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The Stunting Tool for Early Prevention: development and external validation of a novel tool to predict risk of stunting in children at 3 years of age
  1. Sarah Hanieh1,
  2. Sabine Braat2,
  3. Julie A Simpson2,
  4. Tran Thi Thu Ha3,
  5. Thach D Tran3,4,
  6. Tran Tuan3,
  7. Jane Fisher4,
  8. Beverley-Ann Biggs1,5
  1. 1Medicine at the Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, Victoria, Australia
  2. 2Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
  3. 3Research and Training Centre for Community Development, Hanoi, Vietnam
  4. 4School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
  5. 5The Victorian Infectious Diseases Service, Royal Melbourne Hospital, Melbourne, Victoria, Australia
  1. Correspondence to Dr Sarah Hanieh; shanieh{at}


Introduction Globally, an estimated 151 million children under 5 years of age still suffer from the adverse effects of stunting. We sought to develop and externally validate an early life predictive model that could be applied in infancy to accurately predict risk of stunting in preschool children.

Methods We conducted two separate prospective cohort studies in Vietnam that intensively monitored children from early pregnancy until 3 years of age. They included 1168 and 475 live-born infants for model development and validation, respectively. Logistic regression on child stunting at 3 years of age was performed for model development, and the predicted probabilities for stunting were used to evaluate the performance of this model in the validation data set.

Results Stunting prevalence was 16.9% (172 of 1015) in the development data set and 16.4% (70 of 426) in the validation data set. Key predictors included in the final model were paternal and maternal height, maternal weekly weight gain during pregnancy, infant sex, gestational age at birth, and infant weight and length at 6 months of age. The area under the receiver operating characteristic curve in the validation data set was 0.85 (95% Confidence Interval, 0.80–0.90).

Conclusion This tool applied to infants at 6 months of age provided valid prediction of risk of stunting at 3 years of age using a readily available set of parental and infant measures. Further research is required to examine the impact of preventive measures introduced at 6 months of age on those identified as being at risk of growth faltering at 3 years of age.

  • Stunting
  • child health
  • prevention strategies

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  • Handling editor Seye Abimbola

  • SH and SB contributed equally.

  • Contributors SH and SB analysed the data, prepared the results, and wrote the first and subsequent drafts of the manuscript. SH, SB, JAS, JF, TDT and B-AB designed the study. SB managed the data set and performed the statistical analysis. TDT, TTTH, JF and JAS contributed to the study and survey design, and reviewed and commented on the drafts of the report. TTTH facilitated the conduct of the survey at the commune health stations. All authors approved the final submitted version of the manuscript.

  • Funding The study was funded by a grant from the Australian National Health and Medical Research Council (NHMRC) (Grant Number 1041988). SH is funded by an NHMRC Early Career Fellowship 1112581. JAS is funded by an NHMRC Senior Research Fellowship 1104975. B-AB was partly supported by NHMRC project grant 1131932 (the HOT NORTH initiative). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Ethics approval The original study protocol was approved by the Melbourne Health Human Research Ethics Committee and the Ha Nam Provincial Human Research Ethics Committee. The cluster randomised trial is registered in the Australia New Zealand Clinical Trials Registry: 12610000944033.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement No data are available.

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