Factors influencing childhood anaemia in Bangladesh: a two level logistic regression analysis

Abstract

Background Anemia is not only a major public health problem among children in developing countries, it is also an important predictor for their future growth and development. The objective of this study was to identify possible factors associated with anemia among pre-school children in Bangladesh after removing a cluster effect of the population, and to determine the prevalence of this condition. Methods Data for this study was extracted from the 2011 Bangladesh Demographic and Health Survey (BDHS-2011). In this survey, data was collected using a two-stage stratified cluster sampling approach. The chi-square test and a two-level logistic regression model were used for further analysis. Results Data from 2231 children aged 6–59 months were included for analysis. The prevalence of child anemia was noted to be 52.10%. Among these anemic children, 48.40% where from urban environment and 53.90% were from rural areas. The prevalence of mild, moderate and severe anemia among children was 57.10, 41.40 and 1.50% respectively. The two-level logistic regression model revealed that the following factors were associated with childhood anemia: children of anemic mothers ( p < 0.01), undernourished children ( p < 0.05), younger children (age < 2 years) ( p < 0.01) and children from poor family ( p < 0.05). Lastly, anemia was more common among children living in Barisal and Rangpur divisions compared to those from Dhaka division ( p < 0.01), and among non-Muslims than Muslim ( p < 0.05). Conclusions Our study showed that prevalence of anemia among pre-school children in Bangladesh was very high (52.10%). We noted that young children of anemic mothers, from poor families, and being undernourished were at higher risk of developing anemia. Since most of these risk factors were related to socioeconomic conditions, they were potentially modifiable. Therefore, our findings may be useful for the health authorities to identify children at risk for remedial action and to plan for preventive measures.

Maternal health status and household food security on determining childhood anemia in Bangladesh -a nationwide cross-sectional study

“…We found that health status of the mother which include maternal anemia and BMI was highly associated with childhood anemia in Bangladesh, which is in line with prior studies [ 23 – 25 , 40 ]. Maternal anemia works in several pathways.…”

“…Shakur et al found that birth weight and month of birth have a significant association with children’s hemoglobin status [ 17 ]. Several studies have identified the determinants of childhood anemia based on nationally representative data from the Bangladesh Demography and Health Survey’2011 [ 23 – 26 ]. However, none of the studies have considered the impact of household food security on childhood anemia.…”

Association between social capital and mental health among older people living with HIV: the Sichuan Older HIV-Infected Cohort Study (SOHICS)

“…Random intercept models were used to allow the intercept of the regression model to vary across communities/towns, which could account for intra-correlated nested data. Two-level logistic regression models are commonly used in studies using similar sampling method as ours [49,50]. Univariate logistic models were first used to examine the significance of the association between each covariate and outcome variable.…”

Low educational level of head of household, as a proxy for poverty, is associated with severe anaemia among children with sickle cell disease living in a low‐resource setting: evidence from the SPRING trial

“…We demonstrate a prevalence (3·9%, 37/941) of severe anaemia in children with SCA, aged between five and 12 years old, living in northern Nigeria, a low resource setting. Severe anaemia was associated with risk factors of poverty 15 , including the lower educational level of the head of household, and a greater number of people, particularly children, living per room in the household. The risk factors identified reflect the low socioeconomic status and educational gaps prevalent in northern Nigeria and other regions in sub‐Saharan Africa, where more than a third of the global burden of SCD is found 16 …”