• Motivating directed acyclic graph (DAG) from on-going epigenetic work.

    Jonathan Y Huang, PhD, MPH

    Epigenetic technologies coupled with causal inference methodologies promise instrumental insight on how the environment interacts with our bodies. What does this mean for health equity policies?

  • Motivation | "Health Equity via Mechanistic Knowledge"

    For decades now, advocates, academic researchers, and decision makers have highlighted the robust, persistent, and often large differences in chances for good health that are the consequence of material and social (dis)advantage and begin in early life. However, the lack of overall progress in reducing health inequalities or devising novel interventions has spurred a demand for more "consequential" epidemiologic research, taking as a goal policy or practice change. To this end, recent theoretical and methodological developments in causal inference, the application of counterfactual frameworks to define and estimate effects of interventions, have greatly improved researchers' abilities to investigate complex mechanistic questions as they exist in the real world (i.e. outside of controlled experimental settings). This is particularly important for the study of social causation and longitudinal, life course, and intergenerational effects. However, one major criticism is that the application of counterfactual approaches may tend to be conservative in practice, e.g. limited explicitly or de facto to the most plausible existing interventions.
    In contrast, a concurrent flood of molecular epidemiologic findings across the "-omics" (genomics, transcriptomics, metabolomics, etc.) suggest compelling new mechanisms for how social and material disadvantage "gets under the skin" to produce health inequities. For example, epigenetic modifications due to fetal and early childhood exposures may lead to persistent, potentially pathological, differences in gene function without changes to underlying DNA sequence. Better understanding of such mechanisms and the social exposures that influence them may lead to new modes of intervention. However the complexity of biological systems often lead to focused investigations that defy extrapolation to whole individuals, let alone populations within and across generations.
    One fundamental challenge in motivating health equity policies is poor understanding of the extent to which later intervention can eliminate observed health disparities that begin in early life. More deliberate integration of epigenetic and other biomarkers of physical functioning into causal inference frameworks may help motivate and inform such policies: Representing both malleable and immutable features of health variation, biomarkers provide not only potential targets for intervention, but also encode the most up-to-date knowledge of when and where interventions may be less effective. This is critical for pushing the boundaries for intervention in a disciplined manner. Correspondingly, causal inference frameworks provide formal structures within which putative mechanisms may be modeled as well as defining the conditions under which potential intervention effects can be identified from observed data.

    Research Focus |
    How does "early life last a lifetime" and what can we do about it?


    My primary research focus is on modelling mechanisms, including epigenetic mechanisms, linking early life to the life course and hypothetical interventions thereupon on reducing health disparities and improving population health in various global contexts. 


    My work has investigated the important universal and contextual early life exposures relevant to socioeconomic disparities in health across a range of global contexts including the U.S., Israel, South Africa, and Singapore. Correspondingly, the work has considered exposures ranging from malnutrition to environmental chemicals and outcomes from child infections to adult cardiometabolic risk and pregnancy outcome. Methodologically, my work incorporates epigenetic biomarkers such as DNA methylation in life course analyses of intergenerational transmission of socioeconomic differences in health, with particular attention to partitioning biological and sociobehavioral pathways. To model longitudinal effects, I employ standardization- and simulation-based methods built upon counterfactual frameworks coupled with comprehensive sensitivity and bias analyses to quantify the uncertainty around novel biological mechanisms.


    Moreover, I have interests in how and why empirical research is translated to interventions or policy, particularly in contested domains such as social policy. I have authored commentaries on the challenges of inference using biomarkers and the use of epigenetics to motivate ethical claims, and hosted a workshop on the relevance of causal inference to evidence-based policy.

  • Projects

    This will nearly always be out-of-date! Check out the lab site @ jonhuang.org!

    Modeling interventions on early life factors on child adiposity in a Singaporean birth cohort

    Child obesity present a significant long term health and economic burden to Singapore. My work involves modeling the contribution of modifiable maternal pregnancy characteristics, infant feeding, infections, and child diet and physical activity to socioeconomic disparities in child adiposity and body composition in the preschool years. The effects of hypothetical interventions on these factors would be estimated using counterfactual simulation approaches (parametric g-computation and targeted maximum likelihood estimation). Data are drawn from the GUSTO (Growing Up in Singapore Towards Healthy Outcomes) birth cohort, which has enrolled over 1000 mothers and children and now followed them through 8 years. As equal starts to life is a current priority of the government, results from this work will be particularly timely. As a corollary to this work, I will focus specifically on the influence of gestational diabetes (GDM) on child adiposity, as Singapore has one of the highest proportions of pregnancies affected by GDM in the world. The relationship between GDM and long term child outcomes has been inconsistently described and observational studies can be biased by treatment modalities. Causal mediation and quasi-experimental approaches will be used to investigate the potential benefits of intervening on GDM or its sequelae on child adiposity. 

    Pesticides, infections, growth, and determinants of disparities in a rural, South African birth cohort.

    As part of the Venda Health Examination of Mothers, Babies, and their Environment (VHEMBE), a well-characterized, longitudinal, birth cohort located in rural Limpopo, South Africa now in its 5th year of follow-up, I investigated the role of early life pesticide exposures (specifically, DDT/E and pyrethroid metabolites) on common childhood infections and child growth. Pesticides exposures in this cohort are relatively high due to the practice of indoor residual spraying (IRS) for malaria vector control. Notably, I demonstrated that the adverse associations of DDTs were observed solely in the socioeconomically vulnerable. This work has appeared in Environmental Health Perspectives and Environmental Epidemiology. In on-going work, I model the putative effect of joint interventions on pesticide exposure and poverty as well as decompose the contributions of various factors to socioeconomic disparities in child growth and how they differ by sex.
    Sources of Support
    Norman Bethune Award for Global Health (McGill University, Faculty of Medicine, Global Health Programs), $2500. 2017.
    Role: Awardee
    Canadian Institutes of Health Research Operating Grant #343015.

    Completed Work

    Intergenerational adversity and epigenetic markers of cardiometabolic risk among young adult women in the Jerusalem Perinatal Study.

    Investigate associations between parental socioeconomic position (SEP) and candidate gene DNA methylation in young adult women (32 years old) as a potential mediator for associations between parental SEP and offspring cardiometabolic health. Test several structural assumptions using marginal structural models estimated by inverse probability weighting.
    Investigate associations between markers of intrauterine environment (IUE) including maternal pre-pregnancy BMI, gestational weight gain, parental smoking, and offspring birth weight and candidate gene DNA methylation in young adult women as a potential mediator for previously observed associations between IUE and cardiometabolic health.
    Sources of Support
    Canadian Institutes of Health Research (CIHR) Institute of Nutrition, Metabolism, and Diabetes - Institute Community Support Travel Award, $1500. 2015-2016.
    "Life course-adjusted associations between intrauterine environment and DNA methylation in young adult women of a Jerusalem Perinatal Study sub-cohort."
    Role: Awardee
    University of Washington Global Woman, Adolescent, and Child Health (Global WACh) Integrated Health Seed Grant, $25,000. 2013-2014.
    Role: Co-Investigator (PIs: Daniel Enquobahrie, Amelia Gavin)

    Effect of ride-sharing (Uber) on road traffic mortality in South African provinces

    Using administrative death certification data, I investigate the changes in road-traffic related mortality across provinces with different timing of availability of the Uber ride-sharing service. A difference-in-differences approach was applied coupled with sensitivity analyses through placebo treatments and control outcomes (with Farhan Majid and Mark Daku). Forthcoming.

    Workshop on "Epidemiology, Causation, and Public Policy"

    Co-organized a workshop on 24-25 May 2016 bringing together a number of prominent epidemiologists, philosophers, and public policy researchers along with public health practitioners to discuss the role of epidemiologists and causal inference in evidence-based public policy making, particularly considering the idea of a "consequential epidemiology." Works were presented by discussants in a round-table format and debated vigorously.

    Investigating the role of scientific evidence in policy and ethical discourse.

    Review the current discourse regarding how knowledge of epigenetic transmission of health reshapes public health ethics including luck and Rawlsian egalitarianism. Critique the extrapolations from existing evidence, recapitulation of genetic determinism, and the questionable extensions from biomedical evidence to social policies. (with Nicholas King)


    Qualitative and quantitative analysis of the instrumental and rhetorical use of empirical evidence in health and social equity-promoting policy case studies in the U.S. and Canada. (with Zinzi Bailey and Mark Daku)


    Broad survey of opinions and experiences of public health researchers regarding their participation in evidence-informed policy making. Upcoming book proposal on the use of evidence in the production of evidence-based or evidence-informed health policy, synthesizing the above projects. (with Mark Daku)


    Systematically consider the translation of statistical uncertainty and generalizability from empirical findings to several WHO policy statements including infant feeding and vitamin supplementation. (with Tarik Benmarhnia)



    “Ethics, Social Determinants of Health, and Health Equity: Integrating Theory and Practice.” Canadian Institutes for Health Research. 2014 -
    Role: Postdoctoral Fellow, via McGill University (PIs: Daniel Weinstock, Nicholas King)

  • Highlighted Papers

    Selected works (Full list in CV)

    Meng X, Huang JY. Doubly robust, machine learning effect estimation in real-world clinical sciences: A practical evaluation of performance in molecular epidemiology cohort settings. arXiv. (pre-print).


    Huang JY. Leveraging molecular negative controls for effect estimation in non-randomized human health and disease studies: a demonstrative simulation study. ICML 2021 - Neglected Assumptions in Causal Inference Workshop. (accepted pre-print)


    Huang JY, Eskenazi B, Bornman R, Rauch S, Chevrier J. Maternal peripartum serum DDT/E and urinary pyrethroid metabolite concentrations and child infections at 2 years in the VHEMBE birth cohort: associations and modifiers. Environmental Health Perspectives. 2018 June. (FULL TEXT)


    Huang JY, Gariepy G, Gavin AR, Richardson TS, Rowhani-Rahbar A, Siscovick DS, Enquobahrie DA. Maternal education and risk of metabolic syndrome in young adult Americans: Disentangling life course processes through causal models. Epidemiology. 2021 NICHD Special Issue.


    Huang JY, Kaufman J. Getting serious about embodiment: Cautions about interpreting novel findings of socioeconomic patterns in biological function. American Journal of Epidemiology. 2018 June. (FULL TEXT)


    Huang JY, Siscovick DS, Hochner H, Friedlander Y, Enquobahrie DA. Maternal gestational weight gain and DNA methylation in young women: application of life course mediation methods. Epigenomics. December 2017. (ABSTRACT)


    Huang JY, Gavin AR, Richardson TS, Rowhani-Rahbar A, Siscovick DS, Hochner H, Friedlander Y, Enquobahrie DA. Accounting for Life-Course Exposures in Epigenetic Biomarker Association Studies: Early Life Socioeconomic Position, Candidate Gene DNA Methylation, and Adult Cardiometabolic Risk. American Journal of Epidemiology. 2016 October. 184 (7): 520-531. 2016 Articles of the Year. (ABSTRACT)


    Huang JY, Gavin AR, Richardson TS, Rowhani-Rahbar A, Siscovick DS, Enquobahrie DA. Huang, et al. Respond to "Multigenerational Social Determinants of Health." American Journal of Epidemiology. 2015 October. 182 (7): 583-584. (FULL TEXT)


    Huang JY, Gavin AR, Richardson TS, Rowhani-Rahbar A, Siscovick DS, Enquobahrie DA. Are early life socioeconomic conditions directly related to birth outcomes? Grandmaternal education, grandchild birth weight, and associated bias analyses. American Journal of Epidemiology. 2015 October. 182 (7): 568-578. (FULL TEXT)


    (Google Scholar Profile)

  • CV

    Download my most recent CV by clicking the link below.

  • Posters and other visuals

    Presented, published, or in progress.

    Presented at the International Conference on Machine Learning - Neglected Assumptions in Causal Inference Workshop. 2021.
    Presented at the World Congress for the Developmental Origins of Health and Disease. 2019.
    Incorporating novel etiologic investigations in a population health framework. Presented at Society for Pediatric and Perinatal Epidemiologic Research Annual Meeting 2017.
  • Thoughts

    Better yet, follow me on twitter instead at jon_y_huang!

    Much can, has, and is worth saying with respect to the promise of machine learning and its...
    In a recent blog post, Hershbein & company of The Hamilton Project (Brookings Institute) describe...
  • Questions, comments, collaborations?

    Send me an email. I will endeavor to respond as quickly as possible!

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