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While there is strong evidence that maternal smallpox infection can cause foetal loss, it is not clear whether smallpox infections were a demographically important cause of stillbirths historically. In this paper, we use parish-level data from the Swedish Tabellverket data set for 1780–1839 to test the effect of smallpox on stillbirths quantitatively, analysing periods before and after the introduction of vaccination in 1802. We find that smallpox infection was not a major cause of stillbirths before 1820, because most women contracted smallpox as children and were therefore not susceptible during pregnancy. We do find a small, statistically significant effect of smallpox on stillbirths from 1820 to 1839, when waning immunity from vaccination put a greater share of pregnant women at risk of contracting smallpox. However, the reduced prevalence of smallpox in this period limited its impact on stillbirths. Thus, smallpox was not an important driver of historical stillbirth trends. [ABSTRACT FROM AUTHOR]

Introduction Injuries are the leading cause of medical encounters with over 2 million medical encounters for musculoskeletal (MSK) conditions and over 700,000 acute injuries per year. Musculoskeletal injuries (MSKIs) are by far the leading health and readiness problem of the U.S. Military. The Proceedings of the International Collaborative Effort on Injury Statistics published a list of 12 data elements deemed necessary for injury prevention in the civilian population; however, there are no standardized list of common data elements (CDEs) across the DoD specifically designed to study MSKIs in the Military Health System (MHS). This study aims to address this gap in knowledge by defining CDEs across the DoD for MSKIs, establishing a CDE dictionary, and compiling other necessary information to quantify MSKI disease burden in the MHS. Materials and Methods Between November 2022 and March 2023, we conducted an environmental scan of current MSKI data metrics across the DoD. We used snowball sampling with active engagement of groups housing datasets that contained MSKI data elements to determine CDEs as well as information on readiness databases across the DoD containing up-to-date personnel information on disease, hospitalizations, limited duty days (LDDs), and deployability status for all military personnel, as well as MSKI-specific measures from the MHS Dashboard which tracks key performance measures. Results We identified 8 unique databases: 5 containing demographic and diagnostic information (Defense Medical Surveillance System, Medical Assessment and Readiness Systems, Military Health System Data Repository, Person-Data Environment, and Soldier Performance, Health, and Readiness Database); and 3 containing LDD information (Aeromedical Services Information Management System, eProfile, and Limited Duty Sailor Marines Readiness Tracker). Nine CDEs were identified: DoD number, sex, race, ethnicity, branch of service, rank, diagnosis, Common Procedural Terminology coding, and cause codes, as they may be captured in any database that is a derivative of the Military Health System Data Repository. Medical Assessment and Readiness Systems contained most variables of interest, excluding injury/place of region and time in service. The Limited Duty Sailor Marines Readiness Tracker contains a variable corresponding to "days on limited duty." The Aeromedical Services Information Management System uses the "release date" and "profile date" to calculate LDDs. The eProfile system determines LDDs by the difference between the "expiration date" and "approved date." In addition, we identified 2 measures on the MHS Dashboard. One measures the percentage of service members (SMs) who are on limited duty for longer than 90 days because of an MSKI and the other tracks the percentage of SMs that are not medically ready for deployment because of a deployment-limiting medical condition. Conclusions This article identifies core data elements needed to understand and prevent MSKIs and where these data elements can be found. These elements should inform researchers and result in evidence-informed policy decisions supporting SM health to optimize military force readiness. [ABSTRACT FROM AUTHOR]

IntroductionInjury is a significant and increasingly common cause of morbidity and mortality in sub-Saharan Africa; however, the social and economic factors underlying these trends are not well understood. We evaluated the relationship between socioeconomic status (SES) and trauma outcomes using a prospective registry of patients presenting to the largest trauma hospital in Yaoundé, Cameroon.MethodsTrauma patients (n=2855) presenting to the emergency ward at Central Hospital, Yaoundé between April 15 and October 15, 2009 were surveyed regarding demographic and socioeconomic background, nature and severity of injuries, treatment, and disposition. A wealth score was estimated for each patient, corresponding to an SES index constructed using principle components analysis of the urban Cameroonian Demographic and Health Survey. Logistic regression was used to evaluate the effects of SES on care-seeking behaviour, injury severity, and treatment outcome.Main outcome measuresSES wealth score, care-seeking prior to visiting hospital, injury severity, treatment outcome.ResultsPatients aged 1-89 presented with road traffic injuries (59.83%), falls (7.76%), and penetrating trauma (6.16%), and had higher SES than the broader urban Cameroonian population. Within the Yaoundé sample, being in the lowest SES quintile was associated with an increased likelihood of having sought care elsewhere before presenting to the hospital (aOR=3.28, p