How does cytomegalovirus factor into diseases of aging and vaccine responses, and by what mechanisms?

Cytomegalovirus (CMV) is an important pathogen for both clinical and population settings. There is a growing body of research implicating CMV in multiple health outcomes across the life course. At the same time, there is mounting evidence that individuals living in poverty are more likely to be exposed to CMV and more likely to experience many of the chronic conditions for which CMV has been implicated. Further research on the causal role of CMV for health and well-being is needed. However, the strong evidence implicating CMV in type 2 diabetes, autoimmunity, cancer, cardiovascular disease, vaccination, and age-related alterations in immune function warrants clinical and public health action. This imperative is even higher among individuals living in socioeconomically disadvantaged settings and those exposed to high levels of chronic psychosocial stress

P1–222: ApoE4 lipoprotein 4 reduces risk of dementia from high sensitivity C–reactive protein

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/152633/1/alzjjalz200605599.pd

Identifying and estimating effects of sustained interventions under parallel trends assumptions

Many research questions in public health and medicine concern sustained interventions in populations defined by substantive priorities. Existing methods to answer such questions typically require a measured covariate set sufficient to control confounding, which can be questionable in observational studies. Differences-in-differences relies instead on the parallel trends assumption, allowing for some types of time-invariant unmeasured confounding. However, most existing difference-in-differences implementations are limited to point treatments in restricted subpopulations. We derive identification results for population effects of sustained treatments under parallel trends assumptions. In particular, in settings where all individuals begin follow-up with exposure status consistent with the treatment plan of interest but may deviate at later times, a version of Robins' g-formula identifies the intervention-specific mean under SUTVA, positivity, and parallel trends. We develop consistent asymptotically normal estimators based on inverse-probability weighting, outcome regression, and a double robust estimator based on targeted maximum likelihood. Simulation studies confirm theoretical results and support the use of the proposed estimators at realistic sample sizes. As an example, the methods are used to estimate the effect of a hypothetical federal stay-at-home order on all-cause mortality during the COVID-19 pandemic in spring 2020 in the United States.Comment: 15 pages, 2 figure

Helicobacter pylori infection is associated with an increased rate of diabetes.

ObjectiveChronic infections could be contributing to the socioeconomic gradient in chronic diseases. Although chronic infections have been associated with increased levels of inflammatory cytokines and cardiovascular disease, there is limited evidence on how infections affect risk of diabetes.Research design and methodsWe examined the association between serological evidence of chronic viral and bacterial infections and incident diabetes in a prospective cohort of Latino elderly. We analyzed data on 782 individuals aged >60 years and diabetes-free in 1998-1999, whose blood was tested for antibodies to herpes simplex virus 1, varicella virus, cytomegalovirus, Helicobacter pylori, and Toxoplasma gondii and who were followed until June 2008. We used Cox proportional hazards regression to estimate the relative incidence rate of diabetes by serostatus, with adjustment for age, sex, education, cardiovascular disease, smoking, and cholesterol levels.ResultsIndividuals seropositive for herpes simplex virus 1, varicella virus, cytomegalovirus, and T. gondii did not show an increased rate of diabetes, whereas those who were seropositive for H. pylori at enrollment were 2.7 times more likely at any given time to develop diabetes than seronegative individuals (hazard ratio 2.69 [95% CI 1.10-6.60]). Controlling for insulin resistance, C-reactive protein and interleukin-6 did not attenuate the effect of H. pylori infection.ConclusionsWe demonstrated for the first time that H. pylori infection leads to an increased rate of incident diabetes in a prospective cohort study. Our findings implicate a potential role for antibiotic and gastrointestinal treatment in preventing diabetes

Did national folic acid fortification reduce socioeconomic and racial disparities in folate status in the US?

http://deepblue.lib.umich.edu/bitstream/2027.42/61197/1/Dowd, J. Aiello, A. Did national folic acid fortificationhtm.htmhttp://deepblue.lib.umich.edu/bitstream/2027.42/61197/4/Dowd_Aiello_Didnationalfolicacid.pd

Healthcare Workers’ Hand Microbiome May Mediate Carriage of Hospital Pathogens

One function of skin microbiota is to resist colonization and infection by external microorganisms. We sought to detect whether the structure of the hand microbiota of 34 healthcare workers (HCW) in a surgical intensive care unit mediates or modifies the relationship between demographic and behavioral factors and potential pathogen carriage on hands after accounting for pathogen exposure. We used a taxonomic screen (16S rRNA) to characterize the bacterial community, and qPCR to detect presence of Staphylococcus aureus, Enterococcus spp., methicillin-resistant Staphylococcus aureus (MRSA), and Candida albicans on their dominant hands. Hands were sampled weekly over a 3-week period. Age, hand hygiene, and work shift were significantly associated with potential pathogen carriage and the associations were pathogen dependent. Additionally, the overall hand microbiota structure was associated with the carriage of potential pathogens. Hand microbiota community structure may act as a biomarker of pathogen carriage, and modifying that structure may potentially limit pathogen carriage among HCW

Causal inference: the case of hygiene and health

http://deepblue.lib.umich.edu/bitstream/2027.42/55403/1/Causal inference The case of hygiene and health.pd

Systematic risk assessment methods for the infection control professional

http://deepblue.lib.umich.edu/bitstream/2027.42/55416/1/Larson E, Systematic risk assessment methods.pd