Factors influencing childhood anaemia in Bangladesh: a two level logistic regression analysis
Abu Yusuf1, A S M A Mamun1, Md Kamruzzaman1
1Health Research Group, Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh.
Insights
Childhood anemia is a significant public health issue in Bangladesh, affecting over half of preschool children. Key risk factors include maternal anemia, malnutrition, poverty, and young age, highlighting the need for targeted interventions.
Area of Science:
- Public Health
- Pediatrics
- Nutritional Epidemiology
Background:
- Anemia poses a major public health challenge for children in developing nations, impacting their long-term growth and development.
- Identifying anemia's prevalence and associated factors in preschool children is crucial for effective health strategies.
Purpose of the Study:
- To determine the prevalence of anemia among preschool children in Bangladesh.
- To identify factors associated with childhood anemia, accounting for population clustering.
Main Methods:
- Utilized data from the 2011 Bangladesh Demographic and Health Survey (BDHS-2011).
- Employed a two-stage stratified cluster sampling methodology for data collection.
- Applied chi-square tests and a two-level logistic regression model for statistical analysis.
Main Results:
- The study included 2231 children aged 6-59 months, revealing an anemia prevalence of 52.10%.
- Significant risk factors for anemia included maternal anemia, undernutrition, younger age (under 2 years), and lower socioeconomic status.
- Anemia prevalence varied geographically and by religious affiliation, being higher in Barisal and Rangpur divisions and among non-Muslims.
Conclusions:
- The high prevalence of anemia (52.10%) in Bangladeshi preschool children necessitates urgent public health attention.
- Maternal anemia, child malnutrition, poverty, and young age are key modifiable risk factors for childhood anemia.
- Findings provide valuable insights for health authorities to implement targeted preventive and remedial actions for at-risk children.
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.
Related Concept Videos
01:52Regression Toward the Mean
01:11Regression Analysis
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
01:22Bioavailability: Influencing Factors
01:18Microsoft Excel: Regression Analysis
To perform regression...
01:29Factors Influencing Microbial Growth: pH
01:22Factors Influencing Attraction I: Proximity