Iliana Kohler, PhD, is a health researcher and social demographer whose research builds on both social and biomedical sciences, and whose primary research agenda focuses on adult health outcomes, chronic diseases, intergenerational relationships and transfers, and morbidity and mortality in international contexts. She has collaborated extensively in multidisciplinary and international research teams, and has demonstrated leadership in coalescing research teams around new research ideas and innovative projects in population health. Most recently, Dr. Kohler spearheaded the extension of the Malawi Longitudinal Study of Families and Health (MLSFH), towards research on aging, chronic diseases, and mortality in an African high HIV-prevalence context, and established the Mature Adults Cohort of MLSFH (MLSFH-MAC) in 2012.
Dr. Kohler led the development of the MLSFH-MAC research agenda on aging, the development and pre-testing of the aging-related study instruments, and the implementation of all past and the upcoming 2020 MLSFH-MAC data collections. She has also been instrumental in the development of comparable survey instruments that allow the creation of a comparative health research agenda between MLSFH-MAC, HRS, SHARE, focused on chronic diseases and mortality between low-income and high-income countries. In her past role as Associate Director of Penn’s Population Aging Research Center (PARC), she helped initiate an international research network within PARC on “Aging in Sub-Saharan Africa,” in an effort to facilitate innovative aging-related population research in sub-Saharan Africa, and identify and make important contributions at a new challenging frontier of population science.
Dr. Kohler recently served as the lead international consultant for the United Nations DESA project data collection methodology and tools for supporting the formulation of evidence-based policies in response to the challenge of population aging in sub-Saharan Africa. She also has extensive experience working with and analyzing large observational datasets with a focus on survival outcomes.
