Previous studies suggested that almost one-third of U.S. adults did not plan to get a COVID-19 vaccine once it is available to them. The purpose of this study was to examine changes in vaccine inte...

The American Heart Association recommended a renewed focus on primordial prevention to reduce the development of risk factors for cardiovascular disease (CVD) as part of its 2020 Impact Goal to improve population cardiovascular health (CVH) by 20% and to reduce CVD mortality by 20%. For this reason, the American Heart Association developed a score describing CVH that incorporates measures of both lifestyle behaviors (smoking, diet, and physical activity) and risk factors (blood pressure level, body mass index [BMI, calculated as weight in kilograms divided by height in meters squared], and fasting total cholesterol and blood glucose concentrations) that are associated with higher risk of CVD.¹ Community-based studies indicate that higher CVH scores are associated with lower risk of diabetes, CVD, and all-cause mortality.^2-8 Higher CVH scores are also associated with lower levels of indicators of subclinical disease, greater telomere length, and better vascular function.^9-16 Despite the significance of the CVH score and the modifiable nature of its components, little is known about how the maintenance of individuals’ low or high CVH scores over time (ie, duration of CVH score) is associated with morbidity or mortality risks.

Data on proteomic and metabolomic signatures of healthy dietary patterns are limited. We evaluated the cross-sectional association of serum proteomic and metabolomic markers with three dietary patterns: the Alternative Healthy Eating Index (AHEI), the Dietary Approaches to Stop Hypertension (DASH) diet; and a Mediterranean-style (MDS) diet. We examined participants from the Framingham Offspring Study (mean age; 55 years; 52% women) who had complete proteomic (n = 1713) and metabolomic (n = 2284) data; using food frequency questionnaires to derive dietary pattern indices. Proteins and metabolites were quantified using the SomaScan platform and liquid chromatography/tandem mass spectrometry; respectively. We used multivariable-adjusted linear regression models to relate each dietary pattern index (independent variables) to each proteomic and metabolomic marker (dependent variables). Of the 1373 proteins; 103 were associated with at least one dietary pattern (48 with AHEI; 83 with DASH; and 8 with MDS; all false discovery rate [FDR] ≤ 0.05). We identified unique associations between dietary patterns and proteins (17 with AHEI; 52 with DASH; and 3 with MDS; all FDR ≤ 0.05). Significant proteins enriched biological pathways involved in cellular metabolism/proliferation and immune response/inflammation. Of the 216 metabolites; 65 were associated with at least one dietary pattern (38 with AHEI; 43 with DASH; and 50 with MDS; all FDR ≤ 0.05). All three dietary patterns were associated with a common signature of 24 metabolites (63% lipids). Proteins and metabolites associated with dietary patterns may help characterize intermediate phenotypes that provide insights into the molecular mechanisms mediating diet-related disease. Our findings warrant replication in independent populations

COVID-19 vaccine uptake has been suboptimal and disparities in uptake have exacerbated health inequities. It has been postulated that mistrust in the healthcare system and experiences of discrimination or unfair treatment in other settings may be barriers to uptake of the COVID-19 vaccine, although few studies to date have investigated medical mistrust and perceived discrimination together. We conducted a cross-sectional online survey between April 23-May 3, 2021, among a national sample of U.S. adults ages 18 years and older. We assessed receipt of and intention to be vaccinated for COVID-19 and associations with the validated Medical Mistrust Index and Everyday Discrimination Scale. 1449 individuals responded, of whom 70.2% either had ≥1 dose of COVID-19 vaccine or reported that they were ‘very’ or ‘somewhat’ likely to be vaccinated in the future. In bivariate analyses, vaccination status was significantly associated with age, race/ethnicity, education, income, employment, marital status, health insurance, and political party affiliation. In multivariable analyses comparing those who had ≥1 vaccine dose or were likely to get vaccinated in the future with those who had not had any vaccine doses or did not intend to be vaccinated, each additional point in the Medical Mistrust Index was independently associated with a 16% decrease in the odds of vaccination (adjusted odds ratio = 0.84; 95% confidence interval = 0.81, 0.86). Discriminatory experiences were not associated with vaccination behavior or intention in bivariate or multivariable analyses. Medical mistrust is significantly associated with vaccination status and intentions. Increasing uptake of COVID-19 vaccines will likely require substantive efforts on the part of public health and healthcare officials to build trust with those who are not yet fully vaccinated. We recommend that these efforts focus on building the ‘trustworthiness’ of these entities, an approach that will require a paradigm shift away from a focus on correcting individual beliefs and knowledge, to acknowledging and addressing the root causes underlying mistrust.