Composite anthropometric data quality index for children under the age of 5 on the Brazilian National Food and Nutrition Surveillance System, 2019-2021.

Background: A composite evaluation that merges various data quality indicators separately enabled the researchers to score the overall data quality of the research. In this context, the objective of the present study is to develop composite anthropometric data quality indices for children under 5 registered on the Brazilian National Food and Nutrition Surveillance System (SISVAN) from 2019 to 2021.

Methods: Anthropometric data quality indicators were generated for 5,210 Brazilian municipalities: coverage, completeness, the ratio between the sexes, age difference index, preference for height and weight digits, biologically implausible z-score values, and standard deviation. Principal component analysis [PCA] was used to generate a composite anthropometric data quality index for standardized height-for-age (HAZ) and weight-for-height z score (WHZ) indices. The municipalities were ranked in descending order, following their anthropometric quality index values: lowest [worst quality] and highest values [best quality].

Results: In total, 29,367,435 records and 8,930,881 children with anthropometric measurement information were identified. The dispersion indicators, the percentage of biologically implausible values [BIV] and the digit preference had the highest factor loadings. We observed that the worst index values were found in municipalities in the country's poorest and most vulnerable regions [North, Northeast, and Central-West]. The correlation between the HAZ and WHZ quality indices was 0.74.

Conclusion: The proposed index provides a coherent measurement to discriminate municipal anthropometric data quality.