
Lauren Gaydosh
· Associate ProfessorVerifiedUniversity of North Carolina at Chapel Hill · Sociology
Active 2008–2026
About
Lauren Gaydosh is an Associate Professor in the Department of Sociology at the University of North Carolina at Chapel Hill. Her areas of interest include life course determinants, population health disparities, and biosocial perspectives. She earned her PhD from Princeton University in 2015. Her work focuses on understanding how social and biological factors influence health outcomes over the course of individuals' lives, contributing to the fields of sociology and population health through research that integrates biosocial approaches.
Research topics
- Biology
- Gerontology
- Psychology
- Medicine
- Psychiatry
- Ecology
- Genetics
- Developmental psychology
- Demography
Selected publications
UNC Libraries · 2026-04-09
articleOpen accessThe purpose of this document is to 1) describe the provenance, quality control, and curation of the Add Health epigenetic data set and 2) to aid the user in their analysis.
Mapping Lifecourse Reproductive Trajectories in a Nationally Representative Cohort of U.S. Women
Innovation in Aging · 2025-12-01
articleOpen accessSenior authorAbstract Reproductive timing and experiences vary substantially among U.S. women, yet few studies have systematically classified reproductive life course trajectories in nationally representative, longitudinal cohorts. Using data from Waves I–V of the National Longitudinal Study of Adolescent to Adult Health (Add Health), we constructed reproductive trajectories based on age at menarche, timing of first birth, total parity, reproductive lifespan, and pregnancy-related complications. Variables were harmonized and temporally aligned to accommodate changes in survey structure across waves, and latent class analysis identified distinct reproductive patterns. These trajectories capture meaningful variation in reproductive timing and intensity that is hypothesized to be biologically relevant for chronic disease risk in midlife. This work is novel in its application to a large, nationally representative sample with rich longitudinal reproductive histories. The resulting classifications provide a foundation for ongoing research linking reproductive life course patterns to molecular indicators of aging and long-term health outcomes in women.
UNC Libraries · 2025-06-05
articleOpen accessEducational disparities in health are well documented, yet the education-health relationship is inconsistent across racial/ethnic and nativity groups. These inconsistencies may arise from characteristics of the early life environments in which individuals attain their education. We evaluate this possibility by investigating (1) whether educational disparities in cardiometabolic risk vary by race/ethnicity and nativity among Black, Hispanic, and White young adults; (2) the extent to which racial/ethnic-nativity differences in the education-health relationship are contingent on economic, policy, and social characteristics of counties of early life residence; and (3) the county characteristics associated with the best health at higher levels of education for each racial/ethnic-nativity group. Using data from the National Longitudinal Study of Adolescent to Adult Health, we find that Black young adults who achieve high levels of education exhibit worse health across a majority of contexts relative to their White and Hispanic counterparts. Additionally, we observe more favorable health at higher levels of education across almost all contexts for White individuals. For all other racial/ethnic-nativity groups, the relationship between education and health depends on the characteristics of the early life counties of residence. Findings highlight place-based factors that may contribute to the development of racial/ethnic and nativity differences in the education-health relationship among U.S. young adults.
The Role of Despair in Predicting Self-Destructive Behaviors
Universität Zürich, ZORA · 2025-05-13
articleOpen access1st authorCorrespondingUNC Dataverse · 2025-12-10
datasetOpen access1st authorCorrespondingThe Data Management and Sharing Plan describes the scientific data to be generated and/or used in the research and outlines a strategy for managing and sharing project data.
The Lancet Regional Health - Americas · 2025-04-07 · 6 citations
articleOpen accessBackground: Alzheimer's disease is a major health concern in the U.S., but most research has focused on older populations. We examined whether established risk factors and blood biomarkers are associated with cognition before midlife. Methods: Data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) were analyzed. Participants were enrolled in 1994-95 (grades 7-12) and followed through 2018. We cross-sectionally analyzed weighted survey and biomarker data from Waves IV and V. We measured the Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) score comprised of age, education, sex, systolic blood pressure, body mass index, cholesteroal, and physical activity and apolipoprotein E ε4 allele (APOE ε4) status. We also measured total Tau and Neurofilament light (NfL), high sensitivity C-reactive protein (hsCRP), Interleukin (IL)-1β, IL-6, IL-8, IL-10, and Tumor necrosis factor alpha (TNF-α). Outcomes included immediate word recall, delayed word recall, and backward digit span. Findings: Analytic sample sizes ranged from 4507 to 11,449 participants in Wave IV and from 529 to 1121 participants in Wave V. The survey-weighted median (IQR) age was 28 (26-29) years in Wave IV and 38 (36-29) years in Wave V. About half of the survey-weighted Wave IV participants were female (48.4-52.1% across analytic samples), 71.4-72.5% were White, 12.5-14.9% were Black, and 9.3-10.2% were Hispanic. In Wave V, 43.6-46.8% were female, 68.7-69.3% were White, 17.1%-20.0% were Black, and 7.3%-9.6% were Hispanic. The CAIDE score was associated with all cognition measures in Wave IV. For example, among adults aged 24-34, each 1-point increase in CAIDE was associated with a 0.03 standard deviation lower backward digit span score (95% CI: -0.04, -0.02). Total Tau was associated with immediate word recall in Wave V (β = -0.13, 95% CI: -0.23, -0.04). Wave IV hsCRP and IL-10 and Wave V IL-6, IL-1β, and IL-8 were also associated with lower cognitive scores. Interpretation: Key risk factors for Alzheimer's Disease are linked to cognitive function as early as ages 24-44, highlighting the need for early prevention in the US. Funding: NIHP01HD31921, U01AG071448, U01AG071450, R01AG057800, P30AG066615, T32HD091058, P2CHD050924.
Research Note: Does Despair in Young Adulthood Predict Mortality?
Demography · 2025-03-24 · 1 citations
articleOpen accessSenior authorThe trend of increasing U.S. working-age (25-64) mortality is well-documented. Yet, our understanding of its causes is incomplete, and analyses are often limited to using population data with little information on individual behaviors and characteristics. One characterization of this trend centers on the role of despair as a catalyst for self-destructive behaviors that ultimately manifest in mortality from suicide and substance use. The role of despair in predicting mortality at the individual level has received limited empirical interrogation. Using Cox proportional hazards models with behavioral risk factors and latent variable measures of despair in young adulthood (ages 24-32 in 2008-2009) as focal predictors, we estimate subsequent mortality risk through 2022 (298 deaths among 12,277 individuals; 177,628 person-years of exposure). We find that suicidal ideation, suicide attempts, illegal drug use, and prescription drug abuse in young adulthood predict all-cause, suicide, and drug poisoning mortality. Notably, all four domains of despair (cognitive, emotional, biosomatic, and behavioral) and overall despair predict all-cause mortality and mortality from drug poisoning and suicide. This research note provides new empirical evidence regarding the relationship between individual despair and mortality, improving our understanding of the life course contributors to working-age mortality.
Impact of young adult life transitions on adult mental health problems: a propensity score analysis
Universität Zürich, ZORA · 2025-01-01
articleOpen accessBackground Mental health problems commonly persist from childhood to adulthood. This study tested whether young adult life transitions can improve adult mental health symptoms after adjusting for childhood mental health symptoms. Methods The analysis uses data from the prospective, representative Great Smoky Mountains Study. Life transitions (e.g., high school completion, partnering, parenthood, and living independently) were assessed up to three times in young adulthood (ages 18 to 26; 3,241 observations). A cumulative variable counted the number of young adult transitions. Emotional, substance use, and antisocial personality symptoms were assessed at age 30 (1,154 participants or 81.2% of the original sample). Propensity models adjusted for early life adversities and psychiatric symptoms. Results Multiple young adult transitions were common (m = 4.62; SD = 1.57). After adjusting for childhood mental health problems and adversities, each additional transition was significantly associated with a reduction in subsequent adult emotional symptoms (β = −0.34, 95% CI: −0.59, −0.08, p = 0.01) and adult antisocial personality disorder symptoms (β = −0.08, 95% CI: −0.14, −0.02, p < 0.001. These associations were stronger in males than in females. Young adult transitions were not associated with reductions in subsequent substance use symptoms (β = −0.04; 95% CI: −0.11, 0.03, p = 0.30). Young adult transitions related to educational milestones and consistent employment were associated with the largest reductions in symptoms. Conclusions In this cohort study, life transitions during young adulthood were associated with reduced emotional and behavioral symptoms in adulthood. These transitions may constitute a potential mental health turning point and a specific, modifiable target for social policies.
Psychoneuroendocrinology · 2025-06-02 · 1 citations
articleOpen access1st authorCorrespondingIndividual educational effort usually promotes educational success and attainment, and generally has long-lasting positive consequences. However, there is important heterogeneity in this relationship due in part to constraints on the efficacy of individual effort presented by structural disadvantage, racism, and ethnocentrism. Using longitudinal data from the Future of Families and Child Wellbeing Study (n=1,670, age 0-17, male and female), we investigate the relationship between educational effort and mental (depressive symptoms) and physical (accelerated epigenetic aging) health. Drawing from scholarship on intersectionality, John Henryism, and skin-deep resilience, we investigate whether the associations are moderated by socioeconomic disadvantage, and test for differences by race and ethnicity (White, Black, and Hispanic). We find that educational effort is consistently protective for depressive symptoms but predicts accelerated epigenetic aging among Hispanic adolescents from low socioeconomic circumstances. • Educational effort generally promotes health, but this benefit depends on childhood exposure to disadvantage. • Educational effort was consistently associated with lower depressive symptoms for all adolescents regardless of socioeconomic disadvantage. • Among adolescents from disadvantaged social contexts, educational effort was associated with accelerated epigenetic aging among Hispanic, but not among White or Black, adolescents.
The Role of Despair in Predicting Self-Destructive Behaviors
Population Research and Policy Review · 2025-05-13 · 2 citations
articleOpen access1st authorCorrespondingWorking age (25-64) mortality in the US has been increasing for decades, driven in part by rising deaths due to drug overdose, as well as increases in suicide and alcohol-related mortality. These deaths have been hypothesized by some to be due to despair, but this has rarely been empirically tested. For despair to explain mortality due to alcohol-related liver disease, suicide, and drug overdose, it must first predict the behaviors that lead to such causes of death. To that end, we aim to answer two research questions. First, does despair predict the behaviors that are antecedent to the "deaths of despair"? Second, what measures and domains of despair are most important? We use data from over 6000 individuals at five waves of the National Longitudinal Study of Adolescent to Adult Health and apply supervised machine learning to assess the role of despair in predicting self-destructive behaviors associated with these causes of death. Comparing predictive performance within each outcome using measures of despair to benchmark models of clinical and prior behavioral predictors, we evaluate the added predictive value of despair above and beyond established risk factors. We find that despair underperforms compared to clinical risk factors for suicidal ideation and heavy drinking, but over performs compared to clinical risk factors and prior behaviors for illegal drug use and prescription drug misuse. We also compare model performance and feature importance across outcomes; our ability to predict thoughts of suicide, drug abuse and misuse, and heavy drinking differs depending on the behavior, and the relative importance of different indicators of despair varies across outcomes as well. Our findings suggest that the self-destructive behaviors are distinct and the pathways from despair to self-destructive behavior varied. The results draw into question the relevance of despair as a unifying framework for understanding the current crisis in midlife health and mortality.
Recent grants
NIH · $162k · 2018
Frequent coauthors
- 42 shared
Kathleen Mullan Harris
University of North Carolina at Chapel Hill
- 24 shared
William Copeland
University of Vermont
- 22 shared
Lilly Shanahan
Youth Development
- 21 shared
Sherika Hill
Center for Child and Family Health
- 21 shared
E. Jane Costello
University of Southern California
- 18 shared
Kenneth A. Dodge
Center for Child and Family Health
- 17 shared
Annekatrin Steinhoff
University of Bern
- 10 shared
Allison E. Aiello
Butler University
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