Given it has been nearly 10 years since the last published estimate of diarrhea morbidity, there is a great need for updated estimates of incidence rates for calculating burden of disease and for planning at the country level.
Using U.S. National Health and Nutrition Examination Survey data (1999 2008), we calculated the burden of dysglycemia (i.e., prediabetes or diabetes from measures of fasting glucose, A1C, and self-report) in nonpregnant women of childbearing age (15 49 years) by race/ethnicity status.
We scanned the aortae with an Olympus macroscope (Olympus, Center Valley, PA, USA), analyzed them using MetaMorph (Molecular Devices, Sunnyvale, CA, USA) and calculated atheroma burden as the percentage of total aortic area.
For PM2.5, we calculated the burden of disease for cardiopulmonary mortality, lung cancer mortality, total nonviolent mortality, chronic bronchitis and restricted-activity days [defined by Hurley et al. (2005)].
Although these reports and others have calculated disease burden related to poor water supply, sanitation, and hygiene there has not been a quantification of the improvement in health related outcomes due to improvements in water supply and sanitation.
We calculated the burden of private mutations predicted by different demographic models, and compared with empirical estimates based on data from the NHLBI Exome Sequencing Project and data from the Neutral Regions (NR) dataset.
To account for differential time over which glycemic burden was calculated, we divided total burden by the number of months of observation to yield average monthly glycemic burden (AMGB).
Reductions in the larval burden were calculated as follows: worm burden reduction rate = (1 − mean number of larvae per gram muscle in vaccinated mice/mean number of larvae per gram muscle in control mice) × 100%.
