The Anniston Community Health Survey was a community-based cross-sectional study of Anniston, Alabama, residents who live in close proximity to a former PCB production facility to identify factors associated with serum PCB levels. The survey comprises 765 Anniston residents who completed a questionnaire interview and provided a blood sample for analysis in 2005-2007. Several reports based on data from the Anniston survey have been previously published, including associations between PCB exposure and diabetes and blood pressure. In this study we examine demographic, behavioral, dietary, and occupational characteristics of Anniston survey participants as predictors of serum PCB concentrations. Of the 765 participants, 54% were White and 45% were African-American; the sample was predominantly female (70%), with a mean age of 55. years. Serum PCB concentrations varied widely between participants (range for sum of 35 PCBs: 0.11-170.4. ng/g wet weight). Linear regression models with stepwise selection were employed to examine factors associated with serum PCBs. Statistically significant positive associations were observed between serum PCB concentrations and age, race, residential variables, current smoking, and local fish consumption, as was a negative association with education level. Age and race were the most influential predictors of serum PCB levels. A small age by sex interaction was noted, indicating that the increase in PCB levels with age was steeper for women than for men. Significant interaction terms indicated that the associations between PCB levels and having ever eaten locally raised livestock and local clay were much stronger among African-Americans than among White participants. In summary, demographic variables and past consumption of locally produced foods were found to be the most important predictors of PCB concentrations in residents living in the vicinity of a former PCB manufacturing facility.

The efficient calculation of Hamiltonian spectra, a problem often intractable on classical machines, can find application in many fields, from physics to chemistry. We introduce the concept of an "eigenstate witness" and, through it, provide a new quantum approach that combines variational methods and phase estimation to approximate eigenvalues for both ground and excited states. This protocol is experimentally verified on a programmable silicon quantum photonic chip, a mass-manufacturable platform, which embeds entangled state generation, arbitrary controlled unitary operations, and projective measurements. Both ground and excited states are experimentally found with fidelities >99%, and their eigenvalues are estimated with 32 bits of precision. We also investigate and discuss the scalability of the approach and study its performance through numerical simulations of more complex Hamiltonians. This result shows promising progress toward quantum chemistry on quantum computers.