Peer-reviewed article
On selection of an appropriate logistic model to determine the risk factors of childhood stunting in Bangladesh
Kakoli Rani Bhowmik, Sumonkanti Das ·
Summary
Written by AI, not yet AICS's view · claude-sonnet-5-5This study uses 2014 Bangladesh Demographic and Health Survey data on 6,931 children aged 0–59 months, about 36% of whom were stunted. It compares four logistic regression models that differ in how they treat the survey's sampling design and clustering. The random intercept logistic model was judged the most appropriate on several model selection criteria. Using this model, the study identifies child, mother, household and regional factors linked to higher odds of stunting.
Key points
- About 36% of the 6,931 children with valid height-for-age data were stunted.
- Ordinary, survey, marginal and random intercept logistic models were compared.
- The random intercept logistic model was the most appropriate based on model selection criteria.
- Higher odds of stunting were linked to child age over 11 months, short birth interval, recent child illness, lower maternal education, young maternity, lower maternal body mass index, and poor household wealth.
- Higher odds were also linked to urban residence and living in Sylhet division.
Limitations
The abstract describes a cross-sectional survey analysis, so the factors identified are associations and not proven causes. It gives no effect sizes or detail on how well the models fit.
Abstract
AbstractStunting is the core measure of child health inequalities as it reveals multiple dimensions of child health and development status. The main focus of this study is to show the procedure of selecting the most appropriate logistic regression model for stunting by developing and comparing several plausible models, which ultimately helps to identify the predictors of childhood stunting in Bangladesh. This study utilizes child anthropometric data collected in the 2014 Bangladesh Demographic and Health Survey. Valid height‐for‐age anthropometric indices were available for a total of 6,931 children aged 0–59 months, of which about 36% were stunted. Ordinary logistic, survey logistic, marginal logistic, and random intercept logistic regression models were developed assuming independence, sampling design, cluster effect, and hierarchy of the data. Based on a number of model selection criteria, random intercept logistic model is found the most appropriate for the studied children. A number of child, mother, household, regional, and community‐level variables were included in the model specification. The factors that increased the odds of stunting are children older than 11 months, short birth interval, recent morbidity of children, lower maternal education, young maternity, lower maternal body mass index, poor household wealth, urban residential place, and living in Sylhet division. Findings of this study recommend to utilize an appropriate logistic model considering the issues relevant to the data, particularly sampling design and clustering for determining the risk factors of childhood stunting in Bangladesh.