Professional Education


  • Doctor of Philosophy, Stanford University, EE-PHD (2013)
  • Master of Science, Stanford University, EE-MS (2009)
  • Bachelor of Science, Washington University, EE & Applied Science (2006)
  • Bachelor of Applied Science, Washington University (2006)

All Publications


  • Comparison of two methods - regression predictive model and intake shift model - for adjusting self-reported dietary recall of total energy intake of populations. Frontiers in public health Lankester, J., Perry, S., Parsonnet, J. 2014; 2: 249-?

    Abstract

    Daily dietary intake data derived from self-reported dietary recall surveys are widely considered inaccurate. In this study, methods were developed for adjusting these dietary recalls to more plausible values. In a simulation model of two National Health and Nutrition Examination Surveys (NHANES), NHANES I and NHANES 2007-2008, a predicted one-third of raw data fell outside a range of physiologically plausible bounds for dietary intake (designated a 33% failure rate baseline). To explore the nature and magnitude of this bias, primary data obtained from an observational study were used to derive models that predicted more plausible dietary intake. Two models were then applied for correcting dietary recall bias in the NHANES datasets: (a) a linear regression to model percent under-reporting as a function of subject characteristics and (b) a shift of dietary intake reports to align with experimental data on energy expenditure. After adjustment, the failure rates improved to <2% with the regression model and 4-9% with the intake shift model - both substantial improvements over the raw data. Both methods gave more reliable estimates of plausible dietary intake based on dietary recall and have the potential for more far-reaching application in correction of self-reported exposures.

    View details for DOI 10.3389/fpubh.2014.00249

    View details for PubMedID 25506048

    View details for PubMedCentralID PMC4245891

  • Urinary Triclosan is Associated with Elevated Body Mass Index in NHANES. PloS one Lankester, J., Patel, C., Cullen, M. R., Ley, C., Parsonnet, J. 2013; 8 (11)

    Abstract

    Triclosan-a ubiquitous chemical in toothpastes, soaps, and household cleaning supplies-has the potential to alter both gut microbiota and endocrine function and thereby affect body weight.We investigated the relationship between triclosan and body mass index (BMI) using National Health and Nutrition Examination Surveys (NHANES) from 2003-2008. BMI and spot urinary triclosan levels were obtained from adults. Using two different exposure measures-either presence vs. absence or quartiles of triclosan-we assessed the association between triclosan and BMI. We also screened all NHANES serum and urine biomarkers to identify correlated factors that might confound observed associations.Compared with undetectable triclosan, a detectable level was associated with a 0.9-point increase in BMI (p<0.001). In analysis by quartile, compared to the lowest quartile, the 2nd, 3rd and 4th quartiles of urinary triclosan were associated with BMI increases of 1.5 (p<0.001), 1.0 (p = 0.002), and 0.3 (p = 0.33) respectively. The one strong correlate of triclosan identified in NHANES was its metabolite, 2,4-dichlorophenol (ρ = 0.4); its association with BMI, however, was weaker than that of triclosan. No other likely confounder was identified.Triclosan exposure is associated with increased BMI. Stronger effect at moderate than high levels suggests a complex mechanism of action.

    View details for DOI 10.1371/journal.pone.0080057

    View details for PubMedID 24278238

    View details for PubMedCentralID PMC3836985