likely to be stunted or underweight, and conversely less likely to be overweight overall. This study also reveals that the male children are more likely to be overweight as well as wasted than female children. Children from the greater income households tend to have overweight than the lower income households. Most of the overweight children belong to the Dhaka division; however, children from Sylhet division are mostly suffering from malnutrition. This study also shows that overweight and taller mothers tend to have overweight children. Moreover, shorter heighted mothers tend to have child with malnutrition.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFood habit of children of Dhaka and Sylhet needed to be studied to identify clearly why children from Dhaka tend to be overweight and those from Sylhet tend to be malnourished. Women’s education is again needed to be strongly taken care of, as educated mothers can take educated decisions regarding her and her child’s wellbeing. Mothers’ weight should be kept at check at a normal BMI, to avoid both malnutrition as well as overweight problem in their offspring. Proper food intake and nutritional balance should be maintained even if a child gets older, because this study found that at higher ages children tend to be more malnourished.\u003c/p\u003e\n\u003cp\u003eThough Bangladesh had declining child malnutrition over the past years, however, the results shows that the percentage of stunting (31%) and underweight (22%) are still distressing. \u0026nbsp;Thus, to achieve the Sustainable Development Goal (SDG) of 2030- improving nutrition (goal-2), we need to focus on to the key factors behind malnutrition to effectively control their prevalence. Government’s clear directives along with private initiatives in these aspects can bring about a healthy young generation.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eBDHS:\u003c/strong\u003e Bangladesh Demographic and Health Survey\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBMI:\u003c/strong\u003e Body mass index\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCI:\u003c/strong\u003e Confidence Interval\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNIPORT:\u003c/strong\u003e National Institute of Population Research and Training\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOR:\u003c/strong\u003e Odds ratio\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSDG:\u003c/strong\u003e Sustainable Development Goal\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWHO:\u003c/strong\u003e World Health Organization\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledge the National Institute of Population Research and Training (NIPORT), and ICF for providing the BDHS 2017-2018 dataset.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere is no funding source for this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data is available in the Demographic and Health Survey website (https://dhsprogram.com/data/dataset/Bangladesh_Standard-DHS_2017.cfm?flag=0).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSohel Rana- Conceptualization, Formal Analysis, Validation, Writing-original draft, Writing-review \u0026amp; editing. F. M. Arifur Rahman- Data curation, Formal Analysis, Validation, Visualization, Writing-original draft, Writing-review \u0026amp; editing. Abu Sayed Md. Al Mamun- Conceptualization, Formal Analysis, Writing-original draft. Md. Mobarak Hossain Khan- Writing-review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding author\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to Sohel Rana.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNational Institute of Population Research and Training (NIPORT), and ICF is responsible for ethics approval and consent to participate. Because, the BDHS 2017-2018 datasetwas collected under the National Institute for Population Research and Training (NIPORT) of the Ministry of Health and Family Welfare, Bangladesh and ICF.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eZerga AA, Tadesse SE, Ayele FY \u003cem\u003eet al\u003c/em\u003e. Impact of malnutrition on the academic performance of school children in Ethiopia: A systematic review and meta-analysis. SAGE Open Med 10:20503121221122398.2022; DOI: 10.1177/20503121221122398.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eCaulfield LE, de Onis M. Bl\u0026ouml;ssner M \u003cem\u003eet al\u003c/em\u003e. Undernutrition as an underlying cause of child deaths associated with diarrhea, pneumonia, malaria, and measles. Am J Clin Nutr. 2004; 80 (1), 193-198. \u0026nbsp; DOI: 10.1093/ajcn/80.1.193.\u003c/li\u003e\n \u003cli\u003eDe P, Chattopadhyay N. Effects of malnutrition on child development: Evidence from a backward district of India. Clin Epidemiol Glob Health. 2019; \u0026nbsp;7 (3), 439-445. DOI: 10.1016/j.cegh.2019.01.014.\u003c/li\u003e\n \u003cli\u003eVonaesch P, Tondeur L, Breurec S \u003cem\u003eet al\u003c/em\u003e. Factors associated with stunting in healthy children aged 5 years and less living in Bangui (RCA). PLoS One. 2017; 12(8):e0182363. DOI: 10.1371/journal.pone.0182363.\u003c/li\u003e\n \u003cli\u003eBrennhofer S, Reifsnider E, Bruening M. Malnutrition coupled with diarrheal and respiratory infections among children in Asia: A systematic review. Public Health Nurs. 2017; \u0026nbsp;34(4), 401-409. DOI: 10.1111/phn.12273.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eDe Sanctis V, Soliman A, Alaaraj N \u003cem\u003eet al\u003c/em\u003e. Early and Long-term Consequences of Nutritional Stunting: From Childhood to Adulthood. Acta bio-medica : Atenei Parmensis. 2021; 92(1), e2021168. DOI: 10.23750/abm.v92i1.11346.\u003c/li\u003e\n \u003cli\u003eUnited Nations Children\u0026rsquo;s Fund (UNICEF), World Health Organization, International Bank for Reconstruction and Development/The World Bank. Levels and trends in child malnutrition: key findings of the 2021 edition of the joint child malnutrition estimates. New York: United Nations Children\u0026rsquo;s Fund. 2021; License: CC BY-NC-SA 3.0 IGO. ISBN (WHO) 978-92-4-002525-7 (electronic version).\u003c/li\u003e\n \u003cli\u003eNational Institute of Population Research and Training (NIPORT), and ICF. Bangladesh Demographic and Health Survey 2017-18: Key Indicators. Dhaka, Bangladesh, and Rockville, Maryland, USA: NIPORT, and ICF. 2019.\u003c/li\u003e\n \u003cli\u003eHabimana S, Biracyaza E. Risk Factors of Stunting Among Children Under 5 Years Of Age In The Eastern And Western Provinces Of Rwanda: Analysis Of Rwanda Demographic And Health Survey 2014/2015. Pediatric Health Med Ther. 2019; 10, 115-130. DOI: 10.2147/PHMT.S222198.\u003c/li\u003e\n \u003cli\u003eHossain S, Chowdhury PB, Biswas RK \u003cem\u003eet al\u003c/em\u003e. \u0026nbsp; Malnutrition status of children under 5 years in Bangladesh: A sociodemographic assessment. Child Youth Serv Rev. 2020; 117:105291 DOI: 10.1016/j.childyouth.2020.105291.\u003c/li\u003e\n \u003cli\u003eLi Z, Kim R, Vollmer S \u003cem\u003eet al\u003c/em\u003e. Factors Associated with Child Stunting, Wasting, and Underweight in 35 Low- and Middle-Income Countries. JAMA Netw Open. 2020; 3(4):e203386. DOI: 10.1001/jamanetworkopen.2020.3386.\u003c/li\u003e\n \u003cli\u003eChowdhury TR., Chakrabarty S, Rakib M \u003cem\u003eet al\u003c/em\u003e. Risk factors for child stunting in Bangladesh: an analysis using MICS 2019 data. Arch Pub Health. 2022; 80:126. DOI: 10.1186/s13690-022-00870-x.\u003c/li\u003e\n \u003cli\u003eHarding KL, Aguayo VM, and Webb P. Factors associated with wasting among children under five years old in South Asia: Implications for action. PLoS ONE. 2018; 13 (7): e0198749. DOI: 10.1371/journal.pone.0198749.\u003c/li\u003e\n \u003cli\u003eKhan S, Zaheer S, Safdar NF. Determinants of stunting, underweight and wasting among children \u0026lt; 5 years of age: evidence from 2012-2013 Pakistan demographic and health survey. BMC Public Health. 2019; 19 (1):358. DOI: 10.1186/s12889-019-6688-2.\u003c/li\u003e\n \u003cli\u003eWali N, Agho KE, Renzaho AMN Wasting and Associated Factors among Children under 5 Years in Five South Asian Countries (2014\u0026ndash;2018): Analysis of Demographic Health Surveys. Int J Environ Res Public Health. 2021; 18:4578. DOI: 10.3390/ijerph18094578.\u003c/li\u003e\n \u003cli\u003eTosheno D, Adinew YM, Thangavel T \u003cem\u003eet al\u003c/em\u003e. Risk Factors of Underweight in Children Aged 6\u0026ndash;59 Months in Ethiopia. J Nutr Metab. 2017; 2017:6368746. DOI: 10.1155/2017/6368746.\u003c/li\u003e\n \u003cli\u003eMoshi CC, Sebastian PJ, Mushumbusi DG \u003cem\u003eet al\u003c/em\u003e. \u0026nbsp;Determinants of underweight among children aged 0\u0026ndash;23 months in Tanzania. Food Sci. Nutr. 2021; 10, 1167-1174. DOI: 10.1002/fsn3.2748.\u003c/li\u003e\n \u003cli\u003eBrophy S, Cooksey R, Gravenor, MB \u003cem\u003eet al\u003c/em\u003e. \u0026nbsp; Risk factors for childhood obesity at age 5: Analysis of the Millennium Cohort Study. BMC Public Health. 2009; 9:467. DOI:10.1186/1471-2458-9-467.\u003c/li\u003e\n \u003cli\u003eDev DA, McBride BA, Fiese BH \u003cem\u003eet al\u003c/em\u003e. Risk factors for overweight/obesity in preschool children: an ecological approach. Child Obes. 2013; 9(5), 399\u0026ndash;408. DOI: 10.1089/CHI.2012.0150.\u003c/li\u003e\n \u003cli\u003eSaha J, Chouhan P, Ahmed F \u003cem\u003eet al\u003c/em\u003e. Overweight/Obesity Prevalence among Under-Five Children and Risk Factors in India: A Cross-Sectional Study Using the National Family Health Survey (2015\u0026ndash;2016). Nutrients. 2022; \u0026nbsp;14:3621. DOI: 10.3390/nu14173621.\u003c/li\u003e\n \u003cli\u003eGortmaker SL, Hosmer DW, Lemeshow S. Applied logistic regression. Contemp Sociol. 1994; 23(1), 159. DOI:10.2307/2074954.\u003c/li\u003e\n \u003cli\u003eFakir AMS, Khan MWR. Determinants of malnutrition among urban slum children in Bangladesh. Health Econ Rev. 2015; 5, 22. DOI: 10.1186/S13561-015-0059-1.\u003c/li\u003e\n \u003cli\u003eKavosi E, Hassanzadeh Rostami Z, Kavosi Z \u003cem\u003eet al\u003c/em\u003e. Prevalence and Determinants of Under-Nutrition Among Children Under Six: A Cross-Sectional Survey in Fars Province, Iran. Int J Health Policy Manag. 2014; 3(2), 71-76. DOI: 10.15171/ijhpm.2014.63.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eDas S, Gulshan J. Different forms of malnutrition among under five children in Bangladesh: A cross sectional study on prevalence and determinants. BMC Nutrition. 2017; \u0026nbsp;3(1). DOI: 10.1186/s40795-016-0122-2.\u003c/li\u003e\n \u003cli\u003eShrimpton R, Victora CG, de Onis \u003cem\u003eet al\u003c/em\u003e. Worldwide timing of growth faltering: implications for nutritional interventions. Pediatrics. 2001; 107(5), E75. DOI: 10.1542/peds.107.5.e75.\u003c/li\u003e\n \u003cli\u003eTaveras EM, Rifas-Shiman SL, Belfort MB \u003cem\u003eet al\u003c/em\u003e. Weight status in the first 6 months of life and obesity at 3 years of age. Pediatrics. 2009; 123(4), 1177\u0026ndash;1183. DOI: 10.1542/peds.2008-1149.\u003c/li\u003e\n \u003cli\u003eWHO, UNICEF. Progress on breastfeeding in Bangladesh undermined by aggressive, Press release, 23 February, \u0026nbsp;2022.\u003c/li\u003e\n \u003cli\u003eTareque MI, Begum S, Saito Y. Inequality in disability in Bangladesh. PLoS ONE. 2014; \u0026nbsp;DOI: 10.1371/journal.pone.0103681.\u003c/li\u003e\n \u003cli\u003eSrinivasan CS, Zanello G, Shankar B. \u0026nbsp;Rural-urban disparities in child nutrition in Bangladesh and Nepal. BMC Public Health. 2013; 13(1):581. DOI: 10.1186/1471- 2458-13-581\u003c/li\u003e\n \u003cli\u003ePirgon \u0026Ouml;, Aslan N. The role of urbanization in childhood obesity. JCRPE J. Clin. Res. Pediatr. 2015; DOI: 10.4274/jcrpe. 1984.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eIslam N, Ullah GMS. Factors Affecting Consumers Preferences On Fast Food Items In Bangladesh. J Appl Bus Res. 2010; 26(4). DOI: 10.19030/jabr.v26i4.313.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eMelby CL, Orozco F, Ochoa D \u003cem\u003eet al\u003c/em\u003e. Nutrition and physical activity transitions in the Ecuadorian Andes: Differences among urban and rural-dwelling women. American journal of human biology : Hum Biol. 2017; 29(4), DOI: 10.1002/ajhb.22986.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eReardon, Hernandez, Ricardo \u003cem\u003eet al\u003c/em\u003e. Urbanization, diet change, and the transformation of the downstream and midstream of the agrifood system: Effects on the poor in Africa and Asia. Econ J. 2015; 66: 43 - 63.\u003c/li\u003e\n \u003cli\u003eGoryakin Y, Suhrcke M. Economic development, urbanization, technological change and overweight: What do we learn from 244 Demographic and Health Surveys? Econ Hum Biol. 2014; 14, 109-127. DOI: 10.1016/j.ehb.2013.11.003.\u003c/li\u003e\n \u003cli\u003eVan de Poel E, O\u0026apos;Donnell O, Van Doorslaer E. Are urban children really healthier? Evidence from 47 developing countries. Soc sc. Med. 2007; 65(10), 1986\u0026ndash;2003. DOI: 10.1016/j.socscimed.2007.06.032\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eMishra K, Kumar P, Basu S \u003cem\u003eet al\u003c/em\u003e. Risk factors for severe acute malnutrition in children below 5 y of age in India: a case-control study. Indian J Pediatr. 2014; 81(8):762\u0026ndash;5. DOI:10.1007/s12098-013-1127-3\u003c/li\u003e\n \u003cli\u003eTariq J, Sajjad A, Zakar R \u003cem\u003eet al\u003c/em\u003e. Factors Associated with Undernutrition in Children under the Age of Two Years: Secondary Data Analysis Based on the Pakistan Demographic and Health Survey 2012-2013. Nutrients. 2018; 10(6), 676. DOI: 10.3390/nu10060676\u003c/li\u003e\n \u003cli\u003eNavalpotro L, Regidor E, Ortega P \u003cem\u003eet al\u003c/em\u003e. Area-based socioeconomic environment, obesity risk behaviours, area facilities and childhood overweight and obesity: socioeconomic environment and childhood overweight. Prev. Med. 2012; 55(2), 102\u0026ndash;107. DOI: 10.1016/j.ypmed.2012.05.012.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eDas S, Fahim S, Islam M \u003cem\u003eet al\u003c/em\u003e. Prevalence and sociodemographic determinants of household-level double burden of malnutrition in Bangladesh. Public Health Nutr. 2019; 22(8), 1425-1432. DOI:10.1017/S1368980018003580.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eMorgan K, Sonnino R. The urban foodscape: World cities and the new food equation. Cambridge J. Reg. Econ. Soc. 2010. DOI: 10. 1093/cjres/rsq007\u003c/li\u003e\n \u003cli\u003eRahman S. Obesity in junk food generation in Asia: A health time bomb that needs early defusing! South East Asia J Public Health. 2013; 3(1):1-2. DOI: 10.3329/seajph.v3i1.17703.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eJananthan R, Wijesinghe D, Sivananthewerl T. Maternal Anthropometry as a Predictor of Birth Weight. J Trop Agric. 2009; 21(1), 89-98. DOI: 10.4038/tar.v21i1.2590.\u003c/li\u003e\n \u003cli\u003eHart, N. Famine, Maternal Nutrition and Infant Mortality: A Re-Examination of the Dutch Hunger Winter. Popul Stud. 1993; 47(1), 27\u0026ndash;46. http://www.jstor.org/stable/2175224.\u003c/li\u003e\n \u003cli\u003eSubramanian SV, Ackerson LK, Smith GD \u003cem\u003eet al\u003c/em\u003e. Association of maternal height with child mortality, anthropometric failure, and anemia in India. JAMA. 2009; \u0026nbsp;301(16):1691\u0026ndash;1701. DOI:10.1001/jama.2009.548.\u003c/li\u003e\n \u003cli\u003eAddo OY, Stein AD, Fall CH \u003cem\u003eet al\u003c/em\u003e. Maternal height and child growth patterns. J Pediatr. 2013; 163(2), 549\u0026ndash;54. DOI: 10.1016/j.jpeds.2013.02.002.\u003c/li\u003e\n \u003cli\u003eAkombi BJ, Agho KE, Merom D \u003cem\u003eet al\u003c/em\u003e. Multilevel analysis of factors associated with wasting and underweight among children under five years in Nigeria. Nutrients. 2017; \u0026nbsp; 9(1): 44. DOI: 10.3390/nu9010044.\u003c/li\u003e\n \u003cli\u003eHasan MT, Soares Magalh\u0026atilde;es, Williams GM \u003cem\u003eet al\u003c/em\u003e. Long-term changes in childhood malnutrition are associated with long-term changes in maternal BMI: evidence from Bangladesh, 1996-2011. The American journal of Clin Nutr. 2016; \u0026nbsp;104(4), 1121\u0026ndash;1127. DOI: 10.3945/ajcn.115.111773\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 2 are available in the Supplementary Files section\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Bangladesh, Malnutrition, DHS, Determinants, Public Health.","lastPublishedDoi":"10.21203/rs.3.rs-4274697/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4274697/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground \u003c/strong\u003eMalnutrition is a major risk factor to create permanent, widespread damage to child's growth, development and well-being. This study aimed to determine the risk factors of malnutrition status of below five-years aged children in Bangladesh.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods \u003c/strong\u003eAnalysis was conducted using data from Bangladesh Demographic \u0026amp; Health Survey (BDHS, 2017-18). A total number of 8402 under five-year old children’s data from BDHS 2017-18 were included in this study. \u0026nbsp;Descriptive statistics, chi-square test and binary logistic regression models were implemented to examine the prevalence of malnutrition status and its association with the different selected socio-demographic factors in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults \u003c/strong\u003eThe study found that the prevalence of stunting, wasting, underweight, and overweight of under-5 children were 31.0%, 8.8%, 22.0% and 2.4% respectively. Current age of children, division, mothers’ educational level, mothers’ height and BMI were found to be significant predictors for stunting and underweight children. Whereas, sex of child, mothers’ educational level and mothers’ BMI significantly impacted wasting. Furthermore, children’s overweight status was significantly associated with sex of child, current age of children, division, wealth index, mothers’ height and BMI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions \u003c/strong\u003eSeveral geographical and socio-demographic factors significantly impacted on malnutrition status of Bangladeshi under-five children. Therefore, government of Bangladesh and other health authorities should focus on the findings of this study to develop and implement concrete policies in the aim to reduce complications arising from under-five child malnutrition in Bangladesh.\u003c/p\u003e","manuscriptTitle":"Malnutrition status of children aged under-5 years in Bangladesh: evidence from BDHS 2017-2018","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-29 13:26:26","doi":"10.21203/rs.3.rs-4274697/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dbde63ab-df7f-4cd6-b35c-c256cc109128","owner":[],"postedDate":"April 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-06T10:32:19+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-29 13:26:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4274697","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4274697","identity":"rs-4274697","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}