Quality of Anthropometric Data for Child Nutrition Monitoring in India: A Comparative Assessment Using Two Rounds of...

High-quality anthropometric data are critical for accurately monitoring child nutritional outcomes and informing policy decisions, yet inconsistencies in measurement and reporting across large-scale surveys continue to challenge data reliability.

This research assesses the quality of height-for-age (HAZ), weight-for-age (WAZ), and weight-for-height (WHZ) z-scores based on a repeated cross-sectional analysis of two rounds of the National Family Health Survey (NFHS-4, 2015-2016 and NFHS-5, 2019-2021), examining improvements, persistent gaps, and regional disparities. We have used WHO-recommended diagnostics including digit preference, age-heaping, completeness of measurements, biologically implausible values, and distributional properties of z-scores to evaluate the plausibility of anthropometric data and generate state-level rankings to compare transitions across rounds.

The results indicate modest national-level improvements in data quality in NFHS-5, particularly reductions in digit preference and implausible values; however, substantial inter-state variation remains, with some states demonstrating clear progress while others continue to exhibit measurement anomalies. The completeness of date of birth improved from 99.0% in NFHS-4 to 99.9% in NFHS-5, while completeness of anthropometric measurements declined from 98.5% to 96.6%. Digit preference for height decreased from 15.2% to 14.4%, and the proportion of biologically implausible HAZ values declined from 3.4% to 2.3%. However, the standard deviation of HAZ increased from 1.77 to 1.85 and that of WHZ from 1.40 to 1.50, indicating persistent measurement variability. Transitions in HAZ rankings further reveal mixed patterns of advancement and stagnation, with regional clustering of improvements more evident in certain parts of the country. Overall, while NFHS-5 reflects progress in anthropometric data quality, key challenges persist related to inconsistent adherence to measurement protocols, variable field performance, and inadequate supervisory oversight.

Strengthening training, standardizing procedures, and reinforcing monitoring mechanisms are essential for achieving more reliable anthropometric data, thereby enhancing the accuracy of child nutrition estimates and supporting more evidence-based policy interventions in India.