Rationing Rights: Administrative Burden in Medicaid Long-term Care Programs.

CONTEXT: States use Medicaid waivers to provide supports for disabled people in communities, rather than in institutions. Because waivers are not entitlements, those deemed eligible are not guaranteed these supports. How do states, in practice, use bureaucratic procedures to ration this 'conditional' right? METHODS: Drawing on primary and secondary data, we analyze waiver programs, and document state administrative procedures to indirectly and directly ration access. FINDINGS: Burdens indirectly limit disabled peoples' access to Medicaid home and community-based services, via a complex array of waiver programs that exacerbate costs associated with gaining eligibility, and directly limit access, via waitlists and prioritization among the eligible. There is also evidence that states strategically deploy opaqueness to provide political cover for unpopular waitlists. The overall process is opaque, confusing, and time intensive, with burdens falling hardest on marginalized groups. CONCLUSIONS: Administrative burdens impede the right to live in the community afforded to people with disabilities under the American with Disabilities Act. The opaqueness and associated burdens with waiver programs are a way to conceal these costs, thereby demonstrating how burdens "neatly carry out the 'how' in the production of inequality, while concealing . . . the why."

Improving Older Adults' Health by Reducing Administrative Burden.

Policy Points Administrative burdens, which are the onerous experiences people have when trying to access government benefits and services, reduce older adult's access to health promoting policies. Although considerable attention has been focused on threats to the old-age welfare state, ranging from long-term financing problems to attempts to roll back benefits, administrative barriers to these programs already threaten their effectiveness. Reducing administrative burden is a viable way to improve population health among older adults going forward over the next decade.

Genetic analysis of social-class mobility in five longitudinal studies.

A summary genetic measure, called a "polygenic score," derived from a genome-wide association study (GWAS) of education can modestly predict a person's educational and economic success. This prediction could signal a biological mechanism: Education-linked genetics could encode characteristics that help people get ahead in life. Alternatively, prediction could reflect social history: People from well-off families might stay well-off for social reasons, and these families might also look alike genetically. A key test to distinguish biological mechanism from social history is if people with higher education polygenic scores tend to climb the social ladder beyond their parents' position. Upward mobility would indicate education-linked genetics encodes characteristics that foster success. We tested if education-linked polygenic scores predicted social mobility in >20,000 individuals in five longitudinal studies in the United States, Britain, and New Zealand. Participants with higher polygenic scores achieved more education and career success and accumulated more wealth. However, they also tended to come from better-off families. In the key test, participants with higher polygenic scores tended to be upwardly mobile compared with their parents. Moreover, in sibling-difference analysis, the sibling with the higher polygenic score was more upwardly mobile. Thus, education GWAS discoveries are not mere correlates of privilege; they influence social mobility within a life. Additional analyses revealed that a mother's polygenic score predicted her child's attainment over and above the child's own polygenic score, suggesting parents' genetics can also affect their children's attainment through environmental pathways. Education GWAS discoveries affect socioeconomic attainment through influence on individuals' family-of-origin environments and their social mobility.

Sick Individuals and Sick (Microbial) Populations: Challenges in Epidemiology and the Microbiome.

The human microbiome represents a new frontier in understanding the biology of human health. While epidemiology in this area is still in its infancy, its scope will likely expand dramatically over the coming years. To rise to the challenge, we argue that epidemiology should capitalize on its population perspective as a critical complement to molecular microbiome research, allowing for the illumination of contextual mechanisms that may vary more across populations rather than among individuals. We first briefly review current research on social context and the gut microbiome, focusing specifically on socioeconomic status (SES) and race/ethnicity. Next, we reflect on the current state of microbiome epidemiology through the lens of one specific area, the association of the gut microbiome and metabolic disorders. We identify key methodological shortcomings of current epidemiological research in this area, including extensive selection bias, the use of noncompositionally robust measures, and a lack of attention to social factors as confounders or effect modifiers.

The Influence of Men's Military Service on Smoking Across the Life Course.

The military is described as a social context that contributes to the (re-)initiation or intensification of cigarette smoking. We draw on data from the 1985-2014 National Survey of Drug Use and Health (NSDUH) and the Wisconsin Longitudinal Study (WLS) to conduct complementary sub-studies of the influence of military service on men's smoking outcomes across the life course. Descriptive findings from an age-period-cohort analysis of NSDUH data document higher probabilities of current smoking and heavy smoking among veteran men across a broad range of cohorts and at all observed ages. Findings from sibling fixed-effects Poisson models estimated on the WLS data document longer durations of smoking among men who served in the military and no evidence that selection explains the observed relationship. Together, these results provide novel and potentially generalizable evidence that participation in the military in early adulthood exerts a causal influence on smoking across the life course.

The Implications of Unintended Pregnancies for Mental Health in Later Life.

Despite decades of research on unintended pregnancies, we know little about the health implications for the women who experience them. Moreover, no study has examined the implications for women whose pregnancies occurred before Roe v. Wade was decided--nor whether the mental health consequences of these unintended pregnancies continue into later life. Using the Wisconsin Longitudinal Study, a 60-year ongoing survey, we examined associations between unwanted and mistimed pregnancies and mental health in later life, controlling for factors such as early life socioeconomic conditions, adolescent IQ, and personality. We found that in this cohort of mostly married and White women, who completed their pregnancies before the legalization of abortion, unwanted pregnancies were strongly associated with poorer mental health outcomes in later life.

Underestimating the Relationship: Unpacking Both Socioeconomic Resources and Cognitive Function and Decline in Midlife to Later Life.

Although there is robust evidence that socioeconomic position influences later-life cognitive function, two issues limit knowledge regarding the nature and magnitude of these relationships and potential policy interventions. First, most social science research tends to treat cognition as a unitary concept despite evidence that cognitive outcomes are not interchangeable. Second, most biomedical research focuses exclusively on education, with limited attention to economic resources despite robust social science theoretical and empirical rationales for their role. Relatedly, there has been limited attention to how these relationships may vary across cohorts, even as educational and economic contexts have changed. Using the Health and Retirement Study (N = 36,494), we show that failing to attend to different facets of cognition, socioeconomic resources, and cohort differences leads to underestimates in the magnitude of educational and economic disparities in cognitive function and decline. This has important implications for appropriate policy interventions to address these disparities.

Hearing from parents: the impact of receiving the diagnosis of Williams syndrome in their child.

Healthcare providers often share difficult or life-altering news with their patients yet this challenging and delicate process is frequently met with dissatisfaction by those receiving this news. Articles and guidelines exist to aid providers in sharing diagnoses such as Down syndrome, but relatively few have focused on rare genetic conditions often diagnosed years after birth. For this reason, we sought to learn about the experience of receiving a diagnosis from parents of children with Williams syndrome. We asked members of the Williams Syndrome Association to complete an anonymous online survey about recollections related to the diagnostic process. Responses, both close-ended and open-ended, were received from 600 families across the United States. Analysis revealed a high proportion of families (59.91%) with at least some negative recollections about the experience (and nearly half of those with negative recollections denied recalling anything positive). Factors influencing a more positive overall perception of the experience included receiving written information about Williams syndrome and seeing a genetic counselor. Analysis of open-ended responses identified additional positive and negative themes; for example, nearly one quarter of respondents expressed a desire to be given hope when receiving the diagnosis. Based on these analyses, we offer several specific recommendations for improving the diagnostic process in the future.

Assessment of genetic and nongenetic interactions for the prediction of depressive symptomatology: an analysis of the Wisconsin Longitudinal Study using machine learning algorithms.

OBJECTIVES: We examined depression within a multidimensional framework consisting of genetic, environmental, and sociobehavioral factors and, using machine learning algorithms, explored interactions among these factors that might better explain the etiology of depressive symptoms. METHODS: We measured current depressive symptoms using the Center for Epidemiologic Studies Depression Scale (n = 6378 participants in the Wisconsin Longitudinal Study). Genetic factors were 78 single nucleotide polymorphisms (SNPs); environmental factors-13 stressful life events (SLEs), plus a composite proportion of SLEs index; and sociobehavioral factors-18 personality, intelligence, and other health or behavioral measures. We performed traditional SNP associations via logistic regression likelihood ratio testing and explored interactions with support vector machines and Bayesian networks. RESULTS: After correction for multiple testing, we found no significant single genotypic associations with depressive symptoms. Machine learning algorithms showed no evidence of interactions. Naïve Bayes produced the best models in both subsets and included only environmental and sociobehavioral factors. CONCLUSIONS: We found no single or interactive associations with genetic factors and depressive symptoms. Various environmental and sociobehavioral factors were more predictive of depressive symptoms, yet their impacts were independent of one another. A genome-wide analysis of genetic alterations using machine learning methodologies will provide a framework for identifying genetic-environmental-sociobehavioral interactions in depressive symptoms.

How difficult should it be? Evidence of burden tolerance from a nationally representative sample.

There is growing attention to how policymakers and bureaucrats think about administrative burdens, but we know less about public tolerance for burdens. We examine public burden tolerance in two major programmes (Medicaid and SNAP) using a representative sample of US residents. We show broad support for work requirements and weaker support for generally making it difficult to access benefits. People with conservative beliefs, greater opposition to social policies, and higher income are more tolerant of burdens in social policies. Those who have personal experience of welfare policies are less tolerant of burdens.

Associations Between Midlife Menopausal Hormone Therapy Use, Incident Diabetes, and Late Life Memory in the Wisconsin Longitudinal Study.

BACKGROUND: Prior research suggests a link between menopausal hormone therapy (MHT) use, memory function, and diabetes risk. The menopausal transition is a modifiable period to enhance long-term health and cognitive outcomes, although studies have been limited by short follow-up periods precluding a solid understanding of the lasting effects of MHT use on cognition. OBJECTIVE: We examined the effects of midlife MHT use on subsequent diabetes incidence and late life memory performance in a large, same-aged, population-based cohort. We hypothesized that the beneficial effects of MHT use on late life cognition would be partially mediated by reduced diabetes risk. METHODS: 1,792 women from the Wisconsin Longitudinal Study (WLS) were included in analysis. We employed hierarchical linear regression, Cox regression, and causal mediation models to test the associations between MHT history, diabetes incidence, and late life cognitive performance. RESULTS: 1,088/1,792 women (60.7%) reported a history of midlife MHT use and 220/1,792 (12.3%) reported a history of diabetes. MHT use history was associated with better late life immediate recall (but not delayed recall), as well as a reduced risk of diabetes with protracted time to onset. Causal mediation models suggest that the beneficial effect of midlife MHT use on late life immediate recall were at least partially mediated by diabetes risk. CONCLUSION: Our data support a beneficial effect of MHT use on late life immediate recall (learning) that was partially mediated by protection against diabetes risk, supporting MHT use in midlife as protective against late life cognitive decline and adverse health outcomes.

Using sibling models to unpack the relationship between education and cognitive functioning in later life.

As the population ages and the prevalence of dementia increases, unpacking robust and persistent associations between educational attainment and later life cognitive functioning is increasingly important. We do know, from studies with robust causal designs, that policies that increase years of schooling improve later life cognitive functioning. Yet these studies don't illuminate why older adults with greater educational attainment have relatively preserved cognitive functioning. Studies focused on why, however, have been hampered by methodological limitations and inattention to some key explanations for this relationship. Consequently, we test explanations encompassing antecedent factors, specifically family environments, adolescent IQ, and genetic factors, as well as adult mediating mechanisms, specifically health behaviors and health. We employ the Wisconsin Longitudinal Study, which includes 80 years of prospectively collected data on a sample of 1 in every 3 high school graduates, and a selected sibling, from the class of 1957. Sibling models, and the inclusion of prospectively collected early and midlife covariates, allows us to address the explanatory and methodological limitations of the prior literature to better unpack the relationship between education and later life cognitive functioning. We find little evidence that early life genetic endowments and environments, or midlife health and health behaviors, explain the relationship. Adolescent cognition, however, does matter; higher educational attainment, linked to antecedent adolescent cognitive functioning, helps protect against lower levels of cognitive functioning in later life. Both adolescent cognition and education, however, independently associate with later life cognitive functioning at relatively similar magnitudes. Educational attainment's relationship to later life cognitive functioning is not simply a function of adolescent cognitive functioning.

Effect of childhood proximity to lead mining on late life cognition.

INTRODUCTION: Lead exposure negatively affects cognitive functioning among children. However, there is limited evidence about whether exposure to lead in early life impairs later life cognitive functioning. METHODS: Participants in the prospective Wisconsin Longitudinal Study cohort (N = 8583) were linked to the 1940 Census, which was taken when they were young children. We estimated the effect of living near a lead mine in childhood on late life memory/attention and language/executive function in 2004 (mean age 64) and 2011 (mean age 71). RESULTS: Lead-exposed children had significantly steeper memory/attention decline between 2004 and 2011 and worse language/executive function at baseline in late life. These long-term effects of lead were not mediated through adolescent IQ or late life SES and health factors. DISCUSSION: Proximity to lead mining in childhood had long-term effects on late life memory/attention decline and language/executive function, reflecting a possible latent influence of lead exposure. More research is needed to understand behavioral and biological pathways underlying this relationship.

Black-White variation in the relationship between early educational experiences and trajectories of cognitive function among US-born older adults.

Black adults face a substantially higher risk for dementia in later life compared to their White peers. Given the critical role of educational attainment and cognitive function in later life dementia risk, this paper aims to determine if early educational experiences and educational attainment are differentially related to trajectories of cognitive status across race and if this further varies by education cohort. We use data from the Life History Mail Survey (LHMS) and prospective data on cognition from the Health and Retirement Study (HRS). We restrict our sample to Black and White US-born adults who provided at least one measure of cognitive status from 1995/6-2016. We find evidence of Black-White differences in the association between educational experiences and level of cognitive function, episodic memory, and working memory, but little evidence of Black-White differences in these associations with decline. Having a learning problem was associated with lower levels of cognitive function, episodic memory, and working memory for White and Black older adults, but was more strongly related to these outcomes among Black older adults. Further, the Black-White difference in this association was generally found in older cohorts that completed schooling after enactment of federal policies that improved educational resources for children with learning disabilities. Attending racially discordant schools was positively associated with level of these cognitive outcomes for Black older adults but not for White older adults. We also find that the educational gradient in level of cognitive function was larger for Black compared to White older adults in older cohorts not benefiting from the Brown v Board of Education decision but was similar for Black and White older adults attending school in the post-Brown era.

Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals.

We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI's magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significant SNPs, and a separate X-chromosome additive GWAS identifies 57.

Does Rural Living in Early Life Increase the Risk for Reduced Cognitive Functioning in Later Life?

BACKGROUND: There is a robust consensus, most recently articulated in the 2020 Lancet Commission, that the roots of dementia can be traced to early life, and that the path to prevention may start there as well. Indeed, a growing body of research demonstrates that early life disadvantage may influence the risk for later life dementia and cognitive decline. A still understudied risk, however, is early life rural residence, a plausible pathway given related economic and educational disadvantages, as well as associations between later life rural living and lower levels of cognitive functioning. OBJECTIVE: We aim to examine whether living in rural environments during early life has long term implications for cognitive health in later life. METHODS: We employed the Wisconsin Longitudinal Study, which tracked 1 in every 3 high school graduates from the class of 1957, from infancy to ∼age 72. The data include a rich array of prospectively collected early life data, unique among existing studies, as well as later life measures of cognitive functioning. RESULTS: We found a robust relationship between early life rural residence, especially living on a farm, and long-term risk for reduced cognitive performance on recall and fluency tasks. Controls for adolescent cognitive functioning, APOEɛ2 and APOEɛ4, as well as childhood and adult factors, ranging from early life socioeconomic conditions to later life health and rural and farm residency, did not alter the findings. CONCLUSION: Rural living in early life is an independent risk for lower levels of cognitive functioning in later life.

Reconstructing Sociogenomics Research: Dismantling Biological Race and Genetic Essentialism Narratives.

We detail the implications of sociogenomics for social determinants research. We focus on education and race because of how early twentieth-century scientific eugenic thinking facilitated a range of racist and eugenic policies, most of which helped justify and pattern racial and educational morbidity and mortality disparities that remain today, and are central to sociological research. Consequently, we detail the implications of sociogenomics research by unpacking key controversies and opportunities in sociogenomics as they pertain to the understanding of racial and educational inequalities. We clarify why race is not a valid biological or genetic construct, the ways that environments powerfully shape genetic influence, and risks linked to this field of research. We argue that sociologists can usefully engage in genetics research, a domain dominated by psychologists and behaviorists who, given their focus on individuals, have mostly not examined the role of history and social structure in shaping genetic influence.

Assessing Dementia Prevalence in the Wisconsin Longitudinal Study: Cohort Profile, Protocol, and Preliminary Findings.

BACKGROUND: There is growing consensus that non-genetic determinants of dementia can be linked to various risk- and resiliency-enhancing factors accumulating throughout the lifespan, including socioeconomic conditions, early life experiences, educational attainment, lifestyle behaviors, and physical/mental health. Yet, the causal impact of these diverse factors on dementia risk remain poorly understood due to few longitudinal studies prospectively characterizing these influences across the lifespan. OBJECTIVE: The Initial Lifespan's Impact on Alzheimer's Disease and Related Dementia (ILIAD) study aims to characterize dementia prevalence in the Wisconsin Longitudinal Study (WLS), a 60-year longitudinal study documenting life course trajectories of educational, family, occupational, psychological, cognitive, and health measures. METHODS: Participants are surveyed using the modified Telephone Interview for Cognitive Status (TICS-m) to identify dementia risk. Those scoring below cutoff undergo home-based neuropsychological, physical/neurological, and functional assessments. Dementia diagnosis is determined by consensus panel and merged with existing WLS data for combined analysis. RESULTS: Preliminary findings demonstrate the initial success of the ILIAD protocol in detecting dementia prevalence in the WLS. Increasing age, hearing issues, lower IQ, male sex, APOE4 positivity, and a steeper annualized rate of memory decline assessed in the prior two study waves, all increased likelihood of falling below the TICS-m cutoff for dementia risk. TICS-m scores significantly correlated with standard neuropsychological performance and functional outcomes. CONCLUSION: We provide an overview of the WLS study, describe existing key lifespan variables relevant to studies of dementia and cognitive aging, detail the current WLS-ILIAD study protocol, and provide a first glimpse of preliminary study findings.

Resource profile and user guide of the Polygenic Index Repository.

Polygenic indexes (PGIs) are DNA-based predictors. Their value for research in many scientific disciplines is growing rapidly. As a resource for researchers, we used a consistent methodology to construct PGIs for 47 phenotypes in 11 datasets. To maximize the PGIs' prediction accuracies, we constructed them using genome-wide association studies-some not previously published-from multiple data sources, including 23andMe and UK Biobank. We present a theoretical framework to help interpret analyses involving PGIs. A key insight is that a PGI can be understood as an unbiased but noisy measure of a latent variable we call the 'additive SNP factor'. Regressions in which the true regressor is this factor but the PGI is used as its proxy therefore suffer from errors-in-variables bias. We derive an estimator that corrects for the bias, illustrate the correction, and make a Python tool for implementing it publicly available.

Reporting guidelines for human microbiome research: the STORMS checklist.

The particularly interdisciplinary nature of human microbiome research makes the organization and reporting of results spanning epidemiology, biology, bioinformatics, translational medicine and statistics a challenge. Commonly used reporting guidelines for observational or genetic epidemiology studies lack key features specific to microbiome studies. Therefore, a multidisciplinary group of microbiome epidemiology researchers adapted guidelines for observational and genetic studies to culture-independent human microbiome studies, and also developed new reporting elements for laboratory, bioinformatics and statistical analyses tailored to microbiome studies. The resulting tool, called 'Strengthening The Organization and Reporting of Microbiome Studies' (STORMS), is composed of a 17-item checklist organized into six sections that correspond to the typical sections of a scientific publication, presented as an editable table for inclusion in supplementary materials. The STORMS checklist provides guidance for concise and complete reporting of microbiome studies that will facilitate manuscript preparation, peer review, and reader comprehension of publications and comparative analysis of published results.