Undernutrition is responsible for nearly half of all global deaths in children under 5 years old. The prevalence of chronic child undernutrition (stunting) at the global level stands at approximately 22%, with the highest prevalence regions being in sub-Saharan Africa and South Asia.

This project explores several multilevel approaches (e.g. spatial statistics, machine learning) to identify significant socioeconomic, demographic, cultural, climatic and environmental risk factors of child stunting from Demographic and Health Survey (DHS) datasets.

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Project Leadership

Parker VanValkenburgh, Ph.D. – Director

Assistant Professor of Anthropology, Brown University

Researchers at Brown page – https://vivo.brown.edu/display/pvanvalk

Academia.edu page - https://brown.academia.edu/ParkerVanValkenburgh

Lic. Daniela Zevallos Castañeda – Co-Director, 2015-16 Field Seasons

Independent Scholar

Links to publications

Kelloway, Sarah J., VanValkenburgh, Parker, Iñañez, Javier G., Dussubieux, Laure, Quilter, Jeffrey, Glascock, Michael D. Identifying New World majolica from 16th–18th Century sites on Peru's north coast. Journal of Archaeological Science: Reports/Journal of Archaeological Science: Reports. 2018; 17 : 311-324. 
https://doi.org/10.1016/j.jasrep.2017.10.008

(Click to check the large size image.)

The PAZC's archaeological survey registered a significant reduction in the number of sites and total settled area in the lower Zaña valley following 1570 CE.

Project Description

Measurements of economic growth often fall short for developing countries, particularly in sub-Saharan Africa, and are rarely calculated at all for cities throughout the world. In a new working paper, three Brown University economists suggest a way to improve GDP estimates for such areas by using images of nighttime lights as seen from outer space.

The Longitudinal Tract Data Base estimates population characteristics for constant small areas from 1970 through 2010, based on census tract boundaries in 2010.  These data can also be viewed in a web-based map or downloaded.