
About
Jason Boardman is a professor in the Department of Sociology at the University of Colorado Boulder, affiliated with the Institute of Behavioral Science. His research focuses on the social determinants of health, with an emphasis on gene-environment interactions related to health behaviors. He teaches undergraduate and graduate courses in statistics, social demography, and the sociology of race and ethnicity. His work explores how social and genetic factors influence health outcomes, educational attainment, and social behaviors, contributing to the understanding of the complex interplay between genetics and social environments in shaping health and social patterns.
Research topics
- Computer Science
- Medicine
- Biology
- Genetics
- Psychiatry
- Internal medicine
- Psychology
- Computational biology
- Environmental health
- Evolutionary biology
- Demography
Selected publications
Nature Mental Health · 2023 · 225 citations
- Computer Science
- Psychiatry
- Psychology
Demography · 2023
- Computer Science
- Computer Science
The Editors of Demography rely on the expertise and judgment of outside reviewers in selecting manuscripts for publication. We thank our many colleagues for their thoughtful and professional contributions to this process. Their detailed, constructive criticism is essential in supporting authors during manuscript revision. Over the last year, we have experienced increased difficulty in recruiting reviewers and receiving timely reviews. Hence, we are especially grateful for this most recent roster of reviewers. The following individuals served as peer reviewers during the period September 1, 2022, to August 31, 2023.
SSM - Population Health · 2023-05-08 · 6 citations
articleOpen accessSenior authorChildren who experience parental imprisonment report greater mental and physical health adversities in adolescence and adulthood relative to comparable individuals whose parents did not serve time in prison. Research has linked BMI gain with parental imprisonment among females, but other studies have shown null or negative associations between parental imprisonment and weight increases for their offspring. Using longitudinal data from the National Longitudinal Study of Adolescent to Adult Health, this study attempts to resolve these differential findings by examining the interrelationship between delinquent behavior and BMI associated with parental imprisonment as individuals progress from adolescence into adulthood (ages 12-32). We show that higher delinquency levels are associated with lower BMI among men and women. With the transition from adolescence to adulthood, parental imprisonment is linked with increased BMI gain and obesity among females who are not delinquent. These findings highlight the need to consider how the decline in delinquent behavior and increasing health disparities between adolescence and adulthood may intersect as individuals experiencing parental imprisonment transition from adolescence to adulthood.
Genetic diversity fuels gene discovery for tobacco and alcohol use
Nature · 2022 · 504 citations
- Biology
- Genetics
- Evolutionary biology
. Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.
Nature Human Behaviour · 2021 · 161 citations
- Biology
- Demography
- Genetics
UNC Libraries · 2021-01-09
articleOpen accessBACKGROUND: Maltreatment by an adult or caregiver during childhood is a prevalent and important predictor of antisocial behaviors in adulthood. A functional promoter polymorphism in the monoamine oxidase A (MAOA) gene has been implicated as a moderating factor in the relationship between childhood maltreatment and antisocial behaviors. Although there have been numerous attempts at replicating this observation, results remain inconclusive. METHODS: We examined this gene-environment interaction hypothesis in a sample of 3356 white and 960 black men (aged 24-34) participating in the National Longitudinal Study of Adolescent Health. RESULTS: Primary analysis indicated that childhood maltreatment was a significant risk factor for later behaviors that violate rules and the rights of others (p < .05), there were no main effects of MAOA genotype, and MAOA genotype was not a significant moderator of the relationship between maltreatment and antisocial behaviors in our white sample. Post hoc analyses identified a similar pattern of results among our black sample in which maltreatment was not a significant predictor of antisocial behavior. Post hoc analyses also revealed a main effect of MAOA genotype on having a disposition toward violence in both samples and for violent convictions among our black sample. None of these post hoc findings, however, survived correction for multiple testing (p > .05). Power analyses indicated that these results were not due to insufficient statistical power. CONCLUSIONS: We could not confirm the hypothesis that MAOA genotype moderates the relationship between childhood maltreatment and adult antisocial behaviors.
Model-based assessment of replicability for genome-wide association meta-analysis
Nature Communications · 2021 · 40 citations
- Computer Science
- Computational biology
- Computer Science
Genome-wide association meta-analysis (GWAMA) is an effective approach to enlarge sample sizes and empower the discovery of novel associations between genotype and phenotype. Independent replication has been used as a gold-standard for validating genetic associations. However, as current GWAMA often seeks to aggregate all available datasets, it becomes impossible to find a large enough independent dataset to replicate new discoveries. Here we introduce a method, MAMBA (Meta-Analysis Model-based Assessment of replicability), for assessing the "posterior-probability-of-replicability" for identified associations by leveraging the strength and consistency of association signals between contributing studies. We demonstrate using simulations that MAMBA is more powerful and robust than existing methods, and produces more accurate genetic effects estimates. We apply MAMBA to a large-scale meta-analysis of addiction phenotypes with 1.2 million individuals. In addition to accurately identifying replicable common variant associations, MAMBA also pinpoints novel replicable rare variant associations from imputation-based GWAMA and hence greatly expands the set of analyzable variants.
Social Science & Medicine · 2021-02-17 · 8 citations
articleOpen accessSenior authorUNC Libraries · 2021-01-09
articleOpen accessHere we provide a detailed description of the genome-wide information available on the National Longitudinal Study of Adolescent to Adult Health (Add Health) sibling pair subsample (Harris et al., 2012). A total of 2020 samples were genotyped (including duplicates) arising from 1946 Add Health individuals from the sibling pairs subsample. After various steps for quality control (QC) and quality assurance (QA), we have high quality genome-wide data available on 1,888 individuals. In this report, we first highlight theQC and QA steps that were taken to prune the data of poorly performing samples and genetic markers. We further estimate the pairwise biological relationships using genome-wide data and compare those estimates to the assumed relationships in Add Health. Additionally, using genome-wide data from knownregional reference populations from Europe, West Africa, North and South America, Japan and China, weestimate the relative genetic ancestry of the respondents. Finally, rather than conducting a traditional cross-sectional genome-wide association study (GWAS) of body mass index (BMI), we opted to utilize the extensivepublicly available genome-wide information to conduct a weighted genome-wide association study (GWAS) of longitudinal BMI while accounting for both family and ethnic variation.
The Sequencing of a College Degree during the Transition to Adulthood: Implications for Obesity
UNC Libraries · 2021-01-13 · 8 citations
articleOpen access1st authorCorrespondingIn this study we consider the health implications of the sequencing of a college degree vis-à-vis familial roles during the transition to adulthood. We hypothesize that people who earned a college degree before assuming familial roles will have better health than people who earned a college degree afterwards. To test this hypothesis, we focus on obesity and use data from the National Longitudinal Study of Adolescent Health. Results show that marriage before completion of college was associated with a 50% higher probability of becoming obese when compared with marriage after completion of college. Parenthood before college completion was associated with a greater-than two-fold increase in the probability of becoming obese when compared to parenthood afterwards for Black men. These findings suggest that the well-established association of education with health depends on its place in a sequence of roles.
Recent grants
NIH · $60k · 2018
NIH · $300k · 2016
NIH · $2.7M · 2016
University of Colorado Population Center
NIH · $923k · 2010–2027
NIH · $602k · 2010
Frequent coauthors
- 74 shared
Benjamin W. Domingue
- 65 shared
Kathleen Mullan Harris
University of North Carolina at Chapel Hill
- 46 shared
Robbee Wedow
Broad Institute
- 38 shared
Matthew B. McQueen
Mitre (United States)
- 34 shared
Henry R. Kranzler
Washington University in St. Louis
- 33 shared
Dalton Conley
- 32 shared
Michael C. Stallings
University of Colorado System
- 32 shared
John K. Hewitt
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