Modelling stunting in LiST: the effect of applying smoothing to linear growth data

BMC Public Health

Richard L. Guerrant¹  Zulfiqar Bhutta²  Sajid Soofi²  Simon Cousens³  Kåre Mølbak⁴  Palle Valentiner-Branth⁴  William Checkley⁵  R. Bradley Sack⁵  Jamie Perin⁵  Jean Humphrey⁵  Lee Shu-Fune Wu⁵  Neff Walker⁵  Robert H. Gilman⁵  Robert E. Black⁵  Aldo A. M. Lima⁶  Claudio Lanata⁷  Parul Christian⁸ 

[1] Center for Global Health, University of Virginia School of Medicine;Center of Excellence in Women and Child Health, the Aga Khan University;Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine;Department of Infectious Diseases Epidemiology, Statens Serum Institut;Department of International Health, Johns Hopkins Bloomberg School of Public Health;Institute of Biomedicine, Faculty of Medicine, Federal University of Ceará;Instituto de Investigación Nutricional;The Bill & Melinda Gates Foundation;

关键词: Lives saved tool;    Mixed effects modelling;    Nutritional interventions;    Stunting;   

DOI  :  10.1186/s12889-017-4744-3

来源: DOAJ

【 摘 要 】

Abstract Background The Lives Saved Tool (LiST) is a widely used resource for evidence-based decision-making regarding health program scale-up in low- and middle-income countries. LiST estimates the impact of specified changes in intervention coverage on mortality and stunting among children under 5 years of age. We aimed to improve the estimates of the parameters in LiST that determine the rate at which the effects of interventions to prevent stunting attenuate as children get older. Methods We identified datasets with serial measurements of children’s lengths or heights and used random effects models and restricted cubic splines to model the growth trajectories of children with at least six serial length/height measurements. We applied WHO growth standards to both measured and modelled (smoothed) lengths/heights to determine children’s stunting status at multiple ages (1, 6, 12, 24 months). We then calculated the odds ratios for the association of stunting at one age point with stunting at the next (“stunting-to-stunting ORs”) using both measured and smoothed data points. We ran analyses in LiST to compare the impact on intervention effect attenuation of using smoothed rather than measured stunting-to-stunting ORs. Results A total of 21,786 children with 178,786 length/height measurements between them contributed to our analysis. The odds of stunting at a given age were strongly related to whether a child is stunted at an earlier age, using both measured and smoothed lengths/heights, although the relationship was stronger for smoothed than measured lengths/heights. Using smoothed lengths/heights, we estimated that children stunted at 1 month have 45 times the odds of being stunted at 6 months, with corresponding odds ratios of 362 for the period 6 to 12 months and 175 for the period 12 to 24 months. Using the odds ratios derived from the smoothed data in LiST resulted in a somewhat slower attenuation of intervention effects over time, but substantial attenuation was still observed in the LiST outputs. For example, in Mali the effect of effectively eliminating SGA births reduced prevalence of stunting at age 59 months from 44.4% to 43.7% when using odds ratios derived from measured lengths/heights and from 44.4% to 41.9% when using odds ratios derived from smoothed lengths/heights. Conclusions Smoothing of children’s measured lengths/heights increased the strength of the association between stunting at a given age and stunting at an earlier age. Using odds ratios based on smoothed lengths/heights in LiST resulted in a small reduction in the attenuation of intervention effects with age and thus some increase in the estimated benefits, and may better reflect the true benefits of early nutritional interventions.

【 授权许可】

Unknown