Aspirin use for primary prevention among US adults with and without elevated Lipoprotein(a).

Objective: Lipoprotein(a) [Lp(a)] is an atherogenic and prothrombotic lipoprotein associated with atherosclerotic cardiovascular disease (ASCVD). We assessed the association between regular aspirin use and ASCVD mortality among individuals with versus without elevated Lp(a) in a nationally representative US cohort. Methods: Eligible participants were aged 40-70 years without clinical ASCVD, reported on aspirin use, and had Lp(a) measurements from the Third National Health and Nutrition Examination Survey (NHANES III, 1988-1994), the only cycle of this nationally representative US cohort to measure Lp(a). Regular aspirin use was defined as taking aspirin ≥30 times in the previous month. Using NHANES III linked mortality records and weighted Cox proportional hazards regression, the association between regular aspirin use and ASCVD mortality was observed in those with and without elevated Lp(a) (≥50 versus <50 mg/dL) over a median 26-year follow-up. Results: Among 2,990 persons meeting inclusion criteria (∼73 million US adults), the mean age was 50 years, 86% were non-Hispanic White, 9% were non-Hispanic Black, 53% were female, and 7% reported regular aspirin use. The median Lp(a) was 14 mg/dL and the proportion with elevated Lp(a) was similar among those with versus without regular aspirin use (15.1% versus 21.9%, p = 0.16). Among individuals with elevated Lp(a), the incidence of ASCVD mortality per 1,000 person-years was lower for those with versus without regular aspirin use (1.2, 95% CI: 0.1-2.3 versus 3.9, 95% CI: 2.8-4.9). In multivariable modeling, regular aspirin use was associated with a 52% lower risk of ASCVD mortality among individuals with elevated Lp(a) (HR=0.48, 95% CI: 0.28-0.83), but not for those without elevated Lp(a) (HR=1.01, 95% CI: 0.81-1.25; p-interaction=0.001). Conclusion: Regular aspirin use was associated with significantly lower ASCVD mortality in adults without clinical ASCVD who had elevated Lp(a). These findings may have clinical and public health implications for aspirin utilization in primary prevention.

Prevalence estimates and factors associated with violence among older adults: National Intimate Partner and Sexual Violence (NISVS) Survey, 2016/2017.

Abuse of older adults is a public health problem. The National Intimate Partner and Sexual Violence Survey (NISVS) is a nationally-representative, telephone survey for non-institutionalized adults in the United States. To determine the prevalence and factors of intimate partner psychological aggression and physical violence and sexual violence by any perpetrator against older adults, we analyzed NISVS 2016/2017 data (n = 10,171, aged ≥ 60 years). Past 12-month prevalence of psychological aggression, physical violence, and sexual violence was 2.1%, 0.8%, and 1.7%, respectively. Odds of psychological aggression were significantly higher among those with hearing or vision impairment, and lower among those aged ≥70 years. Odds of physical violence were significantly higher for males and for those with hearing or vision impairment. Odds of sexual violence were significantly higher for unpartnered individuals and those with cognitive impairment; and lower for those aged ≥ 70 years. Epidemiologic studies of violence against older adults can inform population-specific prevention strategies.

Predicting Food Sources of Listeria monocytogenes Based on Genomic Profiling Using Random Forest Model.

Listeria monocytogenes can cause severe foodborne illness, including miscarriage during pregnancy or death in newborn infants. When outbreaks of L. monocytogenes illness occur, it may be possible to determine the food source of the outbreak. However, most reported L. monocytogenes illnesses do not occur as part of a recognized outbreak and most of the time the food source of sporadic L. monocytogenes illness in people cannot be determined. In the United States, L. monocytogenes isolates from patients, foods, and environments are routinely sequenced and analyzed by whole genome multilocus sequence typing (wgMLST) for outbreak detection by PulseNet, the national molecular surveillance system for foodborne illnesses. We investigated whether machine learning approaches applied to wgMLST allele call data could assist in attribution analysis of food source of L. monocytogenes isolates. We compiled isolates with a known source from five food categories (dairy, fruit, meat, seafood, and vegetable) using the metadata of L. monocytogenes isolates in PulseNet, deduplicated closely genetically related isolates, and developed random forest models to predict the food sources of isolates. Prediction accuracy of the final model varied across the food categories; it was highest for meat (65%), followed by fruit (45%), vegetable (45%), dairy (44%), and seafood (37%); overall accuracy was 49%, compared with the naive prediction accuracy of 28%. Our results show that random forest can be used to capture genetically complex features of high-resolution wgMLST for attribution of isolates to their sources.

Shiga Toxin-Producing Escherichia coli Outbreaks in the United States, 2010-2017.

Shiga toxin-producing Escherichia coli (STEC) cause illnesses ranging from mild diarrhea to ischemic colitis and hemolytic uremic syndrome (HUS); serogroup O157 is the most common cause. We describe the epidemiology and transmission routes for U.S. STEC outbreaks during 2010-2017. Health departments reported 466 STEC outbreaks affecting 4769 persons; 459 outbreaks had a serogroup identified (330 O157, 124 non-O157, 5 both). Among these, 361 (77%) had a known transmission route: 200 foodborne (44% of O157 outbreaks, 41% of non-O157 outbreaks), 87 person-to-person (16%, 24%), 49 animal contact (11%, 9%), 20 water (4%, 5%), and 5 environmental contamination (2%, 0%). The most common food category implicated was vegetable row crops. The distribution of O157 and non-O157 outbreaks varied by age, sex, and severity. A significantly higher percentage of STEC O157 than non-O157 outbreaks were transmitted by beef (p = 0.02). STEC O157 outbreaks also had significantly higher rates of hospitalization and HUS (p < 0.001).

Recency-Weighted Statistical Modeling Approach to Attribute Illnesses Caused by 4 Pathogens to Food Sources Using Outbreak Data, United States.

Foodborne illness source attribution is foundational to a risk-based food safety system. We describe a method for attributing US foodborne illnesses caused by nontyphoidal Salmonella enterica, Escherichia coli O157, Listeria monocytogenes, and Campylobacter to 17 food categories using statistical modeling of outbreak data. This method adjusts for epidemiologic factors associated with outbreak size, down-weights older outbreaks, and estimates credibility intervals. On the basis of 952 reported outbreaks and 32,802 illnesses during 1998-2012, we attribute 77% of foodborne Salmonella illnesses to 7 food categories (seeded vegetables, eggs, chicken, other produce, pork, beef, and fruits), 82% of E. coli O157 illnesses to beef and vegetable row crops, 81% of L. monocytogenes illnesses to fruits and dairy, and 74% of Campylobacter illnesses to dairy and chicken. However, because Campylobacter outbreaks probably overrepresent dairy as a source of nonoutbreak campylobacteriosis, we caution against using these Campylobacter attribution estimates without further adjustment.