As a demographer, sociologist, and social epidemiologist, I pursue several research questions.   They are all related to population health.  Some questions are fascinating to me because of deep substantive implications — for instance, how is educational attainment related to adult health?  Other questions captivate me because of methodological paradoxes or quandaries.  Here are nice examples of both kinds of questions.


My main research area concerns the relationship between educational attainment and health of U.S. adults.

A few years ago, I discovered unexpected anomalies in the health gradient for two groups:  recipients of the GED diploma and adults with some college but no degree.  The first group is assumed to be equivalent to regular high school graduates and thus to have equivalent health.   The second group is assumed to have better health than HS graduates as a function of their additional education.  However, the data I examined did not support these expectations.  Instead, they showed that GED recipients had worse health and college dropouts no better health than high school graduates.

The first results were published in 2012 and 2013 in Social Science Quarterly, American Journal of Public Health, and Social Science and Medicine.   These studies documented the anomalies at the GED level and the subbaccalaureate level.  Since then, I focused on understanding the why these anomalies exist.

For instance, these recent studies used self-reported data.   What if the observed patters aredue to systematic reporting differences across groups rather than differences in the actual underlying health status?  With Vicki Johnson-Lawrence,  we solved this question by using biomarker measures available in NHANES.  We found that the anomaly was smaller but still visible even when we eliminated potential self-report bias. The paper was published in 2016 in Social Science and Medicine-Population Health.


Another line of research I have been pursuing for nearly a decade is primarily methodological.  The obesity paradox is a phenomenon wherein high body weight is associated with poor health during the life course but paradoxically lower mortality at older ages. Many researchers, including me, believe that at least a part of this phenomenon is due to our inability to model weight changes adequately.

In a recent paper published in The Gerontologist, I applied a joint generalized growth mixture-proportional hazards survival model and found that weight gain among older adults has little detrimental effects on mortality while weight loss is a powerful predictor of mortality.

Currently, with several collaborators, I am using a powerful nonparametric approach to model BMI trajectories.  In a paper currently under review, we are applying hierarchical clustering of body weight functions estimated via the PACE algorithm.  This method is completely novel – its components have recently been developed in statistical journals but it has never been applied to any substantive questions, whether in population health or elsewhere.  Looking forward, I plan to expand this flexible functional approach to understanding aspects of body weight trajectories such as socioeconomic and health correlates.