Counting Household-Level Child Malnutrition Among Children Age Under Five Years in Bangladesh: ASpatial Cross-Sectional Study

Although child malnutrition has declined globally over recent decades, it remains a major public health challenge in developing countries such as Bangladesh. This study analyzes data from the Multiple Indicator Cluster Survey (MICS), conducted by UNICEF in collaboration with the Bangladesh Bureau of Statistics (BBS) using a two-stage stratified sampling design. The survey covered approximately 64,000 households nationwide, of which 8,671 households with at least one child under five years of age were included in the analysis. The outcome variable is the household-level count of malnourished children, while the explanatory variables consist of categorical sociodemographic characteristics listed in Appendix table: 4. The study sample consisted of nearly equal proportions of male (51.0%) and female children across age groups. More than half of the households (57.0%) reported zero malnourished children, supporting the use of a zero-inflated modeling approach. Bivariate associations between socio-demographic factors and child malnutrition were initially assessed using the Pearson chi-square (χ2) test. Given the presence of excess zeros and the fact that the variance (σ2 = 1.18) was not substantially larger than the mean (μ = 0.78), a zero-inflated Poisson (ZIP) model was fitted within a Bayesian spatial framework using Integrated Nested Laplace Approximation (INLA) to estimate covariate effects. The INLA estimate suggested that child malnutrition exhibits strong spatial dependence across district levels in Bangladesh. The results also indicate that antenatal care (ANC) visits, higher household economic status, parental education, higher birth weight, and first-order birth were significantly associated with lowering counts of child malnutrition in household level. In contrast, children aged 24–59 months, residence in middle-income households, and low birth weight were associated with increasing household-level counts of child malnutrition.