Biological Risk Profiles in the Elderly Mexican Population at the Turn of the 21st Century
PI: Hiram Beltrán-Sánchez, research scientist, CDHA and sociology
Abstract: The main goal of this study is to examine the association between socioeconomic factors associate and biological indicators of health within the elderly Mexican population. We expect differences in the physiological profile of the Mexican population to vary by age, gender, education, and rural residence. We also conjecture that older persons will have experienced suboptimal development as evidenced by their being shorter in total height and having more stunting resulting from worse levels of infection and nutrition while growing up. Due to likely increases in over-nutrition across all ages due to recent changes in nutrition we also expect differences in the cardiovascular and lipid profiles by age with a larger number of high-risk factors among the old. We will use data from all three waves of MHAS, the Mexican Health and Aging Survey. The third wave includes clinically relevant health indicators estimated from blood samples which were collected on fasting individuals We will study four sets of indicators representing physiological dysregulation: a) physical development and nutrition; b) indicators of metabolic dysregulation; c) indicators of cardiovascular dysregulation; and d) a summary risk indicator.
Identification of Gene Environment Interactions in Cognitive Decline
PI: Corinne Engelman, assistant professor, population health sciences
Abstract: The specific aim of this proposal is to use random forest, a machine learning approach that has worked particularly well in our past research, to identify potential interactions between social and behavioral factors, biomarkers, and genetic variants influencing cognitive decline in the WRAP cohort. We hypothesize that interactions in three main pathways will influence cognitive decline:
(a) Cholesterol metabolism: interaction between physical activity, obesity, lipids, and the cholesterol metabolism genes. (b) Insulin resistance: interaction between physical activity, obesity, HOMA (a blood measure of insulin resistance), and genetic variants in type 2 diabetes-related genes. (c) Inflammation: interaction between social activity, social support, stress, inflammatory biomarkers, and genetic variants related to immune system function.
The data for this project comes from the Wisconsin Registry of Alzheimer’s Prevention (WRAP), one of the few studies in the world that is focusing on this preclinical phase in middle-aged adults enriched for parental history of AD. WRAP is a longitudinal study with detailed information on socio-demographic and behavioral factors, biomarkers, and genetic variants.
This rich dataset is especially important because, as of yet, the only well-established risk factors for AD are increasing age, lower education, family history of AD, the APOE 4 allele, most of which are not modifiable. Nine additional genes of very small effect have recently been confirmed and additional suspected factors include cardiovascular disease risk factors (e.g., high cholesterol and hypertension in midlife and diabetes) and social and cognitive engagement [Alzheimer’s Association].
Genotype-phenotype Associations and Genetic Risk of Aging: Health, Reproductive, Mental Health and Cognitive Phenotypes
PI: Marsha Mailick, director, Waisman Center
Abstract: The proposed project will use WLS genetic biomarkers to provide an unbiased assessment of the phenotype of the “premutation” condition of the disorder known as Fragile X-Associated Disorder (FXS), an inherited form of intellectual disability that results from large expansions of a trinucleotide (CGG) repeat in the 5 unstranslated region of the FMR1 gene. This is a highly prevalent but undiagnosed condition. The goal of this new project is to conduct a deep phenotyping analysis to ascertain whether clinical observations of the symptoms associated with the permutation are in fact evident in an unbiased population sample. We will study the physical, reproductive and mental health as well as cognitive phenotypes associated with gray zone and permutation alleles in WLS respondents and determine whether or not the CGG repeat pattern influences the effects of stressful life events on the physical and mental health and cognitive functioning of respondents.
Political Participation of Older Americans: the Role of Social and Genetic Factors
PIs: Donald Moynihan, professor, La Follette School of Public Affairs
Barry Burden, professor, political science
Jason Fletcher, associate professor, La Follette School of Public Affairs
Abstract: We propose to identify how three factors (genetics, personality, and health) each affect the political participation of older Americans. We plan to pursue these questions by using an expanded version of the Wisconsin Longitudinal Survey. The survey already includes self-reported items on voting, plus other variables we hope to explore, including measures of health, political ideology, personality, socioeconomic status, biomarkers, and other important contextual predictors of voting. We plan to draw on three additional sources that will offer a more reliable and comprehensive account of the political participation of older Americans. First, we will add in individual registration and voting histories for approximately the last 10 years. This will be provided by a private firm that collects such data from state records. Second, we will add campaign contribution data from the state of Wisconsin and the federal government. These public files report on campaign contributions made to candidates, parties, and groups in recent election cycles. Third, we will add a list of Wisconsin residents who signed petitions to recall the governor in 2011. This public document records the name, address, and signing date for each person who added their name to the recall petition.
The Impact of the Economic Recession on the Health and Wellbeing of Elderly Adults
PIs: F. Javier Nieto, chair, population health sciences
Alberto Palloni, Samuel Preston Professor, sociology
Abstract: This proposal leverages resources from the Survey of the Health of Wisconsin (SHOW), established in 2008 by a University of Wisconsin endowment as a statewide geographically-linked examination survey and biorepository. With funding from an NHLBI Grand Opportunities (RC2) grant, the Network for Health Equity in Wisconsin (NHEW) was established, linking SHOW with contextual data on the social, built-in, and health care environments, while developing strong partnerships with community organizations engaged in multi-modal health improvement initiatives. We propose to use the entire cross-sectional data set collected from 2008 to 2011 (N~2479) plus the (new, not yet released) data corresponding to 2012 to assess the effects of the economic recession on older adults’ behaviors and health markers, health care behaviors, residential patterns, and intra-family transfers as well as on the differential impacts by race and migration status. The two main goal of the pilot project are:
- To assess the effects that drastic shifts in economic conditions induced by the 2008 economic recession influence markers and determinants of health status, including self-reported health and conditions; indicators of mental health and cognitive impairment, body mass and biomarkers including cortisol levels, blood pressure, CRP and other markers of inflammation; and, finally, mortality.
- To estimate the degree to which the magnitude of the influence of the recession varies across social groups, particularly among disadvantaged groups, including low income, ethnic minorities and immigrants.
In particular we will focus on the following health outcomes: self-reported health, self-reported conditions (from health histories including CVD, diabetes, stroke), cognitive function and depression, dental health, sleep habits and sleep problems, respiratory function, blood pressure, obesity and weight gain (loss). In addition we will examine behaviors such as physical activity, diet, smoking and alcohol consumption prevention and prevention and safety habits. Finally, we will investigate adherence to treatment and preventative behaviors.