An index of geospatial disadvantage predicts both obesity and unmeasured body weight.

Neighborhood context impacts health. Using an index of geospatial disadvantage measures to predict neighborhood socioeconomic disparities would support area-based allocation of preventative resources, as well as the use of location as a clinical risk factor in care of individual patients. This study tested the association of the Area Deprivation Index (ADI), a neighborhood-based index of socioeconomic contextual disadvantage, with elderly obesity risk. We sampled 5066 Medicare beneficiaries at the University of Missouri between September 1, 2013 and September 1, 2014. We excluded patients with unknown street addresses, excluded body mass index (BMI) lower than 18 or higher than 62 as probable errors, and excluded patients with missing BMI data. We used a plot of simple proportions to examine the association between ADI and prevalence of obesity, defined as BMI of 30 and over. We found that obesity was significantly less prevalent in the least-disadvantaged ADI decile (decile 1) than in all other deciles (p < 0.05) except decile 7. Obesity prevalence within the other deciles (2-6 and 8-10) was not significantly distinguishable except that decile 2 was significantly lower than decile 4. Patients with missing BMI data were more likely to reside in the most disadvantaged areas. There was a positive association between neighborhood disadvantage and obesity in this Midwestern United States Medicare population. The association of missing BMI information with neighborhood disadvantage may reflect unmeasured gaps in care delivery to the most disadvantaged patients. These preliminary results support the continued study of neighborhood socioeconomic measures to identify health disparities in populations.

High efficiency hydrodynamic bacterial electrotransformation.

Synthetic biology holds great potential for addressing pressing challenges for mankind and our planet. One technical challenge in tapping into the full potential of synthetic biology is the low efficiency and low throughput of genetic transformation for many types of cells. In this paper, we discuss a novel microfluidic system for improving bacterial electrotransformation efficiency and throughput. Our microfluidic system is comprised of non-uniform constrictions in microchannels to facilitate high electric fields with relatively small applied voltages to induce electroporation. Additionally, the microfluidic device has regions of low electric field to assist in electrophoretic transport of nucleic acids into the cells. The device features hydrodynamically controlled electric fields that allow cells to experience a time dependent electric field that is otherwise difficult to achieve using standard electronics. Results suggest that transformation efficiency can be increased by ∼4×, while throughput can increase by 100-1000× compared to traditional electroporation cuvettes. This work will enable high-throughput and high efficiency genetic transformation of microbes, facilitating accelerated development of genetically engineered organisms.

The Effect of Neighborhood Disadvantage on Diabetes Prevalence.

Patient socioeconomic data is not usually included in medical records nor easily accessible to clinicians, yet socioeconomic disadvantage can be an important guide to disease management. This study evaluated the neighborhood-level Area Deprivation Index (ADI), a measure of neighborhood socioeconomic disadvantage, as a factor in diabetes mellitus prevalence. Electronic health records at an academic hospital system identified 4,770 Medicare beneficiaries. Logistic regression of diabetes diagnosis (ICD9=250.x) against ADI quintile, age, gender, and race/ethnicity found all these patient characteristics to be significantly associated. Diabetes prevalence was lowest in the least disadvantaged quintile of neighborhoods after adjusting for age, gender, and race/ethnicity. The positive non-linear association of diabetes prevalence with ADI demonstrates the power of this index to practically quantify socioeconomic disadvantage. The ADI may be suitable for clinical decision support, and for informing the policy changes which are needed to reduce socioeconomic disparities in diabetes prevalence and other health outcomes.