2019-2020 Pilot Projects

Testing Gene-environment Interactions without Measuring the Environmental Factor

PI: Qiongshi Lu, Assistant Professor, Biostatistics & Medical Informatics
Abstract: Gene-environment interaction studies for late-life health outcomes often have limited sample sizes. While the size of genome-wide association studies (GWAS) grows rapidly for almost all complex diseases and traits, most of these studies have very limited measurements on epidemiological risk factors that are of interest in gene-environment interaction analysis. In this research, we explore the possibility of using PGS as a proxy of the epidemiological/ environmental risk factor (we refer to it as E-PGS) in gene-environment interaction analysis.

We will conduct simulations to investigate the validity of using E-PGS as a proxy for the ‘E component’ in gene-environment interaction analysis. Then we will conduct a pilot analysis focusing on three prevalent late-life diseases – coronary artery disease, stroke, and breast cancer. The Wisconsin Longitudinal Study (WLS) will be used as the primary discovery cohort, and we will replicate our findings in the Health and Retirement Study (HRS).

The main goal of the proposed work is to determine the feasibility of identifying gene-environment interactions in late-life health outcomes using E-PGS as a proxy. The successful identification of interactions would provide a strong basis for expanding our analysis to broader phenotypes.

Medicaid Expansions and Formal and Informal Care for the Elderly

PI: Yang Wang, Associate Professor, La Follette School of Public Affairs
Abstract: The Affordable Care Act has led to substantial increases in health insurance coverage for individuals in the US, and expansions in Medicaid have played a large role in the increased coverage. We explore how these changes have affected the provision and receipt of informal care, as well as changes in the demand for formal (nursing home) care for the elderly.

We will use the American Time Use Survey (ATUS) and the Health and Retirement Study (HRS). The ATUS provides nationally representative estimates of how, where, and with whom Americans spend their time. The Health and Retirement Study (HRS), focused on providing detailed information on health, health care, work, family and the aging process of Americans, will be used to measure the symmetric informal care receipt by the elderly to validate the results from the ATUS and to measure the effects of Medicaid expansions on actual nursing home use by the elderly.

WLS Digitization

PI: Jason Fletcher, Professor, La Follette School of Public Affairs and Nora Cate Schaeffer, Professor, Sociology
Abstract: The Wisconsin Longitudinal Study (WLS), which started with a state-wide survey of all 30,000 Wisconsin high school seniors in 1957, has become a premier resource for understanding how events and circumstances throughout life shape economic and health trajectories into older ages and can answer questions that no other data resource in the US can answer.  It merges deep social scientific advances with more recent biological assessments, including genetics and the microbiome.

In this project, we plan to digitize over 20,000 of the original WLS surveys from 1957.  This work will substantially expand the WLS in ways that will allow new research areas to be explored that have not been previously available.  An enhanced WLS can substantially expand our understanding of the connections between early life conditions and experiences and later life outcomes.  Having access to data on the full population of the Wisconsin Class of 1957 seniors thus allows us to contextualize the school and social environments during this time period to a degree not previously available.

The digitization effort will make possible a number of extensions to the WLS that will also expand the reach of the data.  First, the 20,000 newly digitized surveys can be linked to the 1940 Decennial Census in order to add information on early environments, such as family characteristics and geographic location (the survey respondents were born in 1939).  Second, the surveys can be linked to US Mortality records to create an additional “panel” of respondents. Third, eventually, all WLS respondents could be “PIK”ed and linked with Census data projects (e.g. 2000 Decennial Census) inside an FSRDC.

Understanding the long-term relationship between Community Health and Voter Turnout in the Midwest

PI: Michal Engelman, Associate Professor, Sociology
Abstract:Reports of declining life expectancy and rising economic and social anxieties among white Americans (particularly those living outside of major metropolitan areas) captured both popular and scholarly attention in the lead-up to and aftermath of the 2016 election. In attempting to explain the Republican candidate’s victory in a state that had favored Democratic presidential candidates since 1988, early reports stated that white voters – and particularly older, white, working-class voters – were responsible for flipping Wisconsin from blue to red. Subsequent analysis has shown that the story is considerably more complicated, encompassing low voting rates among African Americans (due to unenthusiastic turnout as well as voter ID policies that created barriers for interested voters) and higher-than-predicted support for Trump among white voters of varied socioeconomic backgrounds.

In this study, we will create a unique linkage between the rich sociodemographic and health data available in the Wisconsin Longitudinal Study (WLS), State Voter Files up to 2019, and aggregate data on population health and economic well-being in order to understand voting patterns among older, largely white adults who grew up in Wisconsin. This study will allow us to identify individual and community level predictors of voting patterns, marshaling longitudinal data to assess the extent to which the 2016 election represented continuity with or a break from prior elections. Our aim in creating this linked data set is to enrich the resources available for future research focused on the interaction of socio-demographic and health characteristics with political participation.