Current prevalence and determinants of anaemia in under-five children in rural Bangladesh: a cross sectional study

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Moniruzzaman Mollah, Ashik Mosaddi, Asgor Hossain, Andrew A. Roy, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-609632/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 Anaemia and its association with low physical and cognitive development in under-five children remain as a common public health burden in developing countries including Bangladesh. Childhood anemia is significantly associated with age, rural residence, infant and young child feeding (IYCF) practices, infectious disease, maternal illiteracy etc. We have studied to identify current prevalence, and to explore associated socio-demographic, health, and nutritional factors of anaemia in under-five children of rural Bangladesh. Methods and materials A cross-sectional study was conducted at five remote northern districts of Bangladesh involving rural children aged 6 - <60 months. We used an interviewer-administered questionnaire for data collection. Potential study subjects were approached conveniently at selected rural health centres. Chi-squared test was the main statistical model to identify association between explanatory variables and anaemia. A p-value <0.05 was considered as significant. Results Overall prevalence of anaemia (N = 258) was 61.23% with mild, moderate and severe anaemia of 28.29%, 28.68% and 4.26% respectively. The prevalence of anaemia was the highest (72%) in age group 6-24 months, which were followed by 63% in >24-36 months and 44.3% in >36-<60 months categories. The following explanatory variables showed statistically significant association with high anaemia: younger-age (p = <0.001), low family income, and maternal education (p = <0.001), exclusive versus non-exclusive breast feeding (p = 0.02), and timely versus delayed or early weaning (p = <0.001). Non consumption of animal proteins, fruits and green leafy vegetables were also significantly linked to high anaemia prevalence (p = 0.001). Further, underweight, stunting, and wasting were significantly related to anaemia (p = 0.02, 0.006, and 0.001 respectively). Conclusion Prevalence of anaemia in under-five children of rural Bangladesh remains noticeably high. Age, maternal education, family income, consumption of animal protein, green leafy vegetables, and fruits along with underweight, stunting and wasting are inversely related to anaemia prevalence. Exclusive breast feeding and timely weaning may reduce risk of anaemia. Health Economics & Outcomes Research anaemia prevalence childhood anaemia determinants iron deficiency under-five children rural Bangladesh Figures Figure 1 Background Anaemia is one of the major public health burdens in the world particularly for young and preschool children. Globally, nearly 50% of under-five children are suffering from anaemia. 1 . Anaemia is linked to a wide range of childhood disorders such as cognitive development, low scholastic performance, insufficient physical growth and behavioral development and low immunity among others. Because of these adverse health and socio-economic consequences, anaemia prevalence of more than 40% in any population is identified as a serious public health problem. 2 Anemia is the second leading nutritional cause of diverse disorders with adverse effects on socioeconomic development. 3 Anemia is significantly associated with fetal low birth weight (LBW). sex, age, rural residence, infant and young child feeding (IYCF) practices, infectious disease (e.g., malaria, tuberculosis, intestinal parasitic infestation), under-nutrition (e.g., stunting, wasting, and underweight), poor socioeconomic status, household food insecurity, duration of lactation, poor dietary iron intake, maternal illiteracy and maternal anemia are reported as predictors of anaemia. (4, 5, 6, 7) According to recent information from the South-Asian region, nearly 79% Indian children aged 6–35 months suffer from anaemia with a rural predominance. 8, 9 Anaemia still remains as one of the major cause of mortality and morbidity in many developing countries including Bangladesh.. 1 In Bangladesh, several studies have reported that anemia among the under-five children is a considerable public health problem. Bangladesh Demographic Health Survey (BDHS) 2011 reported 51% anaemia prevalence in the total population. 10 An anemia prevalence of 33.1% was reported by National Micronutrient Status Survey in pre-school children with rural and urban prevalence of 37.0% and 22.8% respectively.. Several studies found that the prevalence of anemia was higher in children aged < 3 years among under-five children. 11 Timely starting of complementary feeding at age 6 months is an utmost importance for infant growth and nutrition. In Bangladesh, nearly 62% of children start delayed complementary feeding. 10 The suboptimal infant and young child feeding (IYCF) practices along with early or delayed weaning was found associated with high level nutritional anaemia. 10 Iron deficiency is the most common cause of nutritional anemia in young children. 11, 12 Folic acid and vitamin B12 deficiency are also not uncommon causes of nutritional anaemia. 11, Prevalence of iron deficiency anemia varies across countries with four-times higher in developing than in developed countries. 5 . Empirically, iron deficiency anemia increases risk of morbidity and mortality from infectious disease. 4,9,13 To eliminate childhood nutritional anemia, particularly iron deficiency anaemia is a public-health priority and reportedly the most common cause of anaemia among under-five children with high prevalence among rural dwellers who occupy nearly 68% of the total population of Bangladesh. 14 However, there are very few studies and consistent data on the current prevalence of anaemia and its determinants in under-five children in rural Bangladesh to fight anaemia. Hence, we aim for such a study. Materials And Methods Objective: This study is aimed (i) to identify the current prevalence of anemia among under-five children in rural Bangladesh, and (ii) to assess if there are any associations of anemia with socio-demographic, health, food and nutritional factors in this target population. Study design, settings, and population A cross-sectional study was conducted in the rural areas of northern Bangladesh. Eleven Upazillas (sub-district) of five districts were selected purposively as the study settings ( Table 1 ). The study districts and Upazilla represent typical and nearly homogenous socioeconomic, demographic and cultural contexts of rural Bangladesh. Nearly 85% population of the sample districts were rural residents. 10 Table 1 Sample districts with corresponding sample upazillas District Corresponding upazilla* Joypurhat Panchbibi, Jopurhat Sador, Ketlal, Kalai, Akkelpur Dinajpur Hakimpur, Ghoraghat Naugaon Dhamuirhat, Bodolgachi Gaibandha Gobindogong Bogura Sibgong Note: several upazillas form a district. Under-five children aged 6 - <60 months were the target population. A sample size of 325 was calculated using Cockranch's formula ( where N = Sample size, z = 1.96 (95% confidence level), p = 33% estimated prevalence of anemia in under-five population basing on available information, and e = 0.05 at 5% margin of error). Rural children of aged 6 - <60 months whose guardians provided written consent were included in the study. Children who were living in urban, i.e., municipality area, in need of emergency care and hospitalization, and/or having history of blood transfusion within last three months from the date of data collection were not included. Data collection tools and techniques A questionnaire was prepared involving three researchers; any contradictions were solved by discussion. A piloting was conducted by the Principal Investigator (PI) involving parents of ten patients for testing mainly the qualitative variables and to develop skills of the PI. The questionnaire was finalized with minimum changes and contained the following four main section : particulars of the child ren, quantitative domains : nutritional anthropometry (height/length, weight) and laboratory reports (complete hemogram, ferritin level, Hb electrophoresis, Zinc level, Folate and vitamin B 12 assay); qualitative domains : socio- demographic variables (maternal education, income and occupation of household head, number of children, consanguinity), nutrition (breast feeding, IYCF, stunting, wasting, underweight, consumption of protein, fruits, vegetable) and health (maturity at birth and birth size, and history of recent infection. Data was collected consecutively from purposively selected 22 rural health facilities and EPI outreach centers in the study Upazilas. At first the PI (a child health specialist experienced in primary research), approached the under-five children presented at the out-patient department of the selected health facilities. The objectives of the study and the reason of collecting blood were explained. Parents/guardians were assured free of cost blood tests which would solely be used for the study. They were also assured access to the study findings with a guideline for the next treatment options, but without financial benefits. Following an initial face-to-face interview for collecting qualitative data, parents with eligible child were sent to the assigned laboratory. Five millilitre (ml) venous blood was drawn using a sterile syringe (3ml blood were preserved into ethylene ediamine tetraacetic acid (EDTA) vial and the next 2ml into another test-tube for separating serum). The EDTA blood was analyzed on the same day with an ‘Automated Hematology Analyzer’ (Nihon Kohden,Tokyo, Japan) for a Complete Blood Count (CBC; i.e., haemoglobin percentage, hematocrit), Red cell indices (i.e., MCV, MCH, MCHC, RWD), total count of white blood cell (WBC), differential count of WBC and total platelet count. The degree of anaemia was classified into three categories on the basis of hemoglobin level as defined by the World Health Organization. 3 Accordingly, mild anaemia was considered with a Hb% of 10.00–10.90 gm/dl, which for moderate and severe anaemia were 7.00–9.90 gm/dl and < 7.00gm/dl respectively. Basing on mean corpuscular volume (MCV), anemia were further classified as normocytic (MCV 80–96 fl), microcytic (MCV 96 fl). Serum Ferritin and/or Hb-electrophoresis were done in children with microcytic hypochromic anemia; whereas macrocytic anemias were evaluated assaying Vitamin B 12 and folic acid levels; and normocytic normochromic anaemia were investigated with Serum Zinc level to reach the etiological pattern of anemia (Fig. 1 ). Ethical clearance Ethical clearance was obtained from the Institutional Animal, Medical Ethics, Bio-safety and Bio-security Committee (IAMEBBC) of the Institute of Biological Sciences, Rajshahi University (memo no: 83/320/IAMEBBC/IBSC, date: 27 August 2017). Informed written consents were taken from parents of the sample children. Statistical analysis Data were computed and analyzed using SPSS (version 23.0). Univariate analysis and chai-squared tests were the main models to identify the prevalence of anaemia and to assess any association between the independent variables and anaemia. A p-value < 0.05 was considered as significant. Results Because of time and resource constraints, it was possible to collect data from a total of 258 target children from a total of eleven sample upazillas of five districts (Table 2 ). 60% of the total study subjects were male and the rest were female. Overall prevalence of anaemia was 61.23% (N = 258). Of the total male children (n = 154), nearly 65% were anaemic and that was 56% in female children (n = 104). Table 2 distribution of sample children across the sample districts District (No. of Upazilla) Sampled children (% of total enrolled) Joypurhat (5) 90 (34.88%) Dinajpur (2) 59 (22.86%) Gaibandha (1) 38 (14.73%) Naugaon (2) 41 (15.90%) Bogura (1) 30 (11.63%) The gender difference in prevalence of anaemia was not significant ( p = 0.088). The majority (50%) children was in age group 6–24 months, which was followed by > 36–60 months (34%) and > 24–36 months (16%). The prevalence of anaemia was 72%, the highest, in 6–24 months Table 3 Socio-demographic characteristics of the participant children in relation to anaemia Variables Subject distribution (%) (N = 258) Prevalence of anaemia n = 158 (100%) Chi-squire statistics Gender 100 (64.93) χ 2 = 791.22; p = 0.08 phi = − .092 Male 154 (59.7%) Female 104 (40.3%) 58 (55.77) Age (in month) χ 2 = 9.1; p = 0.001 phi = .257 6–24 129 (50%) 93 (72.09) > 24–36 41 (15.9%) 26 (63.41) > 36–59 88 (34.1%) 39 (44.31) Religion or ethnicity χ 2 = 792.4; p = 0.117 phi = .129 Islam 229 (88.8%) 145 (63.31) Hinduism 22 (8.5%) 9 (40.90) Indigenous 7 (2.7%) 4 (57.14) Education level of mother χ 2 =783.31; p = 0.001 phi = .228 Primary enrollment or below 151 (58.5%) 104 (68.87) Secondary enrollment 65 (25.2%) 38 (58.46) Above secondary or higher 42 (16.3%) 16 (38.09) Number of children (parity) χ 2 = 478; p = 0.35 phi = − .058 ≤ 2 235 (91.1%) 146 (62.12) > 2 23 (8.9%) 12 (52.17) Occupation of household head χ 2 = 8.6; p = 0.111 phi = .153 Service (public or private) 89 (34.5%) 54 (60.67) Agriculture 63 (24.4%) 41 (65.07) Small Business 91 (35.3%) 50 (54.94) Day Labour 15 (5.8%) 13 (86.66) Monthly (family) income in Taka χ 2 =811.62; p = 20,000 62 (24.0%) 24 (38.70) group, which was followed by 63% in age group > 24–36 months and 44.3% in > 36–60 months with a statistically significant association between age categories and anaemia ( p = < 0.001). Among the children, Muslims were from the majority 88.8% and the rest were from Hindu and indigenous population. The prevalence of anaemia was the highest (63.3%) in Muslims, which was followed by 57.1% in indigenous group and 40.9% in Hindus. The association between religion and anaemia was not significant ( p = 0.12) (Table 2 ). Parity (i.e., mothers with ≤ 2 children (91.1%) versus > 2 children (8.9%)) was found not significantly associated with anaemia ( p = 0.23). The distribution of small business and service were nearly equal of the children’s family heads’ occupation, 35.5% and 34.5% respectively and that the rest 24.4% and 5.8% were farming and day labour. Prevalence of anaemia in children belong to the day labour families was noticeably the highest (nearly 87%), which among the children in the other three family occupation groups were nearly equal ranging from 55% in small business family to 65% in farmer family. There was no significant association between anaemia and family occupations ( p = 0.11). Among four categories of monthly family income, distributions of children were nearly equal in the middle two family income groups (i.e., 33.8% and 31% in 5,001–10,000 Taka (the Bangladesh currency) and 10,001–20,000 Taka groups respectively). Notably, children of the lowest two family income groups had nearly equally the highest prevalence of anaemia; 78% and 72% in 5,001–10,000 Taka and ≤ 5,000 Taka groups respectively (Table 1 ). Anaemia was found significantly associated with monthly family income ( p = < 0.001) (Table 1 ). The majority, 58.5% of the total mothers’ education level was below primary level. Maternal education was found significantly associated with children’s anaemia ( p = 0.001) (Table 3 ). Table 4 Nutrition and food related factors associated with the prevalence of anaemia (n = 258) Variables Subject distribution (%) (N = 258) Prevalence of anaemia Chi-squire statistics Exclusive Breast feeding Yes No 186 (72.1%) 72 (27.9%) 106 (56.99%) 52 (72.22%) χ 2 = 5.074; p = 0.016 phi = .140 Timely weaning/IYCF practice Yes No 169 (65.5%) 89 (34.5%) 89 (52.66%) 69 (77.52%) χ 2 = 15.186; p = < 0.001 phi = .243 Animal protein intake regularly Yes No 210 (81.4%) 48 (18.6%) 113 (53.80%) 45 (93.75%) χ 2 = 26.257; p = < 0.001 phi = .319 Plant protein intake regularly Yes No 93 (36%) 165 (64%) 50 (53.76%) 108 (65.45%) χ 2 = 3.425; p = 0.064 phi = .115 Fruits intake regularly Yes No 141 (54.7%) 117 (45.3%) 70 (49.65%) 88 (75.21%) χ 2 = 17.61; p = < 0.001 phi = .261 Green leafy vegetable regularly Yes No 150 (58.1%) 108 (41.9%) 77 (51.33% 81 (75%) χ 2 = 14.81; p = < 0.001 phi = .240 Underweight Yes No 40 (15.5%) 218 (84.5%) 31 (77.5%) 127 (58.26%) χ 2 = 5.27; p = 0.022 phi = .143 Stunted Yes No 74 (28.7%) 184 (31.3%) 55 (74.32%) 103 (55.98%) χ 2 = 7.48; p = 0.007 phi = .170 Wasted Yes No 29 (11.2%) 229 (88.8%) 26 (89.66%) 132 (57.64%) χ 2 = 11.11; p = < 0.001 phi = .208 Exclusive breast feeding children had nearly 18% lower anaemia prevalence than non-exclusive breast feeding group and the difference was statistically significant ( p = 0.02). Delayed or early weaning-practiced children had nearly 25% higher prevalence of anaemia than their properly weaning counterpart with a statistically significant difference ( p = < 0.001). Non-consumption of animal protein group were found almost 2 times higher anaemia prevalence than animal protein consumption group, which was statistically significant ( p = 0.001). Plant protein (pulses) intake group had nearly 10% lower anaemia prevalence than non-consumption group, which was not significant ( p = 0.064). Children with regular fruits intake had significantly lower prevalence of anaemia by 26% than non-consumption group ( p = 0.001). Children with regular intake of green leafy vegetables also had nearly 26% lower anaemia prevalence than in non-consumption group with a statistically significant difference ( p = 0.001). Underweight children had 1.5 times higher prevalence of anaemia than their normal counterpart with a significant difference ( p = 0.022). Stunted children were found 20% higher and significant risk of developing anaemia than their counterpart ( p = 0.006). Acute under-nourished children had nearly twice higher vulnerability of developing anaemia than normal children with a significant difference ( p = 0.001) (Table 4 ). Parents’ consanguinity status showed no significant difference in childhood anaemia ( p = 0.373). Pre-term children had nearly 4.5 times and 9 times higher anaemia prevalence than term and post-term babies respectively although the differences were not significant ( p = 0.153). Birth size of babies (normal/small/large) had no significant influence on the prevalence of anaemia ( p = 0.69). Children suffering from chronic illness or recent illness had 23% higher anaemia prevalence than apparently healthy children, which was statistically significant ( p = 0.001) (Table 5 ). Table 5 Association of key health and social factors to anaemia (N = 258) Variables Distribution of subjects (%) (N = 258) Prevalence of anaemia (%) Chi-squire statistics Consanguinity of parents χ 2 = 1.058; p = .373 Phi = .064 Yes 39 (15.1%) 21 (53.84%) No 219 (84.9%) 137 (62.55%) Maturity level at birth χ 2 = 3.758; p = 0.153 Phi = .121 Full term 201 (77.91%) 12 (5.79%) Pre-term 45 (17.44%) 32 (71.11%) Post-term 12(04.65%) 5 (41.67%) Size of baby at birth χ 2 = 0.724; p = 0.69 Phi = .054 Normal 148 (57.4%) 5 (62.12%) Small 50 (19.4%) 32 (64.00%) Large 60 (23.2) 34 (56.66%) Chronic illness or recent illness χ 2 = 12.867; p = 0.001 Phi = .223 Yes 97 (37.6%) 73 (75.25%) No 161 (62.4%) 85 (52.79%) Among the anaemic children ( n = 158), mild (Hb% 10-<11 gm/dl) and moderate (Hb% 7-<10 gm/dl) degree of anaemia were nearly equally distributed 46.2% ( n = 73) and 47% ( n = 74) respectively, whereas severe anaemia (Hb% <7 gm/dl) was only 7%. Discussion The study was undertaken to assess the current prevalence of anemia and its association with socio-demographic, health and nutritional factors in under-five children in rural Bangladesh. The overall prevalence of anaemia (N = 258) was 61.23% with proportion of mild, moderate and severe anaemia of 28.29%, 28.68% and 4.26% respectively. High prevalence of anaemia was found in some other studies in India, Tanzania, Kenya, and South Africa where the prevalence of anaemia was observed between (69% − 79%) in under-five children 18–20,29 . The prevalence of severe anaemia (4.26%) was lower than in similar settings; for example, Muoneke et al, 15 reported a prevalence of severe anaemia of 9.7% in Nigerian under-five children. Nearly consistent trends of mild, moderate and severe anaemia and associated factors in under-five children of this study were found in a study of Simbauranga et al at Tanzania. 16 In their study, the mild, moderate and severe anaemia were found 16.5%, 33% and 27.7% respectively. In a study in India, the overall prevalence of anaemia in under-five children was found 69.5% with percentage of mild moderate and severe anaemia were 26.2%,, 40.4%, 2.9% respectively 30 , which is nearly consistent with our findings. Mild and moderate anaemia in the total sample accounted nearly equally, 30% each, may be due to nutritional deficiencies and socio-demography related factors in rural Bangladesh. We found no association between gender and anaemia. Age is a significant factor of anaemia in under-five children with the highest prevalence (73%) in < 24 months age group than their older counterparts. These findings is consistent with the study findings of Goswmai and Das and the authors mentioned that high demand for nutrients to support the rapid body growth of the children at this age against a low supply might be the key underlying factor. 17 We also found that increasing trends of anaemia up to 2 years and then decreasing after 2 years may be relating to the children’s ability to eat varieties of foods. This finding is consistent with the study of Gebreweld et al. 18 We found no significant link of ethnicity, religion or consanguinity to childhood anaemia which contradicts the findings of Goswmai and Das. 17 In this Indian study among under-five children, the authors found significant difference in religion and all types of anaemia prevalence (severe, moderate, and mild) were higher among children of Hindu families than other religions. We found that higher the mother’s level of education lower the anaemia prevalence in children. Children of mothers with higher/above HSC education level had nearly two times lower risk of developing anaemia than that in below HSC level mothers. This finding is agreed with the studies of Kuziga et al. 19 and Leite et al 20 . We found that neither occupation nor parity is significantly linked to childhood anaemia. However, family income is a significant factor with an inverse relationship between income and prevalence of childhood anaemia. The similar observations were also noted in some previous studies. 20, 21–22 This is may be due to the fact that higher income is linked to good maternal education and better nutritional protection to children. Both non-exclusive breast feeding and delayed/early weaning were found significant factors of developing anaemia in children. Oppositely, EBF, timely weaning, regular consumption of animal protein, green leafy vegetables and locally available fruits were found protective to childhood anaemia. These findings are consistent with the study of Kejo et al. 23 Stunted, underweight and wasted children were found more anaemic, which is consistent with the study of Kisiangani et al. 24 . Children with chronic illness and recent illness were nearly 1.5 time high risk of developing anaemia which is also comply with the findings of Kumari et al. 25 However, it is not known if those disorders are causing anaemia or vice versa although synergistic effects on each other are well-known. Limitations and strengths Because of time and resource limits, the sample size was smaller than expected. The study was confined in northern Bangladesh. However, in nearly a homogenous rural context of the country, this study finding is claimed as a reflection of the childhood anaemia scenario of rural Bangladesh. In regard to the associated factors of anaemia, only univariant analyses were done, but the variants did not put together in a regressive model to identify the potential predictors. Conclusion Prevalence of anaemia in under-five children of rural Bangladesh remains noticeably high. Age, maternal education, family income, consumption of animal protein, green leafy vegetables, and fruits along with underweight, stunting and wasting are inversely related to anaemia prevalence. Exclusive breast feeding and timely weaning may reduce risk of anaemia. In addition, chronic and recent illness increase susceptibility to anaemia development. Abbreviations BDHS Bangladesh Demographic Health Survey CBC Complete Blood Count LBW low birth weight EDTA Ethylene-Diamine-Tetraacetic-Acid EPI Expanded Programme on Immunization Hb Hemoglobin HKI Helen Keller International HIV Human Immunodeficiency Virus ICDDR,B International Centre for Diarrheal Disease Research, Bangladesh IDA Iron Deficiency Anaemia IPHN Institute of Public Health Nutrition IYCF Infant and Young Child Feeding MCH Mean corpuscular hemoglobin MCHC Mean corpuscular hemoglobin concentration MCV Mean corpuscular volume ORC Out Reach Centre PreSAC Pre-school aged children RBC Red Blood Cell RDW Red Cell distribution Width UNICEF United Nations International Children’s Emergency Fund WHO World Health Organization. UHC Upazila Health Complex SAC School aged children Declarations Ethics approval E thical clearance was obtained from the Institutional Animal, Medical Ethics, Bio - safety and Bio-security Committee (IAMEBBC) of the Institute of Biological Sciences, Rajshahi University ( memo no: 83/320/IAMEBBC/IBSC, date: 27 August 2017 ) . Informed written consent were taken from the attending guardian of enrolled children. Consent for publication : not applicable. Availability of data and materials Data of this study will be made available from the corresponding author on rational request. Competing interests All authors declare that they have no competing interests. Funding The research was funded by the Institute of Biological Sciences, Rajshahi University , Rajshahi, Bangladesh Authors’ contributions MdMM: research concept, questionnaire development, interview, data collection, nutritional anthropometry, data processing, analyzing, interpreting, and writing the manuscript. AM: research concept, developing questionnaire, reviewing and revising the final manuscript. AH: Checking clinical data, and methodology development, AAR: developing research concept, major contribution in statistical analysis, data interpretation, reviewing the manuscript, and revising the final version. SN: data processing, questionnaire development PH: research concept, developing questionnaire, data interpretation, reviewing and revising the final manuscript. All authors read and approved the final manuscript. Acknowledgements Authors of the paper acknowledge and offer thanks to the Institute of Biological Sciences, Rajshahi University for providing resourceful environment for conducting the research . Also the cooperation of the expert laboratory staff is highly appreciated. Authors’ information Md. Moniruzzaman Mollah, (MBBS, DCH) PhD Fellow (IBSc), Assistant Professor, Department of Paediatrics, Shaheed Ziaur Rahman Medical College, Bogura, Bangladesh; Prof. Dr. Ashik Mosaddi PhD, Professor and Chairman, Department of Pharmacy, University of Rajshahi, Rajshahi; Dr. Asgor Hossain, MBBS, FCPS . Associate Prof. (Rtd.), Department of Paediatrics, Rajshahi Medical College, Rajshahi, Bangladesh; Dr. Andrew A. Roy (PhD, MBBS, MSc, MPH) Faculty and Researcher, Department of Medicine and Biomedical Sciences, Maastricht University, the Netherlands; Dr. Sultana Naznin MBBS, DGO. Resident Surgeon, Department of Gynae and Obs, IBMCH, Rajshahi, Bangladesh; Prof. Dr. Parvez Hassan PhD, IBSc, Rajshahi University, Rajshahi, Bangladesh. References 1. Khan JR, Awan N, Misu F. Determinants of anemia among 6-59 months aged children in Bangladesh: Evidence from nationally representative data. BMC Pediatr . 2016;16(1):1-13. doi:10.1186/s12887-015-0536-z 2. World Health Organization. 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Distinguishing iron deficiency anaemia from thalassemia trait in clinical obstetric practice. J Pregnancy Reprod . 2018;2(1):1-6. doi:10.15761/jpr.1000125 8. USAID. Overview of the Nutrition Situation in Four Countries in South and Central Asia .; 2014. 9. Pasricha SR, Black J, Muthayya S, et al. Determinants of anemia among young children in rural India. Pediatrics . 2010;126(1). doi:10.1542/peds.2009-3108 10. National Institute of Population Research and Training. BANGLADESH BANGLADESH AND HEALTH SURVEY 2014 .; 2014. 11. International Centre for Diarrhoeal Disease Research Bangladesh. National Micronutrients Status Survey 2011-12: Final Report .; 2013. https://static1.squarespace.com/static/56424f6ce4b0552eb7fdc4e8/t/57490d3159827e39bd4d2314/1464405328062/Bangladesh_NMS_final_report_2011-12.pdf. 12. Gamit M, Talwelkar H. Survey of different types of anemia. Int J Med Sci Public Heal . 2017;6(3):1. doi:10.5455/ijmsph.2017.0851807092016 13. Oppenheimer SJ. Iron-deficiency anemia: reexamining the nature and magnitude of the public health problem. J Nutr . 2001;131:616-635. 14. Institute of Public Health Nutrition. Institute of Public Health Nutrition Directorate General of Health Services Ministry of Health and Family Welfare Government of the People’s Republic of Bangladesh .; 2015. http://iphn.dghs.gov.bd/wp-content/uploads/2016/01/NMDCS-.pdf. 15. Muoneke VU, ChidiIbekwe R. Prevalence and Aetiology of Severe Anaemia in Under-5 Children in Abakaliki South Eastern Nigeria. Pediatr Ther . 2011;01(03):3-7. doi:10.4172/2161-0665.1000107 16. Simbauranga RH, Kamugisha E, Hokororo A, Kidenya BR, Makani J. Prevalence and factors associated with severe anaemia amongst under-five children hospitalized at Bugando Medical Centre, Mwanza, Tanzania. BMC Hematol . 2015;15(1). doi:10.1186/s12878-015-0033-5 17. Goswmai S, Das KK. Socio-economic and demographic determinants of childhood anemia. J Pediatr (Rio J) . 2015;91(5):471-477. doi:10.1016/j.jped.2014.09.009 18. Gebreweld A, Ali N, Ali R, Fisha T. Prevalence of anemia and its associated factors among children under five years of age attending at Guguftu health center, South Wollo, Northeast Ethiopia. PLoS One . 2019;14(7):1-13. doi:10.1371/journal.pone.0218961 19. Kuziga F, Adoke Y, Wanyenze RK. Prevalence and factors associated with anaemia among children aged 6 to 59 months in Namutumba district, Uganda: A cross- sectional study. BMC Pediatr . 2017;17(1):1-9. doi:10.1186/s12887-017-0782-3 20. Leite MS, Cardoso AM, Coimbra CE, et al. Prevalence of anemia and associated factors among indigenous children in Brazil: Results from the First National Survey of Indigenous People’s Health and Nutrition. Nutr J . 2013;12(1):1-11. doi:10.1186/1475-2891-12-69 21. Parbey PA, Tarkang E, Manu E, et al. Risk Factors of Anaemia among Children under Five Years in the Hohoe Municipality, Ghana: A Case Control Study. Anemia . 2019;2019. doi:10.1155/2019/2139717 22. Magalhães RJS, Clements ACA. Mapping the risk of anaemia in preschool-age children: The contribution of malnutrition, malaria, and helminth infections in West Africa. PLoS Med . 2011;8(6). doi:10.1371/journal.pmed.1000438 23. Kejo D, Petrucka P, Martin H, Kimanya M, Mosha T. Prevalence and predictors of anemia among children under 5 years of age in Arusha District, Tanzania. Pediatr Heal Med Ther . 2018;Volume 9:9-15. doi:10.2147/phmt.s148515 24. Kisiangani I, Mbakaya C, Makokha A. Prevalence of Anaemia and Associated Factors Among Preschool Children ( 6-59 Months ) in Western Province , Kenya. Public Heal Prev Med . 2015;1(1):28-32. 25. Kumari S, Garg N, Kumar A, et al. Maternal and severe anaemia in delivering women is associated with risk of preterm and low birth weight: A cross sectional study from Jharkhand, India. One Heal . 2019;8(February):100098. doi:10.1016/j.onehlt.2019.100098 Additional Declarations No competing interests reported. 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-609632","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":33012522,"identity":"5097ebd9-c6c2-4761-8ca4-d464836a023a","order_by":0,"name":"Md. Moniruzzaman Mollah","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYDCCA2BSAs6XY2DgIVGLMbFaECCxgZAWvtsHWDd83GGRb3D++MNPN2rupG84fvbggw8MdnK6Ddi1SJ5LYLs584yE5YYDB5Klc449y91wJi/ZcAZDsrEZugOgwOAMA9tt3jYJA4ODDQekc9gO5244kGMmzcNwIHEbQS2HGZt/5/w7nG5w/g2xWo4xs0nnth1OMLhBwBZJoJabM4FaJM+wsVnn9h02nHnjjbHhDAPcfuEDarnxsa3OgO/88ce3c74dluc7n2P44EOFnRwuLQwM/B9Q+QpglQa4lGMD8g2kqB4Fo2AUjIKRAAA2b2E3o3V/ggAAAABJRU5ErkJggg==","orcid":"","institution":"Rajshahi University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Md.","middleName":"Moniruzzaman","lastName":"Mollah","suffix":""},{"id":33012523,"identity":"b74683ed-db61-4ff7-b471-a95b4581eb24","order_by":1,"name":"Ashik Mosaddi","email":"","orcid":"","institution":"University of Rajshahi","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ashik","middleName":"","lastName":"Mosaddi","suffix":""},{"id":33012524,"identity":"9c3e2297-9ff1-4932-ab76-e0f6fc3fd5cc","order_by":2,"name":"Asgor Hossain","email":"","orcid":"","institution":"Rajshahi Medical College","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Asgor","middleName":"","lastName":"Hossain","suffix":""},{"id":33012525,"identity":"e9a9657c-3944-4faa-b639-a6525895d259","order_by":3,"name":"Andrew A. Roy","email":"","orcid":"","institution":"Maastricht University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Andrew","middleName":"A.","lastName":"Roy","suffix":""},{"id":33012526,"identity":"016562b6-e5f8-4b91-9653-8ebaf863d5ca","order_by":4,"name":"Sultana Naznin","email":"","orcid":"","institution":"IBMCH","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sultana","middleName":"","lastName":"Naznin","suffix":""},{"id":33012527,"identity":"d7225321-7581-4682-b8b2-d1956bdbfd9a","order_by":5,"name":"Parvez Hassan","email":"","orcid":"","institution":"Rajshahi University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Parvez","middleName":"","lastName":"Hassan","suffix":""}],"badges":[],"createdAt":"2021-06-10 15:59:52","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-609632/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-609632/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":10388574,"identity":"69f32b60-527a-4aea-8cef-d1eac1c38048","added_by":"auto","created_at":"2021-06-15 14:28:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":10978,"visible":true,"origin":"","legend":"laboratory diagnostic algorithm of anaemia","description":"","filename":"groupimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-609632/v1/a4bdb41a73a6990eea376e94.png"},{"id":13698890,"identity":"01bef3e8-7a35-45bb-9fde-924dabdc25e4","added_by":"auto","created_at":"2021-09-17 13:16:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":363282,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-609632/v1/dcce4464-cbbd-4856-b0cf-2fc26753f19d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Current prevalence and determinants of anaemia in under-five children in rural Bangladesh: a cross sectional study","fulltext":[{"header":"Background","content":" \u003cp\u003eAnaemia is one of the major public health burdens in the world particularly for young and preschool children. Globally, nearly 50% of under-five children are suffering from anaemia.\u003csup\u003e1\u003c/sup\u003e. Anaemia is linked to a wide range of childhood disorders such as cognitive development, low scholastic performance, insufficient physical growth and behavioral development and low immunity among others. Because of these adverse health and socio-economic consequences, anaemia prevalence of more than 40% in any population is identified as a serious public health problem.\u003csup\u003e2\u003c/sup\u003e Anemia is the second leading nutritional cause of diverse disorders with adverse effects on socioeconomic development.\u003csup\u003e3\u003c/sup\u003e Anemia is significantly associated with fetal low birth weight (LBW). sex, age, rural residence, infant and young child feeding (IYCF) practices, infectious disease (e.g., malaria, tuberculosis, intestinal parasitic infestation), under-nutrition (e.g., stunting, wasting, and underweight), poor socioeconomic status, household food insecurity, duration of lactation, poor dietary iron intake, maternal illiteracy and maternal anemia are reported as predictors of anaemia. \u003csup\u003e(4, 5, 6, 7)\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAccording to recent information from the South-Asian region, nearly 79% Indian children aged 6\u0026ndash;35 months suffer from anaemia with a rural predominance.\u003csup\u003e8, 9\u003c/sup\u003e Anaemia still remains as one of the major cause of mortality and morbidity in many developing countries including Bangladesh..\u003csup\u003e1\u003c/sup\u003e In Bangladesh, several studies have reported that anemia among the under-five children is a considerable public health problem. Bangladesh Demographic Health Survey (BDHS) 2011 reported 51% anaemia prevalence in the total population.\u003csup\u003e10\u003c/sup\u003e An anemia prevalence of 33.1% was reported by National Micronutrient Status Survey in pre-school children with rural and urban prevalence of 37.0% and 22.8% respectively.. Several studies found that the prevalence of anemia was higher in children aged\u0026thinsp;\u0026lt;\u0026thinsp;3 years among under-five children.\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eTimely starting of complementary feeding at age 6 months is an utmost importance for infant growth and nutrition. In Bangladesh, nearly 62% of children start delayed complementary feeding.\u003csup\u003e10\u003c/sup\u003e The suboptimal infant and young child feeding (IYCF) practices along with early or delayed weaning was found associated with high level nutritional anaemia.\u003csup\u003e10\u003c/sup\u003e Iron deficiency is the most common cause of nutritional anemia in young children.\u003csup\u003e11, 12\u003c/sup\u003e Folic acid and vitamin B12 deficiency are also not uncommon causes of nutritional anaemia.\u003csup\u003e11,\u003c/sup\u003e Prevalence of iron deficiency anemia varies across countries with four-times higher in developing than in developed countries.\u003csup\u003e5\u003c/sup\u003e. Empirically, iron deficiency anemia increases risk of morbidity and mortality from infectious disease.\u003csup\u003e4,9,13\u003c/sup\u003e To eliminate childhood nutritional anemia, particularly iron deficiency anaemia is a public-health priority and reportedly the most common cause of anaemia among under-five children with high prevalence among rural dwellers who occupy nearly 68% of the total population of Bangladesh.\u003csup\u003e14\u003c/sup\u003e However, there are very few studies and consistent data on the current prevalence of anaemia and its determinants in under-five children in rural Bangladesh to fight anaemia. Hence, we aim for such a study.\u003c/p\u003e "},{"header":"Materials And Methods","content":"\u003cp\u003eObjective:\u003c/p\u003e \u003cp\u003eThis study is aimed (i) to identify the current prevalence of anemia among under-five children in rural Bangladesh, and (ii) to assess if there are any associations of anemia with socio-demographic, health, food and nutritional factors in this target population.\u003c/p\u003e \u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003eStudy design, settings, and population\u003c/h2\u003e \u003cp\u003e \u003cem\u003eA cross-sectional study was conducted in the rural areas of northern Bangladesh. Eleven Upazillas (sub-district) of five districts were selected purposively as the study settings (\u003c/em\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cem\u003e). The study districts and Upazilla represent typical and nearly homogenous socioeconomic, demographic and cultural contexts of rural Bangladesh. Nearly 85% population of the sample districts were rural residents.\u003c/em\u003e\u003csup\u003e\u003cem\u003e10\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSample districts with corresponding sample upazillas\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eDistrict\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCorresponding upazilla*\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eJoypurhat\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ePanchbibi, Jopurhat Sador, Ketlal, Kalai, Akkelpur\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eDinajpur\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eHakimpur, Ghoraghat\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNaugaon\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eDhamuirhat, Bodolgachi\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGaibandha\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eGobindogong\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBogura\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eSibgong\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eNote: several upazillas form a district.\u003c/p\u003e \u003cp\u003e \u003cem\u003eUnder-five children aged 6 - \u0026lt;60 months were the target population. A sample size of 325 was calculated using Cockranch's formula\u003c/em\u003e (\u003cem\u003ewhere N\u0026thinsp;=\u0026thinsp;Sample size, z\u0026thinsp;=\u0026thinsp;1.96 (95% confidence level), p\u0026thinsp;=\u0026thinsp;33% estimated prevalence of anemia in under-five population basing on available information, and e\u0026thinsp;=\u0026thinsp;0.05 at 5% margin of error).\u003c/em\u003e\u003c/p\u003e \u003cp\u003eRural children of aged 6 - \u0026lt;60 months whose guardians provided written consent were included in the study. Children who were living in urban, i.e., municipality area, in need of emergency care and hospitalization, and/or having history of blood transfusion within last three months from the date of data collection were not included.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData collection tools and techniques\u003c/h2\u003e \u003cp\u003eA questionnaire was prepared involving three researchers; any contradictions were solved by discussion. A piloting was conducted by the Principal Investigator (PI) involving parents of ten patients for testing mainly the qualitative variables and to develop skills of the PI. The questionnaire was finalized with minimum changes and contained the following four main section : \u003cem\u003eparticulars of the child\u003c/em\u003eren, \u003cem\u003equantitative domains\u003c/em\u003e: nutritional anthropometry (height/length, weight) and laboratory reports (complete hemogram, ferritin level, Hb electrophoresis, Zinc level, Folate and vitamin B\u003csub\u003e12\u003c/sub\u003e assay); \u003cem\u003equalitative domains\u003c/em\u003e: socio- demographic variables (maternal education, income and occupation of household head, number of children, consanguinity), nutrition (breast feeding, IYCF, stunting, wasting, underweight, consumption of protein, fruits, vegetable) and health (maturity at birth and birth size, and history of recent infection.\u003c/p\u003e \u003cp\u003eData was collected consecutively from purposively selected 22 rural health facilities and EPI outreach centers in the study Upazilas. At first the PI (a child health specialist experienced in primary research), approached the under-five children presented at the out-patient department of the selected health facilities. The objectives of the study and the reason of collecting blood were explained. Parents/guardians were assured free of cost blood tests which would solely be used for the study. They were also assured access to the study findings with a guideline for the next treatment options, but without financial benefits. Following an initial face-to-face interview for collecting qualitative data, parents with eligible child were sent to the assigned laboratory. \u003cem\u003eFive millilitre (ml) venous blood was drawn using a sterile syringe (3ml blood were preserved into ethylene ediamine tetraacetic acid (EDTA) vial and the next 2ml into another test-tube for separating serum). The EDTA blood was analyzed on the same day with an \u0026lsquo;Automated Hematology Analyzer\u0026rsquo; (Nihon Kohden,Tokyo, Japan) for a Complete Blood Count (CBC; i.e., haemoglobin percentage, hematocrit), Red cell indices (i.e., MCV, MCH, MCHC, RWD), total count of white blood cell (WBC), differential count of WBC and total platelet count. The degree of anaemia was classified into three categories on the basis of hemoglobin level as defined by the World Health Organization.\u003c/em\u003e\u003csup\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sup\u003e\u003cem\u003eAccordingly, mild anaemia was considered with a Hb% of 10.00\u0026ndash;10.90 gm/dl, which for moderate and severe anaemia were 7.00\u0026ndash;9.90 gm/dl and \u0026lt;\u0026thinsp;7.00gm/dl respectively.\u003c/em\u003e\u003c/p\u003e \u003cp\u003eBasing on mean corpuscular volume (MCV), anemia were further classified as normocytic (MCV 80\u0026ndash;96 fl), microcytic (MCV\u0026thinsp;\u0026lt;\u0026thinsp;80 fl), and macrocytic (MCV\u0026thinsp;\u0026gt;\u0026thinsp;96 fl). Serum Ferritin and/or Hb-electrophoresis were done in children with microcytic hypochromic anemia; whereas macrocytic anemias were evaluated assaying Vitamin B\u003csub\u003e12\u003c/sub\u003e and folic acid levels; and normocytic normochromic anaemia were investigated with Serum Zinc level to reach the etiological pattern of anemia (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eEthical clearance\u003c/h2\u003e \u003cp\u003e\u003cem\u003eEthical clearance was obtained from the Institutional Animal, Medical Ethics, Bio-safety and Bio-security Committee (IAMEBBC) of the Institute of Biological Sciences, Rajshahi University (memo no: 83/320/IAMEBBC/IBSC, date: 27 August 2017). Informed written consents were taken from parents of the sample children.\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003e \u003cem\u003eData were computed and analyzed using SPSS (version 23.0). Univariate analysis and chai-squared tests were the main models to identify the prevalence of anaemia and to assess any association between the independent variables and anaemia. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered as significant.\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e "},{"header":"Results","content":" \u003cp\u003eBecause of time and resource constraints, it was possible to collect data from a total of 258 target children from a total of eleven sample upazillas of five districts (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). 60% of the total study subjects were male and the rest were female. Overall prevalence of anaemia was 61.23% (N\u0026thinsp;=\u0026thinsp;258). Of the total male children (n\u0026thinsp;=\u0026thinsp;154), nearly 65% were anaemic and that was 56% in female children (n\u0026thinsp;=\u0026thinsp;104).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003edistribution of sample children across the sample districts\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistrict (No. of Upazilla)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSampled children\u003c/p\u003e \u003cp\u003e(% of total enrolled)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJoypurhat (5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e90 (34.88%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDinajpur (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59 (22.86%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGaibandha (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38 (14.73%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNaugaon (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41 (15.90%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBogura (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30 (11.63%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe gender difference in prevalence of anaemia was not significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.088). The majority (50%) children was in age group 6\u0026ndash;24 months, which was followed by \u0026gt;\u0026thinsp;36\u0026ndash;60 months (34%) and \u0026gt;\u0026thinsp;24\u0026ndash;36 months (16%). The prevalence of anaemia was 72%, the highest, in 6\u0026ndash;24 months\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-demographic characteristics of the participant children in relation to anaemia\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSubject distribution (%)\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;258)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePrevalence of anaemia\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;158 (100%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eChi-squire statistics\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eGender\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e100 (64.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e = 791.22; p\u0026thinsp;=\u0026thinsp;0.08\u003c/p\u003e \u003cp\u003ephi\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.092\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e154 (59.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e104 (40.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58 (55.77)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eAge (in month)\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e = 9.1; p\u0026thinsp;=\u0026thinsp;0.001\u003c/p\u003e \u003cp\u003ephi\u0026thinsp;=\u0026thinsp;.257\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u0026ndash;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e129 (50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e93 (72.09)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;24\u0026ndash;36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 (15.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26 (63.41)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;36\u0026ndash;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88 (34.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39 (44.31)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eReligion or ethnicity\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e = 792.4; p\u0026thinsp;=\u0026thinsp;0.117\u003c/p\u003e \u003cp\u003ephi\u0026thinsp;=\u0026thinsp;.129\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIslam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e229 (88.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e145 (63.31)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHinduism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (8.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9 (40.90)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndigenous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (2.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (57.14)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eEducation level of mother\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e =783.31; p\u0026thinsp;=\u0026thinsp;0.001\u003c/p\u003e \u003cp\u003ephi\u0026thinsp;=\u0026thinsp;.228\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary enrollment or below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e151 (58.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e104 (68.87)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary enrollment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65 (25.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38 (58.46)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbove secondary or higher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (16.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16 (38.09)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eNumber of children (parity)\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e = 478; p\u0026thinsp;=\u0026thinsp;0.35\u003c/p\u003e \u003cp\u003ephi\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.058\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e235 (91.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e146 (62.12)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (8.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12 (52.17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eOccupation of household head\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e = 8.6; p\u0026thinsp;=\u0026thinsp;0.111\u003c/p\u003e \u003cp\u003ephi\u0026thinsp;=\u0026thinsp;.153\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eService (public or private)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89 (34.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54 (60.67)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAgriculture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63 (24.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41 (65.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmall Business\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91 (35.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50 (54.94)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDay Labour\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (5.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13 (86.66)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eMonthly (family) income\u003c/span\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003ein Taka\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e=811.62; p\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003cp\u003ephi\u0026thinsp;=\u0026thinsp;.318\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;5000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (11.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(21) 72.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5001\u0026ndash;10000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87 (33.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68 (78.16)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10001- 20,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80 (31.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45 (56.25)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;20,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62 (24.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24 (38.70)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003egroup, which was followed by 63% in age group\u0026thinsp;\u0026gt;\u0026thinsp;24\u0026ndash;36 months and 44.3% in \u0026gt;\u0026thinsp;36\u0026ndash;60\u003c/p\u003e \u003cp\u003emonths with a statistically significant association between age categories and anaemia (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Among the children, Muslims were from the majority 88.8% and the rest were from Hindu and indigenous population. The prevalence of anaemia was the highest (63.3%) in\u003c/p\u003e \u003cp\u003eMuslims, which was followed by 57.1% in indigenous group and 40.9% in Hindus. The association between religion and anaemia was not significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.12) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eParity (i.e., mothers with \u0026le;\u0026thinsp;2 children (91.1%) versus \u0026gt;\u0026thinsp;2 children (8.9%)) was found not significantly associated with anaemia (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.23). The distribution of small business and service were nearly equal of the children\u0026rsquo;s family heads\u0026rsquo; occupation, 35.5% and 34.5% respectively and that the rest 24.4% and 5.8% were farming and day labour. Prevalence of anaemia in children belong to the day labour families was noticeably the highest (nearly 87%), which among the children in the other three family occupation groups were nearly equal ranging from 55% in small business family to 65% in farmer family. There was no significant association between anaemia and family occupations (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.11).\u003c/p\u003e \u003cp\u003eAmong four categories of monthly family income, distributions of children were nearly equal in the middle two family income groups (i.e., 33.8% and 31% in 5,001\u0026ndash;10,000 Taka (the Bangladesh currency) and 10,001\u0026ndash;20,000 Taka groups respectively). Notably, children of the lowest two family income groups had nearly equally the highest prevalence of anaemia; 78% and 72% in 5,001\u0026ndash;10,000 Taka and \u0026le;\u0026thinsp;5,000 Taka groups respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Anaemia was found significantly associated with monthly family income (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The majority, 58.5% of the total mothers\u0026rsquo; education level was below primary level. Maternal education was found significantly associated with children\u0026rsquo;s anaemia (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNutrition and food related factors associated with the prevalence of anaemia (n\u0026thinsp;=\u0026thinsp;258)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSubject distribution (%) (N\u0026thinsp;=\u0026thinsp;258)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePrevalence of anaemia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eChi-squire statistics\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eExclusive Breast feeding\u003c/em\u003e\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e186 (72.1%)\u003c/p\u003e \u003cp\u003e72 (27.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e106 (56.99%)\u003c/p\u003e \u003cp\u003e52 (72.22%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e \u0026thinsp;=\u0026thinsp;5.074; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.016\u003c/p\u003e \u003cp\u003ephi\u0026thinsp;=\u0026thinsp;.140\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTimely weaning/IYCF practice\u003c/em\u003e\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e169 (65.5%)\u003c/p\u003e \u003cp\u003e89 (34.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89 (52.66%)\u003c/p\u003e \u003cp\u003e69 (77.52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;15.186; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003cp\u003ephi\u0026thinsp;=\u0026thinsp;.243\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAnimal protein intake regularly\u003c/em\u003e\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e210 (81.4%)\u003c/p\u003e \u003cp\u003e48 (18.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e113 (53.80%)\u003c/p\u003e \u003cp\u003e45 (93.75%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;26.257; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001 phi\u0026thinsp;=\u0026thinsp;.319\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePlant protein intake regularly\u003c/em\u003e\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93 (36%)\u003c/p\u003e \u003cp\u003e165 (64%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 (53.76%)\u003c/p\u003e \u003cp\u003e108 (65.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e \u0026thinsp;=\u0026thinsp;3.425; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.064\u003c/p\u003e \u003cp\u003ephi\u0026thinsp;=\u0026thinsp;.115\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eFruits intake regularly\u003c/em\u003e\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e141 (54.7%)\u003c/p\u003e \u003cp\u003e117 (45.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70 (49.65%)\u003c/p\u003e \u003cp\u003e88 (75.21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e \u0026thinsp;=\u0026thinsp;17.61; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003cp\u003ephi\u0026thinsp;=\u0026thinsp;.261\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGreen leafy vegetable regularly\u003c/em\u003e\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e150 (58.1%)\u003c/p\u003e \u003cp\u003e108 (41.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77 (51.33%\u003c/p\u003e \u003cp\u003e81 (75%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e \u0026thinsp;=\u0026thinsp;14.81; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003cp\u003ephi\u0026thinsp;=\u0026thinsp;.240\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eUnderweight\u003c/em\u003e\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40 (15.5%)\u003c/p\u003e \u003cp\u003e218 (84.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (77.5%)\u003c/p\u003e \u003cp\u003e127 (58.26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e \u0026thinsp;=\u0026thinsp;5.27; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.022\u003c/p\u003e \u003cp\u003ephi\u0026thinsp;=\u0026thinsp;.143\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eStunted\u003c/em\u003e\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74 (28.7%)\u003c/p\u003e \u003cp\u003e184 (31.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55 (74.32%)\u003c/p\u003e \u003cp\u003e103 (55.98%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e \u0026thinsp;=\u0026thinsp;7.48; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.007\u003c/p\u003e \u003cp\u003ephi\u0026thinsp;=\u0026thinsp;.170\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eWasted\u003c/em\u003e\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (11.2%)\u003c/p\u003e \u003cp\u003e229 (88.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (89.66%)\u003c/p\u003e \u003cp\u003e132 (57.64%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e \u0026thinsp;=\u0026thinsp;11.11; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003cp\u003ephi\u0026thinsp;=\u0026thinsp;.208\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eExclusive breast feeding children had nearly 18% lower anaemia prevalence than non-exclusive breast feeding group and the difference was statistically significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02). Delayed or early weaning-practiced children had nearly 25% higher prevalence of anaemia than their properly weaning counterpart with a statistically significant difference (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Non-consumption of animal protein group were found almost 2 times higher anaemia prevalence than animal protein consumption group, which was statistically significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001). Plant protein (pulses) intake group had nearly 10% lower anaemia prevalence than non-consumption group, which was not significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.064).\u003c/p\u003e \u003cp\u003eChildren with regular fruits intake had significantly lower prevalence of anaemia by 26% than non-consumption group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001). Children with regular intake of green leafy vegetables also had nearly 26% lower anaemia prevalence than in non-consumption group with a statistically significant difference (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001). Underweight children had 1.5 times higher prevalence of anaemia than their normal counterpart with a significant difference (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.022). Stunted children were found 20% higher and significant risk of developing anaemia than their counterpart (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006). Acute under-nourished children had nearly twice higher vulnerability of developing anaemia than normal children with a significant difference (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eParents\u0026rsquo; consanguinity status showed no significant difference in childhood anaemia (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.373). Pre-term children had nearly 4.5 times and 9 times higher anaemia prevalence than term and post-term babies respectively although the differences were not significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.153). Birth size of babies (normal/small/large) had no significant influence on the prevalence of anaemia (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.69). Children suffering from chronic illness or recent illness had 23% higher anaemia prevalence than apparently healthy children, which was statistically significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation of key health and social factors to anaemia (N\u0026thinsp;=\u0026thinsp;258)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDistribution of subjects (%) (N\u0026thinsp;=\u0026thinsp;258)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePrevalence of anaemia (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eChi-squire statistics\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eConsanguinity of parents\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u003cem\u003e=\u0026thinsp;1.058; p\u0026thinsp;=\u0026thinsp;.373\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003ePhi\u0026thinsp;=\u0026thinsp;.064\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39 (15.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21 (53.84%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e219 (84.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e137 (62.55%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMaturity level at birth\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u003cem\u003e=\u0026thinsp;3.758; p\u0026thinsp;=\u0026thinsp;0.153\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003ePhi\u0026thinsp;=\u0026thinsp;.121\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFull term\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e201 (77.91%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12 (5.79%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-term\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45 (17.44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32 (71.11%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost-term\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12(04.65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (41.67%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSize of baby at birth\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u003cem\u003e=\u0026thinsp;0.724; \u0026nbsp;p\u0026thinsp;=\u0026thinsp;0.69\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003ePhi\u0026thinsp;=\u0026thinsp;.054\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e148 (57.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (62.12%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50 (19.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32 (64.00%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLarge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60 (23.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34 (56.66%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChronic illness or recent illness\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u003cem\u003e=\u0026thinsp;12.867; p\u0026thinsp;=\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003ePhi\u0026thinsp;=\u0026thinsp;.223\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e97 (37.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e73 (75.25%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e161 (62.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e85 (52.79%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAmong the anaemic children (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;158), mild (Hb% 10-\u0026lt;11 gm/dl) and moderate (Hb% 7-\u0026lt;10 gm/dl) degree of anaemia were nearly equally distributed 46.2% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;73) and 47% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;74) respectively, whereas severe anaemia (Hb% \u0026lt;7 gm/dl) was only 7%.\u003c/p\u003e "},{"header":"Discussion","content":" \u003cp\u003eThe study was undertaken to assess the current prevalence of anemia and its association with socio-demographic, health and nutritional factors in under-five children in rural Bangladesh.\u003c/p\u003e \u003cp\u003eThe overall prevalence of anaemia (N\u0026thinsp;=\u0026thinsp;258) was 61.23% with proportion of mild, moderate and severe anaemia of 28.29%, 28.68% and 4.26% respectively. High prevalence of anaemia was found in some other studies in India, Tanzania, Kenya, and South Africa where the prevalence of anaemia was observed between (69% \u0026minus;\u0026thinsp;79%) in under-five children\u003csup\u003e18\u0026ndash;20,29\u003c/sup\u003e. The prevalence of severe anaemia (4.26%) was lower than in similar settings; for example, Muoneke et al,\u003csup\u003e15\u003c/sup\u003e reported a prevalence of severe anaemia of 9.7% in Nigerian under-five children. Nearly consistent trends of mild, moderate and severe anaemia and associated factors in under-five children of this study were found in a study of Simbauranga et al at Tanzania.\u003csup\u003e16\u003c/sup\u003e In their study, the mild, moderate and severe anaemia were found 16.5%, 33% and 27.7% respectively. In a study in India, the overall prevalence of anaemia in under-five children was found 69.5% with percentage of mild moderate and severe anaemia were 26.2%,, 40.4%, 2.9% respectively\u003csup\u003e30\u003c/sup\u003e, which is nearly consistent with our findings.\u003c/p\u003e \u003cp\u003eMild and moderate anaemia in the total sample accounted nearly equally, 30% each, may be due to nutritional deficiencies and socio-demography related factors in rural Bangladesh. We found no association between gender and anaemia. Age is a significant factor of anaemia in under-five children with the highest prevalence (73%) in \u0026lt;\u0026thinsp;24 months age group than their older counterparts. These findings is consistent with the study findings of Goswmai and Das and the authors mentioned that high demand for nutrients to support the rapid body growth of the children at this age against a low supply might be the key underlying factor.\u003csup\u003e17\u003c/sup\u003e We also found that increasing trends of anaemia up to 2 years and then decreasing after 2 years may be relating to the children\u0026rsquo;s ability to eat varieties of foods. This finding is consistent with the study of Gebreweld et al.\u003csup\u003e18\u003c/sup\u003e We found no significant link of ethnicity, religion or consanguinity to childhood anaemia which contradicts the findings of Goswmai and Das.\u003csup\u003e17\u003c/sup\u003e In this Indian study among under-five children, the authors found significant difference in religion and all types of anaemia prevalence (severe, moderate, and mild) were higher among children of Hindu families than other religions. We found that higher the mother\u0026rsquo;s level of education lower the anaemia prevalence in children. Children of mothers with higher/above HSC education level had nearly two times lower risk of developing anaemia than that in below HSC level mothers. This finding is agreed with the studies of Kuziga et al.\u003csup\u003e19\u003c/sup\u003e and Leite et al \u003csup\u003e20\u003c/sup\u003e. We found that neither occupation nor parity is significantly linked to childhood anaemia. However, family income is a significant factor with an inverse relationship between income and prevalence of childhood anaemia. The similar observations were also noted in some previous studies. \u003csup\u003e20, 21\u0026ndash;22\u003c/sup\u003e This is may be due to the fact that higher income is linked to good maternal education and better nutritional protection to children.\u003c/p\u003e \u003cp\u003eBoth non-exclusive breast feeding and delayed/early weaning were found significant factors of developing anaemia in children. Oppositely, EBF, timely weaning, regular consumption of animal protein, green leafy vegetables and locally available fruits were found protective to childhood anaemia. These findings are consistent with the study of Kejo et al.\u003csup\u003e23\u003c/sup\u003e Stunted, underweight and wasted children were found more anaemic, which is consistent with the study of Kisiangani et al. \u003csup\u003e24\u003c/sup\u003e. Children with chronic illness and recent illness were nearly 1.5 time high risk of developing anaemia which is also comply with the findings of Kumari et al.\u003csup\u003e25\u003c/sup\u003e However, it is not known if those disorders are causing anaemia or vice versa although synergistic effects on each other are well-known.\u003c/p\u003e \u003cp\u003eLimitations and strengths\u003c/p\u003e \u003cp\u003eBecause of time and resource limits, the sample size was smaller than expected. The study was confined in northern Bangladesh. However, in nearly a homogenous rural context of the country, this study finding is claimed as a reflection of the childhood anaemia scenario of rural Bangladesh. In regard to the associated factors of anaemia, only univariant analyses were done, but the variants did not put together in a regressive model to identify the potential predictors.\u003c/p\u003e "},{"header":"Conclusion","content":" \u003cp\u003ePrevalence of anaemia in under-five children of rural Bangladesh remains noticeably high. Age, maternal education, family income, consumption of animal protein, green leafy vegetables, and fruits along with underweight, stunting and wasting are inversely related to anaemia prevalence. Exclusive breast feeding and timely weaning may reduce risk of anaemia. In addition, chronic and recent illness increase susceptibility to anaemia development.\u003c/p\u003e "},{"header":"Abbreviations","content":" \u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBDHS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBangladesh Demographic Health Survey\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCBC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eComplete Blood Count\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLBW\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003elow birth weight\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEDTA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEthylene-Diamine-Tetraacetic-Acid\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEPI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eExpanded Programme on Immunization\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHb\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHemoglobin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHKI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHelen Keller International\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHIV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHuman Immunodeficiency Virus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eICDDR,B\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInternational Centre for Diarrheal Disease Research, Bangladesh\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIDA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIron Deficiency Anaemia\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIPHN\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInstitute of Public Health Nutrition\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIYCF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInfant and Young Child Feeding\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMCH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMean corpuscular hemoglobin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMCHC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMean corpuscular hemoglobin concentration\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMCV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMean corpuscular volume\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eORC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOut Reach Centre\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePreSAC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePre-school aged children\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRBC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRed Blood Cell\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRDW\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRed Cell distribution Width\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUNICEF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUnited Nations International Children\u0026rsquo;s Emergency Fund\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWHO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWorld Health Organization.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUHC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUpazila Health Complex\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSAC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSchool aged children\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eE\u003c/em\u003e\u003cem\u003ethical clearance was obtained from the Institutional Animal, Medical Ethics, Bio\u003c/em\u003e\u003cem\u003e-\u003c/em\u003e\u003cem\u003esafety and Bio-security\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eCommittee (IAMEBBC) of\u0026nbsp;\u003c/em\u003e\u003cem\u003ethe\u0026nbsp;\u003c/em\u003e\u003cem\u003eInstitute of Biological Sciences, Rajshahi University\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003e(\u003c/em\u003ememo no: 83/320/IAMEBBC/IBSC, date: 27 August \u0026nbsp;2017\u003cem\u003e)\u003c/em\u003e\u003cem\u003e.\u0026nbsp;\u003c/em\u003e\u003cem\u003eInformed written consent were taken from the attending guardian of enrolled children.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e:\u003c/strong\u003e not applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eData of this study will be made available from the corresponding author on rational request. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare that they have no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe research was funded by the \u003cem\u003eInstitute of Biological Sciences, Rajshahi University\u003c/em\u003e\u003cem\u003e, Rajshahi, Bangladesh\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u0026nbsp;\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMdMM: research concept, questionnaire development, interview, data collection, nutritional anthropometry, data processing, analyzing, interpreting, and writing the manuscript. AM: research concept, developing questionnaire, reviewing and revising the final manuscript. AH: Checking clinical data, and methodology development, AAR: developing research concept, major contribution in statistical analysis, data interpretation, reviewing the manuscript, and revising the final version. SN: data processing, questionnaire development PH: research concept, developing questionnaire, data interpretation, reviewing and revising the final manuscript. All authors read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAuthors of the paper\u0026nbsp;acknowledge and offer\u0026nbsp;thanks\u0026nbsp;to\u0026nbsp;\u003cem\u003ethe\u0026nbsp;\u003c/em\u003e\u003cem\u003eInstitute of Biological Sciences, Rajshahi University\u003c/em\u003e\u003cem\u003e\u0026nbsp;for providing resourceful environment for conducting the research\u003c/em\u003e\u003cem\u003e.\u0026nbsp;\u003c/em\u003e\u003cem\u003eAlso the cooperation of the expert laboratory staff is highly appreciated.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eAuthors\u0026rsquo; information \u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMd. Moniruzzaman Mollah,\u0026nbsp;(MBBS, DCH) PhD Fellow (IBSc), Assistant Professor,\u0026nbsp;Department of Paediatrics, Shaheed Ziaur Rahman Medical College, Bogura, Bangladesh; Prof. Dr. Ashik Mosaddi PhD, Professor and Chairman,\u0026nbsp;Department of Pharmacy, University of Rajshahi, Rajshahi; Dr. Asgor Hossain, MBBS, FCPS\u003csup\u003e.\u0026nbsp;\u003c/sup\u003eAssociate Prof. (Rtd.), Department of Paediatrics, Rajshahi Medical College, Rajshahi, Bangladesh; Dr. Andrew A. Roy (PhD, MBBS, MSc, MPH) Faculty and Researcher, Department of Medicine and Biomedical Sciences, Maastricht University, the Netherlands; Dr. Sultana Naznin MBBS, DGO.\u003csup\u003e\u0026nbsp;\u003c/sup\u003eResident Surgeon, Department of Gynae and Obs, IBMCH, Rajshahi, Bangladesh; Prof. Dr. Parvez Hassan PhD,\u003csup\u003e\u0026nbsp;\u003c/sup\u003eIBSc, Rajshahi University, Rajshahi, Bangladesh.\u003c/p\u003e"},{"header":"References","content":"\u003cp\u003e1. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Khan JR, Awan N, Misu F. Determinants of anemia among 6-59 months aged children in Bangladesh: Evidence from nationally representative data. \u003cem\u003eBMC Pediatr\u003c/em\u003e. 2016;16(1):1-13. doi:10.1186/s12887-015-0536-z\u003c/p\u003e\n\u003cp\u003e2. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;World Health Organization. \u003cem\u003eIron Deficiency Anaemia: Assessment, Prevention, and Control A Guide for Programme Managers\u003c/em\u003e. 2001;Vol 314.\u003c/p\u003e\n\u003cp\u003e3. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;World Health Organization. Worldwide prevalence of anaemia, WHO Vitamin and Mineral Nutrition Information System, 1993-2005. 2009. doi:10.1017/S1368980008002401\u003c/p\u003e\n\u003cp\u003e4. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Haas JD, Brownlie IV T. Iron deficiency and reduced work capacity: A critical review of the research to determine a causal relationship. \u003cem\u003eJ Nutr\u003c/em\u003e. 2001;131(2 SUPPL. 2):676-690. doi:10.1093/jn/131.2.676s\u003c/p\u003e\n\u003cp\u003e5. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Villalpando S, Shamah-levy T, Sc B, Ram\u0026iacute;rez-silva CI, Mej\u0026iacute;a-rodr\u0026iacute;guez F, Rivera JA. Prevalence of anemia in children 1 to 12 years of age . Results from a nationwide probabilistic survey in Mexico. \u003cem\u003esalud p\u0026uacute;blica m\u0026eacute;xico /\u003c/em\u003e. 2003;45(1).\u003c/p\u003e\n\u003cp\u003e6. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Shet A, Mehta S, Rajagopalan N, et al. Anemia and growth failure among HIV-infected children in India: A retrospective analysis. \u003cem\u003eBMC Pediatr\u003c/em\u003e. 2009;9:1-9. doi:10.1186/1471-2431-9-37\u003c/p\u003e\n\u003cp\u003e7. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;S. Akers A, Howard D, Ford J. Distinguishing iron deficiency anaemia from thalassemia trait in clinical obstetric practice. \u003cem\u003eJ Pregnancy Reprod\u003c/em\u003e. 2018;2(1):1-6. doi:10.15761/jpr.1000125\u003c/p\u003e\n\u003cp\u003e8. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;USAID. \u003cem\u003eOverview of the Nutrition Situation in Four Countries in South and Central Asia\u003c/em\u003e.; 2014.\u003c/p\u003e\n\u003cp\u003e9. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Pasricha SR, Black J, Muthayya S, et al. Determinants of anemia among young children in rural India. \u003cem\u003ePediatrics\u003c/em\u003e. 2010;126(1). doi:10.1542/peds.2009-3108\u003c/p\u003e\n\u003cp\u003e10. \u0026nbsp; \u0026nbsp; \u0026nbsp;National Institute of Population Research and Training. \u003cem\u003eBANGLADESH BANGLADESH AND HEALTH SURVEY 2014\u003c/em\u003e.; 2014.\u003c/p\u003e\n\u003cp\u003e11. \u0026nbsp; \u0026nbsp; \u0026nbsp;International Centre for Diarrhoeal Disease Research Bangladesh. \u003cem\u003eNational Micronutrients Status Survey 2011-12: Final Report\u003c/em\u003e.; 2013. https://static1.squarespace.com/static/56424f6ce4b0552eb7fdc4e8/t/57490d3159827e39bd4d2314/1464405328062/Bangladesh_NMS_final_report_2011-12.pdf.\u003c/p\u003e\n\u003cp\u003e12. \u0026nbsp; \u0026nbsp; \u0026nbsp;Gamit M, Talwelkar H. Survey of different types of anemia. \u003cem\u003eInt J Med Sci Public Heal\u003c/em\u003e. 2017;6(3):1. doi:10.5455/ijmsph.2017.0851807092016\u003c/p\u003e\n\u003cp\u003e13. \u0026nbsp; \u0026nbsp; \u0026nbsp;Oppenheimer SJ. Iron-deficiency anemia: reexamining the nature and magnitude of the public health problem. \u003cem\u003eJ Nutr\u003c/em\u003e. 2001;131:616-635.\u003c/p\u003e\n\u003cp\u003e14. \u0026nbsp; \u0026nbsp; \u0026nbsp;Institute of Public Health Nutrition. \u003cem\u003eInstitute of Public Health Nutrition Directorate General of Health Services Ministry of Health and Family Welfare Government of the People\u0026rsquo;s Republic of Bangladesh\u003c/em\u003e.; 2015. http://iphn.dghs.gov.bd/wp-content/uploads/2016/01/NMDCS-.pdf.\u003c/p\u003e\n\u003cp\u003e15. \u0026nbsp; \u0026nbsp; \u0026nbsp;Muoneke VU, ChidiIbekwe R. Prevalence and Aetiology of Severe Anaemia in Under-5 Children in Abakaliki South Eastern Nigeria. \u003cem\u003ePediatr Ther\u003c/em\u003e. 2011;01(03):3-7. doi:10.4172/2161-0665.1000107\u003c/p\u003e\n\u003cp\u003e16. \u0026nbsp; \u0026nbsp; \u0026nbsp;Simbauranga RH, Kamugisha E, Hokororo A, Kidenya BR, Makani J. Prevalence and factors associated with severe anaemia amongst under-five children hospitalized at Bugando Medical Centre, Mwanza, Tanzania. \u003cem\u003eBMC Hematol\u003c/em\u003e. 2015;15(1). doi:10.1186/s12878-015-0033-5\u003c/p\u003e\n\u003cp\u003e17. \u0026nbsp; \u0026nbsp; \u0026nbsp;Goswmai S, Das KK. Socio-economic and demographic determinants of childhood anemia. \u003cem\u003eJ Pediatr (Rio J)\u003c/em\u003e. 2015;91(5):471-477. doi:10.1016/j.jped.2014.09.009\u003c/p\u003e\n\u003cp\u003e18. \u0026nbsp; \u0026nbsp; \u0026nbsp;Gebreweld A, Ali N, Ali R, Fisha T. Prevalence of anemia and its associated factors among children under five years of age attending at Guguftu health center, South Wollo, Northeast Ethiopia. \u003cem\u003ePLoS One\u003c/em\u003e. 2019;14(7):1-13. doi:10.1371/journal.pone.0218961\u003c/p\u003e\n\u003cp\u003e19. \u0026nbsp; \u0026nbsp; \u0026nbsp;Kuziga F, Adoke Y, Wanyenze RK. Prevalence and factors associated with anaemia among children aged 6 to 59 months in Namutumba district, Uganda: A cross- sectional study. \u003cem\u003eBMC Pediatr\u003c/em\u003e. 2017;17(1):1-9. doi:10.1186/s12887-017-0782-3\u003c/p\u003e\n\u003cp\u003e20. \u0026nbsp; \u0026nbsp; \u0026nbsp;Leite MS, Cardoso AM, Coimbra CE, et al. Prevalence of anemia and associated factors among indigenous children in Brazil: Results from the First National Survey of Indigenous People\u0026rsquo;s Health and Nutrition.\u0026nbsp;\u003cem\u003eNutr J\u003c/em\u003e. 2013;12(1):1-11. doi:10.1186/1475-2891-12-69\u003c/p\u003e\n\u003cp\u003e21. \u0026nbsp; \u0026nbsp; \u0026nbsp;Parbey PA, Tarkang E, Manu E, et al.\u0026nbsp;Risk Factors of Anaemia among Children under Five Years in the Hohoe Municipality, Ghana: A Case Control Study. \u003cem\u003eAnemia\u003c/em\u003e. 2019;2019. doi:10.1155/2019/2139717\u003c/p\u003e\n\u003cp\u003e22. \u0026nbsp; \u0026nbsp; \u0026nbsp;Magalh\u0026atilde;es RJS, Clements ACA. Mapping the risk of anaemia in preschool-age children: The contribution of malnutrition, malaria, and helminth infections in West Africa. \u003cem\u003ePLoS Med\u003c/em\u003e. 2011;8(6). doi:10.1371/journal.pmed.1000438\u003c/p\u003e\n\u003cp\u003e23. \u0026nbsp; \u0026nbsp; \u0026nbsp;Kejo D, Petrucka P, Martin H, Kimanya M, Mosha T. Prevalence and predictors of anemia among children under 5 years of age in Arusha District, Tanzania. \u003cem\u003ePediatr Heal Med Ther\u003c/em\u003e. 2018;Volume 9:9-15. doi:10.2147/phmt.s148515\u003c/p\u003e\n\u003cp\u003e24. \u0026nbsp; \u0026nbsp; \u0026nbsp;Kisiangani I, Mbakaya C, Makokha A. Prevalence of Anaemia and Associated Factors Among Preschool Children ( 6-59 Months ) in Western Province , Kenya. \u003cem\u003ePublic Heal Prev Med\u003c/em\u003e. 2015;1(1):28-32.\u003c/p\u003e\n\u003cp\u003e25. \u0026nbsp; \u0026nbsp; \u0026nbsp;Kumari S, Garg N, Kumar A, et al. Maternal and severe anaemia in delivering women is associated with risk of preterm and low birth weight: A cross sectional study from Jharkhand, India. \u003cem\u003eOne Heal\u003c/em\u003e. 2019;8(February):100098. doi:10.1016/j.onehlt.2019.100098\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"anaemia prevalence, childhood anaemia, determinants, iron deficiency, under-five children, rural Bangladesh ","lastPublishedDoi":"10.21203/rs.3.rs-609632/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-609632/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Background\nAnaemia and its association with low physical and cognitive development in under-five children remain as a common public health burden in developing countries including Bangladesh. Childhood anemia is significantly associated with age, rural residence, infant and young child feeding (IYCF) practices, infectious disease, maternal illiteracy etc. We have studied to identify current prevalence, and to explore associated socio-demographic, health, and nutritional factors of anaemia in under-five children of rural Bangladesh.\nMethods and materials\nA cross-sectional study was conducted at five remote northern districts of Bangladesh involving rural children aged 6 - \u003c60 months. We used an interviewer-administered questionnaire for data collection. Potential study subjects were approached conveniently at selected rural health centres. Chi-squared test was the main statistical model to identify association between explanatory variables and anaemia. A p-value \u003c0.05 was considered as significant.\nResults\nOverall prevalence of anaemia (N = 258) was 61.23% with mild, moderate and severe anaemia of 28.29%, 28.68% and 4.26% respectively. The prevalence of anaemia was the highest (72%) in age group 6-24 months, which were followed by 63% in \u003e24-36 months and 44.3% in \u003e36-\u003c60 months categories. The following explanatory variables showed statistically significant association with high anaemia: younger-age (p = \u003c0.001), low family income, and maternal education (p = \u003c0.001), exclusive versus non-exclusive breast feeding (p = 0.02), and timely versus delayed or early weaning (p = \u003c0.001). Non consumption of animal proteins, fruits and green leafy vegetables were also significantly linked to high anaemia prevalence (p = 0.001). Further, underweight, stunting, and wasting were significantly related to anaemia (p = 0.02, 0.006, and 0.001 respectively).\nConclusion\nPrevalence of anaemia in under-five children of rural Bangladesh remains noticeably high. Age, maternal education, family income, consumption of animal protein, green leafy vegetables, and fruits along with underweight, stunting and wasting are inversely related to anaemia prevalence. Exclusive breast feeding and timely weaning may reduce risk of anaemia.","manuscriptTitle":"Current prevalence and determinants of anaemia in under-five children in rural Bangladesh: a cross sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-06-15 14:28:42","doi":"10.21203/rs.3.rs-609632/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":"2a561246-eb00-459f-b2ec-28b92a5810a1","owner":[],"postedDate":"June 15th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":5039550,"name":"Health Economics \u0026 Outcomes Research"}],"tags":[],"updatedAt":"2021-06-15T14:28:43+00:00","versionOfRecord":[],"versionCreatedAt":"2021-06-15 14:28:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-609632","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-609632","identity":"rs-609632","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}