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Decoding India's Child Malnutrition Puzzle: A Multivariable Analysis Using a Composite Index
Gulzar Shah1, Maryam Siddiqa2, Padmini Shankar3
1Department of Health Policy and Community Health, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, GA 30460, USA.
Insights
Child malnutrition in India affects over half of children under five. Factors like birth order, maternal health, and socioeconomic status significantly predict nutritional outcomes, requiring comprehensive public health interventions.
Area of Science:
- Public Health
- Pediatrics
- Nutritional Epidemiology
Background:
- Child malnutrition is a persistent public health challenge in India.
- Understanding the determinants of malnutrition is crucial for effective intervention strategies.
Purpose of the Study:
- To investigate the prevalence and identify predictors of malnutrition in Indian children under five years of age.
- To inform public health policies and interventions aimed at improving child nutrition.
Main Methods:
- Utilized data from the India National Family Health Survey (2019-2021).
- Applied the Composite Index of Anthropometric Failure to assess malnutrition.
- Employed multivariable logistic regression to identify significant predictors.
Main Results:
- Over 52% of children experienced anthropometric failure.
- Female gender, larger birth size, higher maternal education, and better socioeconomic status were associated with lower malnutrition risk.
- Higher birth order, severe maternal anemia, and specific religious affiliations were linked to increased malnutrition risk.
Conclusions:
- Child malnutrition remains a critical issue in India, demanding integrated efforts from public and private sectors.
- A 'Health in All Policies' approach is recommended to address factors influencing children's nutritional status.
Background:
This study examines the levels and predictors of malnutrition in Indian children under 5 years of age.
Methods:
Composite Index of Anthropometric Failure was applied to data from the India National Family Health Survey 2019-2021. A multivariable logistic regression model was used to assess the predictors.
Results:
52.59% of children experienced anthropometric failure. Child predictors of lower malnutrition risk included female gender (adjusted odds ratio (AOR) = 0.881) and average or large size at birth (AOR = 0.729 and 0.715, respectively, compared to small size). Higher birth order increased malnutrition odds (2nd-4th: AOR = 1.211; 5th or higher: AOR = 1.449) compared to firstborn. Maternal predictors of lower malnutrition risk included age 20-34 years (AOR = 0.806), age 35-49 years (AOR = 0.714) compared to 15-19 years, normal BMI (AOR = 0.752), overweight and obese BMI (AOR = 0.504) compared to underweight, and secondary or higher education vs. no education (AOR = 0.865). Maternal predictors of higher malnutrition risk included severe anemia vs. no anemia (AOR = 1.232). Protective socioeconomic factors included middle (AOR = 0.903) and rich wealth index (AOR = 0.717) compared to poor, and toilet access (AOR = 0.803). Children's malnutrition risk also declined with paternal education (primary: AOR = 0.901; secondary or higher: AOR = 0.822) vs. no education. Conversely, malnutrition risk increased with Hindu (AOR = 1.258) or Islam religion (AOR = 1.369) vs. other religions.
Conclusions:
Child malnutrition remains a critical issue in India, necessitating concerted efforts from both private and public sectors. A 'Health in All Policies' approach should guide public health leadership in influencing policies that impact children's nutritional status.
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