Early mortality experience in a large military cohort and a comparison of mortality data sources

<p>Abstract</p> <p>Background</p> <p>Complete and accurate ascertainment of mortality is critically important in any longitudinal study. Tracking of mortality is particularly essential among US military members because of unique occupational exposures (e.g., worldwide deployments as well as combat experiences). Our study objectives were to describe the early mortality experience of Panel 1 of the Millennium Cohort, consisting of participants in a 21-year prospective study of US military service members, and to assess data sources used to ascertain mortality.</p> <p>Methods</p> <p>A population-based random sample (n = 256,400) of all US military service members on service rosters as of October 1, 2000, was selected for study recruitment. Among this original sample, 214,388 had valid mailing addresses, were not in the pilot study, and comprised the group referred to in this study as the invited sample. Panel 1 participants were enrolled from 2001 to 2003, represented all armed service branches, and included active-duty, Reserve, and National Guard members. Crude death rates, as well as age- and sex-adjusted overall and age-adjusted, category-specific death rates were calculated and compared for participants (n = 77,047) and non-participants (n = 137,341) based on data from the Social Security Administration Death Master File, Department of Veterans Affairs (VA) files, and the Department of Defense Medical Mortality Registry, 2001-2006. Numbers of deaths identified by these three data sources, as well as the National Death Index, were compared for 2001-2004.</p> <p>Results</p> <p>There were 341 deaths among the participants for a crude death rate of 80.7 per 100,000 person-years (95% confidence interval [CI]: 72.2,89.3) compared to 820 deaths and a crude death rate of 113.2 per 100,000 person-years (95% CI: 105.4, 120.9) for non-participants. Age-adjusted, category-specific death rates highlighted consistently higher rates among study non-participants. Although there were advantages and disadvantages for each data source, the VA mortality files identified the largest number of deaths (97%).</p> <p>Conclusions</p> <p>The difference in crude and adjusted death rates between Panel 1 participants and non-participants may reflect healthier segments of the military having the opportunity and choosing to participate. In our study population, mortality information was best captured using multiple data sources.</p

Ecological approaches in veterinary epidemiology: mapping the risk of bat-borne rabies using vegetation indices and night-time light satellite imagery

Rabies remains a disease of significant public health concern. In the Americas, bats are an important source of rabies for pets, livestock, and humans. For effective rabies control and prevention, identifying potential areas for disease occurrence is critical to guide future research, inform public health policies, and design interventions. To anticipate zoonotic infectious diseases distribution at coarse scale, veterinary epidemiology needs to advance via exploring current geographic ecology tools and data using a biological approach. We analyzed bat-borne rabies reports in Chile from 2002 to 2012 to establish associations between rabies occurrence and environmental factors to generate an ecological niche model (ENM). The main rabies reservoir in Chile is the bat species Tadarida brasiliensis; we mapped 726 occurrences of rabies virus variant AgV4 in this bat species and integrated them with contemporary Normalized Difference Vegetation Index (NDVI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS). The correct prediction of areas with rabies in bats and the reliable anticipation of human rabies in our study illustrate the usefulness of ENM for mapping rabies and other zoonotic pathogens. Additionally, we highlight critical issues with selection of environmental variables, methods for model validation, and consideration of sampling bias. Indeed, models with weak or incorrect validation approaches should be interpreted with caution. In conclusion, ecological niche modeling applications for mapping disease risk at coarse geographic scales have a promising future, especially with refinement and enrichment of models with additional information, such as night-time light data, which increased substantially the model’s ability to anticipate human rabies

Accuracy and completeness of mortality data in the Department of Veterans Affairs

<p>Abstract</p> <p>Background</p> <p>One of the national mortality databases in the U.S. is the Beneficiary Identification and Record Locator Subsystem (BIRLS) Death File that contains death dates of those who have received any benefits from the Department of Veterans Affairs (VA). The completeness of this database was shown to vary widely from cohort to cohort in previous studies. Three other sources of death dates are available in the VA that can complement the BIRLS Death File. The objective of this study is to evaluate the completeness and accuracy of death dates in the four sources available in the VA and to examine whether these four sources can be combined into a database with improved completeness and accuracy.</p> <p>Methods</p> <p>A random sample of 3,000 was drawn from 8.3 million veterans who received benefits from the VA between 1997 and 1999 and were alive on January 1, 1999 according to at least one source. Death dates found in BIRLS Death File, Medical SAS Inpatient Datasets, Medicare Vital Status, and Social Security Administration (SSA) Death Master File were compared with dates obtained from the National Death Index. A combined dataset from these sources was also compared with National Death Index dates.</p> <p>Results</p> <p>Compared with the National Death Index, sensitivity (or the percentage of death dates correctly recorded in a source) was 77.4% for BIRLS Death File, 12.0% for Medical SAS Inpatient Datasets, 83.2% for Medicare Vital Status, and 92.1% for SSA Death Master File. Over 95% of death dates in these sources agreed exactly with dates from the National Death Index. Death dates in the combined dataset demonstrated 98.3% sensitivity and 97.6% exact agreement with dates from the National Death Index.</p> <p>Conclusion</p> <p>The BIRLS Death File is not an adequate source of mortality data for the VA population due to incompleteness. When the four sources of mortality data are carefully combined, the resulting dataset can provide more timely data for death ascertainment than the National Death Index and has comparable accuracy and completeness.</p

Ideology and the Market Metaphor in Rational Choice Theory of Religion : A Rhetorical Critique of “Religious Economies”

Peer reviewedPostprin