June 26, 2023 | Erin Bluvas, [email protected]
The UNICEF, WHO, and World Bank Group have released the 2023 edition of the Joint Child Malnutrition Estimates, with special thanks to two USC faculty members. Alexander McLain, associate professor of biostatistics, and Edward Frongillo, professor of health promotion, education, and behavior, were acknowledged for their role in developing the analytic methods used for estimating overweight and stunting trends among children around the world.
“Global rates of childhood stunting, which is a result of chronic malnutrition and inequality, are still unacceptably high, and childhood overweight and obesity is increasingly common,” says Frongillo, a renowned expert in global nutrition, particularly childhood malnutrition in low- and middle-income countries. “It’s important to monitor countries’ progress toward achieving nutrition targets, such as reduction in stunting, but lack of data and incomplete data make monitoring trends challenging.”
Global rates of childhood stunting, which is a result of chronic malnutrition and inequality, are still unacceptably high, and childhood overweight and obesity is increasingly common.
Established in 2011 as a coordinated effort to measure the progress in ending child
malnutrition, the Joint Malnutrition Estimates Working Group released their first
report in 2012. Since then, they have steadily enhanced their data and methods alongside
the advancements that have taken place in the scientific community.
McLain and Frongillo’s collaborations with scientists from UNICEF, WHO and the World Bank resulted in their publication of a new method for estimating childhood stunting and overweight trends in the European region. The method solved a long-term challenge faced by scientists in estimating malnutrition trends in areas where there is a sparsity of data available for analysis.
Data sparsity is a common challenge in nutritional epidemiology and public health. But new developments in statistical methods now allow us to gain valuable insights by extracting useful information from longitudinal data.
“Data sparsity is a common challenge in nutritional epidemiology and public health,” says McLain, who specializes in solving methodological challenges (e.g., missing data) and led the development of the new methods employed to estimate stunting/overweight trends. “But new developments in statistical methods now allow us to gain valuable insights by extracting useful information from longitudinal data.”
These methods help complete the picture of malnutrition, enabling an improved version of this year’s report. The information contained in the report (see box below for an example) helps inform efforts by public health professionals, humanitarians, and policy makers in reversing childhood malnutrition trends.
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