Peer-reviewed article
Stunting incidence and reversal as metrics of postnatal linear growth faltering in low- and middle-income countries: a critical appraisal and simulation study.
Daniel E Roth, Kelly M Watson, Diego G Bassani ·
Summary
Written by AI, not yet AICS's view · claude-haiku-4-5-20251001This study critically examines how stunting incidence and reversal are measured in children under 2 years old in low- and middle-income countries. Using computer simulations based on data from South Asian cohorts, the researchers found that stunting reversal often occurs simply due to natural measurement variation, not because children actually improve. The study recommends that researchers use 'growth delay' as a better metric than stunting prevalence or incident stunting to understand why children grow slower than expected.
Key points
- Stunting reversal commonly occurs due to within-child measurement variability rather than actual improvement in nutrition or health
- Incident stunting onset and reversal rates are byproducts of whole-population shifts in length-for-age z-scores and measurement variability
- Mean length-for-age z-score and stunting prevalence do not capture the rate and timing of population-level linear growth faltering
- Growth delay (chronological age minus height-age) is recommended as a preferred metric over stunting threshold-crossing events
- Empirical estimates from longitudinal cohorts matched predictions from synthetic simulations with identical growth patterns across the population
Limitations
This is a methodological paper using simulations rather than clinical or intervention data, so it does not measure actual child outcomes or test solutions to stunting. It focuses on measurement approaches for South Asian cohorts and may not apply equally to all low- and middle-income country contexts.
Abstract
OBJECTIVES: Length-for-age z-scores (LAZ) and stunting prevalence (%LAZ <-2) are commonly used to quantify linear growth faltering in young children in low- and middle-income countries (LMICs). The Healthy Birth, Growth and Development knowledge integration (HBGDki) consortium described postnatal linear growth faltering using LAZ-by-age trajectory modelling and child-level LAZ threshold-crossing events, including incident stunting onset (first occurrence of LAZ <-2) and stunting reversal (LAZ rising from <-2 to ≥-2). Using simulations, we assessed the suitability of these LAZ threshold-crossing metrics for characterising linear growth faltering in LMICs. METHODS: We simulated a synthetic cohort with a harmonically downward-shifting LAZ trajectory from birth to 24 months of age, with mean LAZs similar to the HBGDki pooled South Asian cohorts, and without any input parameters intended to differentially affect individuals' growth across the height distribution or at different ages. We compared HBGDki empirical estimates of age interval-specific frequencies of incident stunting onset and stunting reversal with those from the synthetic cohort. Using synthetic cohorts, we examined how estimates of incident onset and reversal were affected by missing data, magnitude of the whole-population shift in the LAZ distribution and strength of the between-time-point correlation. We also compared the 3-24 month pattern of linear growth faltering expressed as age-related trajectories of average growth delay (chronological age minus height-age), mean LAZ or stunting prevalence. RESULTS: Empirical estimates of age interval-specific incident stunting onset and stunting reversal in the HBGDki cohorts were similar to those observed in a synthetic cohort. Variability in LAZ threshold-crossing event rates is explained by starting LAZ, between-time-point correlation and the magnitude of the whole-population shift in the LAZ distribution. Incident stunting onset is also affected by missing data in preceding intervals. Stunting reversal occurs due to within-child variability (ie, imperfect between-time-point correlation) in the absence of any other phenomena that cause stunted children to become non-stunted at a later age. The linear growth faltering pattern based on growth delay differed from corresponding age-related trajectories of mean LAZ or stunting prevalence. CONCLUSIONS: In longitudinal studies of linear growth faltering in LMICs, LAZ threshold-crossing indicators are byproducts of whole-population shifts in LAZ and within-child variability and should be interpreted accordingly. Reporting incident stunting onset and reversal rates, or analyses in which children are grouped by the timing of LAZ threshold-crossing events, may detract from efforts to understand when and why nearly all children in LMICs grow more slowly than expected for their age. Since mean LAZ and stunting prevalence are unsuitable for quantifying the rate and timing of population-average postnatal linear growth faltering, growth delay is recommended for consideration as a preferred metric.