National data sets provide an avenue for students to practice data analytic skills while also answering meaningful research questions. This open education resource was developed to train future public health professionals how to conduct secondary data analysis of national health surveys using SAS statistical software. SAS software was selected because it is one of the most commonly used software programs used among public health departments and academia. The book includes details on how to analyze public-use data from five common national health surveys, including the National Health Interview Survey (NHIS), Medical Expenditure Panel Survey (MEPS), Health Information National Trends Survey (HINTS), Behavior Risk Factor Surveillance System (BRFSS) and National Health and Nutrition and Examination Survey (NHANES). All datasets and corresponding syntax files are available from the Open ICPSR Data Repository (https://doi.org/10.3886/E172301V1). Future steps are to provide databases and syntax files for other analytic software, specifically STATA.
The creation of this textbook began in March 2020. Due to COVID-19 pandemic challenges on teaching and research in higher education, final production was delayed. Chapters 1-8 were piloted during Spring 2021 and Chapters 1-6 and 9-12 were piloted in Spring 2022 to Master of Public Health students enrolled in KINE 5386 Big Data for Epidemiology. Revisions were ongoing throughout the development process. Any corrections from the Spring 2021 pilot were made prior to the Spring 2022 pilot. Efforts are underway for additional reviews to be completed by a consultant, Peace Ossom-Williamson, MLA.
About the Author
Tiffany B. Kindratt, PhD, MPH, is an assistant professor in the Public Health Program, Department of Kinesiology, College of Nursing and Health Innovation at the University of Texas at Arlington. She is Director of the Health Survey Research Laboratory and conducts research focused on predisposing (e.g. race/ethnicity, specifically Arab/Middle Eastern and North African) and enabling (e.g. patient-provider communication, patient experiences) factors that influence individuals’ health behaviors, morbidity, mortality and use of health services across the life course using big data methodologies. She has an extensive background in epidemiologic and large database analysis, Arab/Middle Eastern and North African American health disparities, and training of medical learners. She has 13 years of experience analyzing large databases and complex surveys, including those included in this book. She currently has federal research funding from the National Institutes of Health (National Institute on Aging) and Health Resources and Services Administration and has over 50 manuscripts published in peer reviewed scientific journals.