Disparities In Activity And Traffic Fatalities By Race/Ethnicity
Traffic fatalities remain a major public health challenge despite progress made during recent decades. A study described in the August 2022 issue of the American Journal of Preventive Medicine developed exposure-based estimates of fatalities per mile traveled for pedestrians, cyclists, and light-duty vehicle occupants. Exposure to traffic fatality differs by race/ethnicity group and by mode, indicating that adjustment for differential exposure is needed when estimating disparities. The authors found that fatality rates per 100 million miles traveled are systematically higher for Black and Hispanic Americans for all modes and notably higher for vulnerable modes (e.g., Black Americans died at more than four times the rate for White Americans while cycling, 33.71 [95% CI: 21.84, 73.83] compared with 7.53 [95% CI: 6.64, 8.69], and more than two times the rate while walking, 40.92 [95% CI: 36.58, 46.44] compared with 18.77 [95% CI: 17.30, 20.51]). These fatalities are a substantial and preventable public health challenge in the U.S.
Chronic Conditions Among Adults Aged 18─34 Years — United States, 2019
According to the July 29, 2022 issue of Morbidity and Mortality Weekly Reports, in 2019, 53.8% of adults aged 18─34 years had at least one chronic condition, and 22.3% had more than one condition. CDC analyzed data from the Behavioral Risk Factor Surveillance System (BRFSS) to measure prevalence of 11 chronic conditions among adults aged 18–34 years overall and by selected characteristics, and to measure prevalence of health-related risk behaviors by chronic condition status. The most prevalent conditions were obesity (25.5%), depression (21.3%), and high blood pressure (10.7%). Differences in the prevalence of having a chronic condition were most noticeable between young adults with a disability (75.8%) and without a disability (48.3%) and those who were unemployed (62.3%) and students (45.8%). Addressing conditions in young adulthood can help slow disease progression and improve well-being across the life span. Coordinated efforts might help improve the availability of evidence-based policies and interventions.
HEALTH TECHNOLOGY CORNER
Pan-Cancer Integrative Histology-Genomic Analysis Via Multi-Modal Deep Learning
The rapidly emerging field of computational pathology has demonstrated promise in developing objective prognostic models from histology images. Most prognostic models, however, either are based on histology or genomics alone and do not address how these data sources can be integrated to develop joint image-omic prognostic models. Additionally, identifying explainable morphological and molecular descriptors from these models that govern such prognosis is of interest. As reported on August 8, 2022 in the journal Cancer Cell, researchers at Brigham and Women’s Hospital in Boston used multimodal deep learning to examine pathology whole-slide images and molecular profile data jointly from 14 cancer types. A multimodal deep learning algorithm is able to fuse these heterogeneous modalities to predict outcomes and discover prognostic features that correlate with poor and favorable outcomes. Investigators presented all analyses for morphological and molecular correlates of patient prognosis across the 14 cancer types.
Effects Of Posture And Gastroparesis On Drug Dissolution In The Human Stomach
The oral route is the most common choice for drug administration because of several advantages, such as convenience and high patient compliance, and the demand and investment in research and development for oral drugs continue to grow. The rate of dissolution and gastric emptying of the dissolved active pharmaceutical ingredient (API) into the duodenum is modulated by gastric motility, physical properties of the pill, and the contents of the stomach, but current in vitro procedures for assessing dissolution of oral drugs are limited in their ability to recapitulate this process. A paper on August 9, 2022 in the journal Physics of Fluids describes how researchers at Johns Hopkins employed a biomimetic in silico simulator based on the realistic anatomy and morphology of the stomach to investigate and quantify the effect of body posture and stomach motility on drug bioavailability. Simulations show that changes in posture can potentially have a significant (up to 83%) effect on the emptying rate of the API into the duodenum.