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Background <p>To estimate the burden of developmental delay and identify its correlates among children aged 6–59 months with severe acute malnutrition (SAM), using the Trivandrum Developmental Screening Chart (TDSC) in a hospital setting.</p> Methods <p>This hospital-based cross-sectional analytical study was conducted over 15-months (October 2024–December 2025) at our center in northern India, and enrolled consecutive children aged 6–59 months with SAM defined by WHO criteria. Socio-demographic, perinatal and anthropometric data were collected, TDSC was administered to classify screen-positive developmental delay and count delayed milestones, and data were analyzed using modified Poisson regression with robust standard errors for prevalence ratios and negative binomial regression for incidence rate ratios, adjusting for relevant covariates.</p> Results <p>Of 356 eligible children with SAM, 312 were enrolled (median age 24 months), predominantly female (51.9%), rural (73.1%) and from lower or lower-middle socioeconomic strata. Overall, 204 children (65.4%) screened positive for developmental delay on TDSC; in adjusted models, kaccha-housing (adjusted prevalence ratio (aPR) 1.553, 95%CI 1.283–1.879), maternal illiteracy (aPR 1.447, 95%CI 1.172–1.785), lower weight-for-height z-score (aPR 0.955, 95%CI 0.921–0.991) and lower mid-upper arm circumference (aPR 0.921, 95%CI 0.855–0.992) were independently associated with the presence of delay, while lower height-for-age and lower mid-upper arm circumference predicted a higher number of delayed milestones in negative binomial models.</p> Conclusion <p>Children with SAM have a high burden of developmental delay, closely linked to both anthropometric deficits and adverse socio-environmental conditions, underscoring the need to integrate routine developmental screening and combined nutrition–caregiver support interventions into SAM management pathways in low-resource settings.</p>

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Burden and correlates of developmental delay in severe acute malnutrition: a hospital-based cross- sectional study using TDSC screening and count modeling of delayed milestones

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  • 发表日期：

    2026年7月28日

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  • Shivani Anil Chavan,
  • Rufaida Mazahir,
  • Ajay Patwardhan

摘要

Background

To estimate the burden of developmental delay and identify its correlates among children aged 6–59 months with severe acute malnutrition (SAM), using the Trivandrum Developmental Screening Chart (TDSC) in a hospital setting.

Methods

This hospital-based cross-sectional analytical study was conducted over 15-months (October 2024–December 2025) at our center in northern India, and enrolled consecutive children aged 6–59 months with SAM defined by WHO criteria. Socio-demographic, perinatal and anthropometric data were collected, TDSC was administered to classify screen-positive developmental delay and count delayed milestones, and data were analyzed using modified Poisson regression with robust standard errors for prevalence ratios and negative binomial regression for incidence rate ratios, adjusting for relevant covariates.

Results

Of 356 eligible children with SAM, 312 were enrolled (median age 24 months), predominantly female (51.9%), rural (73.1%) and from lower or lower-middle socioeconomic strata. Overall, 204 children (65.4%) screened positive for developmental delay on TDSC; in adjusted models, kaccha-housing (adjusted prevalence ratio (aPR) 1.553, 95%CI 1.283–1.879), maternal illiteracy (aPR 1.447, 95%CI 1.172–1.785), lower weight-for-height z-score (aPR 0.955, 95%CI 0.921–0.991) and lower mid-upper arm circumference (aPR 0.921, 95%CI 0.855–0.992) were independently associated with the presence of delay, while lower height-for-age and lower mid-upper arm circumference predicted a higher number of delayed milestones in negative binomial models.

Conclusion

Children with SAM have a high burden of developmental delay, closely linked to both anthropometric deficits and adverse socio-environmental conditions, underscoring the need to integrate routine developmental screening and combined nutrition–caregiver support interventions into SAM management pathways in low-resource settings.