Using MEPS to Study Maternal and Child Health
Fellows will work with Dr. Julia Drew, Dr. Susan Mason, and Dr. Susan Short to explore the suitability of using longitudinal data from the Medical Expenditure Panel Survey-Household Component (MEPS-HC), for three maternal and child health topics. Specifically, we will assess whether the MEPS-HC data can be used to study 1) preconception, prenatal, and postpartum maternal mental health; 2) patterns of utilization by during the preconception, prenatal, and postpartum periods; and 3) childhood injuries. Fellows will undertake several foundational activities necessary including the evaluation of sample sizes and benchmarking estimates derived from the MEPS-HC data against estimates from other sources. Also Fellows will conduct a systematic literature reviews will conduct preliminary descriptive analyses.
Zoning Atlas: Examining residential segregation in Minneapolis and St. Paul
Fellows will work with Dr. Evan Roberts, Dr. Ying Song and Kate Knowles to learn about data construction, integration and cleaning, and data analysis to finalize a “Zoning Atlas” for the Twin Cities. Fellows will integrate the zoning atlas GIS layers with block-level data on residential racial segregation and analyze how racial segregation in the Twin Cities is associated with local government restrictions and regulations of housing density. Using the block-level the fellows will examine how changing racial composition affects zoning. A key outcome of the project will be the completion of a detailed zoning atlas that describes the restrictions on housing development in the metropolitan area.
Social Determinants of Health: comparing clinical and publicly available data.
Fellows will work with Dr. Rui Zhang and Dr. David Haynes to learn about clinical and publicly available data that quantifies and measures social determinants of health. There has been an increased focus on understanding the Social Determinants of Health (SDoH), defined as the social and economic conditions outside of the medical domain. SDoH information in the EHR can be stored in both structured (e.g., education and salary level) and unstructured formats (e.g., social history in clinical notes). Since there is no standardized framework for recording SDoH information and such information Fellows will compare clinical and public available sources to help determine which resources health care systems need to use so they supplement this valuable information to address their patient needs.
Exploration of Newly-Public 1950 Census American Indian Reservation Data
The 1950 Census will be released in April 2022, opening new possibilities for social science and health research. In this project, fellows will work with Dr. Cathy Fitch, Dr. Carolyn Liebler, and Kari Williams to investigate a special questionnaire from the 1950 Census that was administered on Indian Reservations. These data are meaningful (but not readily accessible) to tribes and Indigenous people and will be a powerful source for understanding the diversity of Native experiences once linked to other data sources. Fellows will collaborate on tasks such as investigating options for future data transcription and understanding data quality of the 1950 Indian Reservation data; analyzing existing data sources on the people, families, households, and tribes enumerated in the 1950 census; and initiating the outreach component of the project to inform future project developments.
Malaria Transmission in Context: Using International Census Data
Fellows will work with Dr. Kelly Searle and Dr. Tracy Kugler to explore the use of population, ecological, and agricultural data to provide contextual information for studying spatial patterns in vector-borne disease transmission. Fellows will assemble, prepare, and analyze census data tables and ecological data for research projects investigating malaria transmission dynamics and implications for control and elimination strategies. Census data prepared for the research projects will be made publicly available via IPUMS International Historical Geographic Information System (IHGIS). Fellows will also identify additional sources of census data for incorporation into IHGIS, focusing on data that can be linked to datasets in IPUMS Global Health projects.