Abstract
Objective
The aim of this study was to construct a predictive model in order to develop an intervention study to reduce the prevalence of stunting among children aged 12–23 months.
Design
The study followed a cluster randomised pre-post design and measured the impacts on various indicators of livelihood, health and nutrition. The study was based on a large dataset collected from two cross-sectional studies (baseline and endline).
Setting
The study was conducted in the north-eastern region of Bangladesh under the Sylhet division, which is vulnerable to both natural disasters and poverty. The study specifically targeted children between the ages of 12 and 23 months.
Main outcome measures
Childhood stunting, defined as a length-for-age z-score <−2, was the outcome variable in this study. Logistic and probit regression models and a decision tree were constructed to predict the factors associated with childhood stunting. The predictive performance of the models was evaluated by computing the area under the receiver operating characteristic (ROC) curve analysis.
Results
The baseline survey showed a prevalence of 52.7% stunting, while 50.0% were stunted at endline. Several factors were found to be associated with childhood stunting. The model’s sensitivity was 61% and specificity was 56%, with a correctly classified rate of 59% and an area under the ROC curve of 0.615.
Conclusion
The study found that childhood stunting in the study area was correlated with several factors, including maternal nutrition and education, food insecurity and hygiene practices. Despite efforts to address these factors, they remain largely unchanged. The study suggests that a more effective approach may be developed in future to target adolescent mothers, as maternal nutrition and education are age-dependent variables. Policy makers and programme planners need to consider incorporating both nutrition-sensitive and nutrition-specific activities and enhancing collaboration in their efforts to improve the health of vulnerable rural populations.
The aim of this study was to construct a predictive model in order to develop an intervention study to reduce the prevalence of stunting among children aged 12–23 months.
Design
The study followed a cluster randomised pre-post design and measured the impacts on various indicators of livelihood, health and nutrition. The study was based on a large dataset collected from two cross-sectional studies (baseline and endline).
Setting
The study was conducted in the north-eastern region of Bangladesh under the Sylhet division, which is vulnerable to both natural disasters and poverty. The study specifically targeted children between the ages of 12 and 23 months.
Main outcome measures
Childhood stunting, defined as a length-for-age z-score <−2, was the outcome variable in this study. Logistic and probit regression models and a decision tree were constructed to predict the factors associated with childhood stunting. The predictive performance of the models was evaluated by computing the area under the receiver operating characteristic (ROC) curve analysis.
Results
The baseline survey showed a prevalence of 52.7% stunting, while 50.0% were stunted at endline. Several factors were found to be associated with childhood stunting. The model’s sensitivity was 61% and specificity was 56%, with a correctly classified rate of 59% and an area under the ROC curve of 0.615.
Conclusion
The study found that childhood stunting in the study area was correlated with several factors, including maternal nutrition and education, food insecurity and hygiene practices. Despite efforts to address these factors, they remain largely unchanged. The study suggests that a more effective approach may be developed in future to target adolescent mothers, as maternal nutrition and education are age-dependent variables. Policy makers and programme planners need to consider incorporating both nutrition-sensitive and nutrition-specific activities and enhancing collaboration in their efforts to improve the health of vulnerable rural populations.
| Original language | English |
|---|---|
| Article number | e067961 |
| Number of pages | 15 |
| Journal | BMJ Open |
| Volume | 13 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 26 Apr 2023 |
Bibliographical note
Publisher Copyright:© 2023 BMJ Publishing Group. All rights reserved.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 2 Zero Hunger
-
SDG 3 Good Health and Well-being
Research Groups and Themes
- SPS Exercise, Nutrition and Health Sciences
- SPS Health Social Care and Disability Research Centre
Keywords
- epidemiology
- nutrition
- public health
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