Obesity prevalence in the United States is inversely associated with elevation and urbanization, after adjusting for temperature, diet, physical activity, smoking and demographic factors.

Mild traumatic injuries to the brain (e.g., concussion) are common and have been recognized since antiquity, although definitions have varied historically. Nonetheless, studying the epidemiology of concussion helps clarify the overall importance, risk factors, and at-risk populations for this injury. The present review will focus on recent findings related to the epidemiology of concussion including definition controversies, incidence, and patterns in the population overall and in the military and athlete populations specifically. Finally, as this is an area of active research, we will discuss how future epidemiologic observations hold promise for gaining greater clarity about concussion and mild traumatic brain injury.

BackgroundPhysical inactivity, ambient air pollution and obesity are modifiable risk factors for non-communicable diseases, with the first accounting for 10% of premature deaths worldwide. Although community level interventions may target each simultaneously, research on the relationship between these risk factors is lacking.ObjectivesAfter comparing spatial interpolation methods to determine the best predictor for particulate matter (PM2.5; PM10) and ozone (O3) exposures throughout the U.S., we evaluated the cross-sectional association of ambient air pollution with leisure-time physical inactivity among adults.MethodsIn this cross-sectional study, we assessed leisure-time physical inactivity using individual self-reported survey data from the Centers for Disease Control and Prevention's 2011 Behavioral Risk Factor Surveillance System. These data were combined with county-level U.S. Environmental Protection Agency air pollution exposure estimates using two interpolation methods (Inverse Distance Weighting and Empirical Bayesian Kriging). Finally, we evaluated whether those exposed to higher levels of air pollution were less active by performing logistic regression, adjusting for demographic and behavioral risk factors, and after stratifying by body weight category.ResultsWith Empirical Bayesian Kriging air pollution values, we estimated a statistically significant 16–35% relative increase in the odds of leisure-time physical inactivity per exposure class increase of PM2.5 in the fully adjusted model across the normal weight respondents (p-value<0.0001). Evidence suggested a relationship between the increasing dose of PM2.5 exposure and the increasing odds of physical inactivity.ConclusionsIn a nationally representative, cross-sectional sample, increased community level air pollution is associated with reduced leisure-time physical activity particularly among the normal weight. Although our design precludes a causal inference, these results provide additional evidence that air pollution should be investigated as an environmental determinant of inactivity.

We sought to evaluate whether residence at high altitude is associated with the development of obesity among those at increased risk of becoming obese. Obesity, a leading global health priority, is often refractory to care. A potentially novel intervention is hypoxia, which has demonstrated positive long-term metabolic effects in rats. Whether or not high altitude residence confers benefit in humans, however, remains unknown. Using a quasi-experimental, retrospective study design, we observed all outpatient medical encounters for overweight active component enlisted service members in the U.S. Army or Air Force from January 2006 to December 2012 who were stationed in the United States. We compared high altitude (>1.96 kilometers above sea level) duty assignment with low altitude (<0.98 kilometers). The outcome of interest was obesity related ICD-9 codes (278.00-01, V85.3x-V85.54) by Cox regression. We found service members had a lower hazard ratio (HR) of incident obesity diagnosis if stationed at high altitude as compared to low altitude (HR 0.59, 95% confidence interval [CI] 0.54–0.65; p<0.001). Using geographic distribution of obesity prevalence among civilians throughout the U.S. as a covariate (as measured by the Centers for Disease Control and Prevention and the REGARDS study) also predicted obesity onset among service members. In conclusion, high altitude residence predicts lower rates of new obesity diagnoses among overweight service members in the U.S. Army and Air Force. Future studies should assign exposure using randomization, clarify the mechanism(s) of this relationship, and assess the net balance of harms and benefits of high altitude on obesity prevention.

Numerous microbial agents cause obesity in various experimental models-a phenomena known as infectobesity. Several of the same agents alter metabolic function in human cells and are associated with human obesity or metabolic dysfunction in humans. We address the evidence for a role in the genesis of obesity for viral agents in five broad categories: adenoviridae, herpesviridae, phages, transmissible spongiform encephalopathies (slow virus), and other encephalitides and hepatitides. Despite the importance of this topic area, there are many persistent knowledge gaps that need to be resolved. We discuss factors motivating further research and recommend that future infectobesity investigation should be more comprehensive, leveraged, interventional, and patient-centered.

Introduction The coronavirus disease 2019 (COVID-19) pandemic is a global public health emergency causing a disparate burden of death and disability around the world. The molecular characteristics of the virus that predict better or worse outcome are largely still being discovered. Methods We downloaded 155,958 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from GISAID. Of these genomes, 3,637 samples included useable metadata on patient outcomes. Using this subset, we evaluated whether SARS-CoV-2 viral genomic variants improved prediction of reported severity beyond age and region. First, we established whether including genomic variants as model features meaningfully increased predictive power of our model. Next, we evaluated specific variants in order to determine the magnitude of association with severity and the frequency of these variants among SARS-CoV-2 genomes. Results Logistic regression models that included viral genomic variants outperformed other models (AUC = 0.91 as compared with 0.68 for age and gender alone; p &lt; 0.001). Among individual variants, we found 17 single nucleotide variants in SARS-CoV-2 have more than two-fold greater odds of being associated with higher severity and 67 variants associated with ≤0.5 times the odds of severity. The median frequency of associated variants was 0.15% (interquartile range 0.09%-0.45%). Altogether 85% of genomes had at least one variant associated with patient outcome. Conclusion Numerous SARS-CoV-2 variants have two-fold or greater association with odds of mild or severe outcome and collectively, these variants are common. In addition to comprehensive mitigation efforts, public health measures should be prioritized to control the more severe manifestations of COVID-19 and the transmission chains linked to these severe cases. Lay Summary This study explores which, if any, SARS-CoV-2 viral genomic variants are associated with mild or severe COVID-19 patient outcomes. Our results suggest that there are common genomic variants in SARS-CoV-2 that are more often associated with negative patient outcomes, which may impact downstream public health measures.

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several adenoviruses increase adiposity in animals and are associated with obesity in humans. There are critical gaps in the literature needing further investigation including evaluation of other adenovirus subtypes and better research designs to improve the strength of causal inferences.