On August 31, 2021, this report was posted as an MMWR Early Release on the MMWR website (https://www.cdc.gov/mmwr).Viral infections are a common cause of myocarditis, an inflammation of the heart muscle (myocardium) that can result in hospitalization, heart failure, and sudden death (1). Emerging data suggest an association between COVID-19 and myocarditis (2-5). CDC assessed this association using a large, U.S. hospital-based administrative database of health care encounters from >900 hospitals. Myocarditis inpatient encounters were 42.3% higher in 2020 than in 2019. During March 2020-January 2021, the period that coincided with the COVID-19 pandemic, the risk for myocarditis was 0.146% among patients diagnosed with COVID-19 during an inpatient or hospital-based outpatient encounter and 0.009% among patients who were not diagnosed with COVID-19. After adjusting for patient and hospital characteristics, patients with COVID-19 during March 2020-January 2021 had, on average, 15.7 times the risk for myocarditis compared with those without COVID-19 (95% confidence interval [CI] = 14.1-17.2); by age, risk ratios ranged from approximately 7.0 for patients aged 16-39 years to >30.0 for patients aged <16 years or ≥75 years. Overall, myocarditis was uncommon among persons with and without COVID-19; however, COVID-19 was significantly associated with an increased risk for myocarditis, with risk varying by age group. These findings underscore the importance of implementing evidence-based COVID-19 prevention strategies, including vaccination, to reduce the public health impact of COVID-19 and its associated complications.Data for this study were obtained from the Premier Healthcare Database Special COVID-19 Release (PHD-SR), a large hospital-based administrative database. † The monthly * These authors contributed equally to this report. † PHD-SR, formerly known as the PHD COVID-19 Database, is a large U.S. hospital-based all-payer database that includes inpatient and hospital-based outpatient (e.g., emergency department or clinic) health care encounters from >900 geographically diverse, nonprofit, nongovernmental, community, and teaching hospitals and health systems from rural and urban areas. PHD-SR represents approximately 20% of inpatient admissions in the United States.

Persons from racial and ethnic minority groups are disproportionately affected by COVID-19, including experiencing increased risk for infection (1), hospitalization (2,3), and death (4,5). Using administrative discharge data, CDC assessed monthly trends in the proportion of hospitalized patients with COVID-19 among racial and ethnic groups in the United States during March-December 2020 by U.S. Census region. Cumulative and monthly age-adjusted COVID-19 proportionate hospitalization ratios (aPHRs) were calculated for racial and ethnic minority patients relative to non-Hispanic White patients. Within each of the four U.S. Census regions, the cumulative aPHR was highest for Hispanic or Latino patients (range = 2.7-3.9). Racial and ethnic disparities in COVID-19 hospitalization were largest during May-July 2020; the peak monthly aPHR among Hispanic or Latino patients was >9.0 in the West and Midwest, >6.0 in the South, and >3.0 in the Northeast. The aPHRs declined for most racial and ethnic groups during July-November 2020 but increased for some racial and ethnic groups in some regions during December. Disparities in COVID-19 hospitalization by race/ethnicity varied by region and became less pronounced over the course of the pandemic, as COVID-19 hospitalizations increased among non-Hispanic White persons. Identification of specific social determinants of health that contribute to geographic and temporal differences in racial and ethnic disparities at the local level can help guide tailored public health prevention strategies and equitable allocation of resources, including COVID-19 vaccination, to address COVID-19-related health disparities and can inform approaches to achieve greater health equity during future public health threats.Data were obtained from the Premier Healthcare Database Special COVID-19 Release (PHD-SR),* an all-payer, administrative database containing patient-level discharge records (including discharges ending in death) from more than 800 nongovernmental, community, and teaching hospitals across the United States. The database represents 20% of U.S. hospital admissions. Analyses were limited to * Data in PHD-SR, formerly known as the PHD COVID-19 Database, are released every 2 weeks; release date March 2

Objectives People with disabilities are known to experience disparities in behavioral health risk factors including smoking and obesity. What is unknown is how disability, race/ethnicity, and socioeconomic status combine to affect prevalence of these health behaviors. We assessed the association between race/ethnicity, socio-economic factors (income and education), and disability on two behavioral health risk factors. Methods Data from the 2007–2010 Behavioral Risk Factor Surveillance System were used to determine prevalence of cigarette smoking and obesity by disability status, further stratified by race and ethnicity as well as income and education. Logistic regression was used to determine associations of income and education with the two behavioral health risk factors, stratified by race and ethnicity. Results Prevalence of disability by race and ethnicity ranged from 10.1 % of Asian adults to 31.0 % of American Indian/ Alaska Native (AIAN) adults. Smoking prevalence increased with decreasing levels of income and education for most racial and ethnic groups, with over half of white (52.4 %) and AIAN adults (59.3 %) with less than a high school education reporting current smoking. Education was inversely associated with obesity among white, black, and Hispanic adults with a disability. Conclusion Smoking and obesity varied by race and ethnicity and socioeconomic factors (income and education) among people with disabilities. Our findings suggest that disparities experienced by adults with disabilities may be compounded by disparities associated with race, ethnicity, and socioeconomic factors. This knowledge may help programs in formulating health promotion strategies targeting people at increased risk for smoking and obesity, inclusive of those with disabilities.