Equitable access to affordable, effective, and safe obesity prevention and treatment remains a problem for many children and families in the U.S. In 2023, the American Academy of Pediatrics (AAP) published its first Clinical Practice Guideline (CPG) for pediatric obesity evaluation and treatment, aiding the field's awareness of effective approaches. CDC has supported the adapting and packaging of existing, effective Family Healthy Weight Programs that deliver CPG-recommended intensive behavioral treatment for kids. Currently, at least six family-centered programs are recognized by CDC and can be implemented in clinical and community settings to support child health. CDC and other national partners are coordinating the movement of these research-tested FHWPs into public health practice. This work includes implementing FHWPs in over 60 US communities and supporting national-level infrastructure improvements. CDC is committed to engaging with stakeholders to help scale proven strategies that ensure all children receive the care they need to thrive.

IMPORTANCE: Universal screening to identify unfavorable lipid levels is recommended for US children aged 9 to 11 years and adolescents aged 17 to 21 years (hereafter, young adults); however, screening benefits in these individuals have been questioned. Current use of lipid screening and prevalence of elevated lipid measurements among US youths is not well understood. OBJECTIVE: To investigate the prevalence of ambulatory pediatric lipid screening and elevated or abnormal lipid measurements among US screened youths by patient characteristic and test type. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study used data from the IQVIA Ambulatory Electronic Medical Record database and included youths aged 9 to 21 years with 1 or more valid measurement of height and weight during the observation period (2018-2021). Body mass index (BMI) was calculated and categorized using standard pediatric BMI percentiles (9-19 years) and adult BMI categories (≥20 years). The data were analyzed from October 6, 2022, to January 18, 2023. MAIN OUTCOMES AND MEASURES: Lipid measurements were defined as abnormal if 1 or more of the following test results was identified: total cholesterol (≥200 mg/dL), low-density lipoprotein cholesterol (≥130 mg/dL), very low-density lipoprotein cholesterol (≥31 mg/dL), non-high-density lipoprotein cholesterol (≥145 mg/dL), and triglycerides (≥100 mg/dL for children aged 9 years or ≥130 mg/dL for patients aged 10-21 years). After adjustment for age group, sex, race and ethnicity, and BMI category, adjusted prevalence ratios (aPRs) and 95% CIs were calculated. RESULTS: Among 3 226 002 youths (23.9% aged 9-11 years, 34.8% aged 12-16 years, and 41.3% aged 17-21 years; 1 723 292 females [53.4%]; 60.0% White patients, 9.5% Black patients, and 2.4% Asian patients), 11.3% had 1 or more documented lipid screening tests. The frequency of lipid screening increased by age group (9-11 years, 9.0%; 12-16 years, 11.1%; 17-21 years, 12.9%) and BMI category (range, 9.2% [healthy weight] to 21.9% [severe obesity]). Among those screened, 30.2% had abnormal lipid levels. Compared with youths with a healthy weight, prevalence of an abnormal result was higher among those with overweight (aPR, 1.58; 95% CI, 1.56-1.61), moderate obesity (aPR, 2.16; 95% CI, 2.14-2.19), and severe obesity (aPR, 2.53; 95% CI, 2.50-2.57). CONCLUSIONS AND RELEVANCE: In this cross-sectional study of prevalence of lipid screening among US youths aged 9 to 21 years, approximately 1 in 10 were screened. Among them, abnormal lipid levels were identified in 1 in 3 youths overall and 1 in 2 youths with severe obesity. Health care professionals should consider implementing lipid screening among children aged 9 to 11 years, young adults aged 17 to 21 years, and all youths at high cardiovascular risk.

Background Hypertension and diabetes are associated with increased COVID-19 severity. The association between level of control of these conditions and COVID-19 severity is less well understood. Methods and Results This retrospective cohort study identified adults with COVID-19, March 2020 to February 2022, in 43 US health systems in the National Patient-Centered Clinical Research Network. Hypertension control was categorized as blood pressure (BP) <130/80, 130 to 139/80 to 89, 140 to 159/90 to 99, or ≥160/100 mm Hg, and diabetes control as glycated hemoglobin <7%, 7% to <9%, ≥9%. Adjusted, pooled logistic regression assessed associations between hypertension and diabetes control and severe COVID-19 outcomes. Among 1 494 837 adults with COVID-19, 43% had hypertension and 12% had diabetes. Among patients with hypertension, the highest baseline BP was associated with greater odds of hospitalization (adjusted odds ratio [aOR], 1.30 [95% CI, 1.23-1.37] for BP ≥160/100 versus BP <130/80), critical care (aOR, 1.30 [95% CI, 1.21-1.40]), and mechanical ventilation (aOR, 1.32 [95% CI, 1.17-1.50]) but not mortality (aOR, 1.08 [95% CI, 0.98-1.12]). Among patients with diabetes, the highest glycated hemoglobin was associated with greater odds of hospitalization (aOR, 1.61 [95% CI, 1.47-1.76] for glycated hemoglobin ≥9% versus <7%), critical care (aOR, 1.42 [95% CI, 1.31-1.54]), mechanical ventilation (aOR, 1.12 [95% CI, 1.02-1.23]), and mortality (aOR, 1.18 [95% CI, 1.09-1.27]). Black and Hispanic adults were more likely than White adults to experience severe COVID-19 outcomes, independent of comorbidity score and control of hypertension or diabetes. Conclusions Among 1.5 million patients with COVID-19, higher BP and glycated hemoglobin were associated with more severe COVID-19 outcomes. Findings suggest that adults with poorest control of hypertension or diabetes might benefit from efforts to prevent and initiate early treatment of COVID-19.

IMPORTANCE: Information on the probability of weight loss among US adults with overweight or obesity is limited. OBJECTIVE: To assess the probability of 5% or greater weight loss, 10% or greater weight loss, body mass index (BMI) reduction to a lower BMI category, and BMI reduction to the healthy weight category among US adults with initial overweight or obesity overall and by sex and race. DESIGN, SETTING, AND PARTICIPANTS: This cohort study obtained data from the IQVIA ambulatory electronic medical records database. The sample consists of US ambulatory patients 17 years or older with at least 3 years of BMI information from January 1, 2009, to February 28, 2022. Minimum age was set at 17 years to allow for the change in BMI or weight starting at 18 years. Maximum age was censored at 70 years. EXPOSURES: Initial BMI (calculated as weight in kilograms divided by height in meters squared) category was the independent variable of interest, and the categories were as follows: lower than 18.5 (underweight), 18.5 to 24.9 (healthy weight), 25.0 to 29.9 (overweight), 30.0 to 34.9 (class 1 obesity), 35.0 to 39.9 (class 2 obesity), and 40.0 to 44.9 and 45.0 or higher (class 3 or severe obesity). MAIN OUTCOMES AND MEASURES: The 2 main outcomes were 5% or greater weight loss (ie, a ≥5% reduction in initial weight) and BMI reduction to the healthy weight category (ie, BMI of 18.5-24.9). RESULTS: The 18 461 623 individuals in the sample had a median (IQR) age of 54 (40-66) years and included 10 464 598 females (56.7%) as well as 7.7% Black and 72.3% White patients. Overall, 72.5% of patients had overweight or obesity at the initial visit. Among adults with overweight and obesity, the annual probability of 5% or greater weight loss was low (1 in 10) but increased with higher initial BMI (from 1 in 12 individuals with initial overweight to 1 in 6 individuals with initial BMI of 45 or higher). Annual probability of BMI reduction to the healthy weight category ranged from 1 in 19 individuals with initial overweight to 1 in 1667 individuals with initial BMI of 45 or higher. Both outcomes were generally more likely among females than males and were highest among White females. Over the 3 to 14 years of follow-up, 33.4% of persons with overweight and 41.8% of persons with obesity lost 5% or greater of their initial weight. At the same time, 23.2% of persons with overweight and 2.0% of persons with obesity reduced BMI to the healthy weight category. CONCLUSIONS AND RELEVANCE: Results of this cohort study indicate that the annual probability of 5% or greater weight loss was low (1 in 10) despite the known benefits of clinically meaningful weight loss, but 5% or greater weight loss was more likely than BMI reduction to the healthy weight category, especially for patients with the highest initial BMIs. Clinicians and public health efforts can focus on messaging and referrals to interventions that are aimed at clinically meaningful weight loss (ie, ≥5%) for adults at any level of excess weight.

Background: Prior studies have documented differences in the age, racial, and ethnic characteristics among patients with SARS-CoV-2 infection. However, little is known about how these characteristics changed over time during the pandemic and whether racial, ethnic, and age disparities evident early in the pandemic were persistent over time. This study reports on trends in SARS-CoV-2 infections among U.S. adults from March 1, 2020 to January, 31 2022, using data from electronic health records. Methods and Findings: We captured repeated cross-sectional information from 43 large healthcare systems in 52 U.S. States and territories, participating in PCORnet, the National Patient-Centered Clinical Research Network. Using distributed queries executed at each participating institution, we acquired information for all patients >= 20 years of age who were tested for SARS-CoV-2 (both positive and negative results), including care setting, age, sex, race, and ethnicity by month as well as comorbidities (assessed with diagnostic codes). During this time period, 1,325,563 patients had positive (13% inpatient) and 6,705,868 patients had negative (25% inpatient) viral tests for SARS-CoV-2. Disparities in testing positive were present across racial and ethnic groups, especially in the inpatient setting. Compared to White patients, Black or African American and other race patients had relative risks for testing positive of 1.5 or greater in the inpatient setting for 12 of the 23-month study period. Compared to non-Hispanic patients, Hispanic patients had relative risks for testing positive in the inpatient setting of 1.5 or greater for 16 of 23. Ethnic and racial differences were present in emergency department and ambulatory settings but were less common across time than in inpatient settings. Trends in infections by age group demonstrated higher test positivity for older patients in the inpatient setting only for most months, except for June and July of 2020, April to August 2021, and January 2022. Comorbidities were common, with much higher rates among those hospitalized; hypertension (38% of patients SARS-CoV-2 positive vs. 29% for those negative) and type 2 diabetes mellitus (22% vs. 13%) were the most common. Conclusion and Relevance: Racial and ethnic disparities changed over time among persons infected with SARS-CoV-2. These trends highlight potential underlying mechanisms, such as poor access to care and differential vaccination rates, that may have contributed to greater disparities, especially early in the pandemic. Monitoring data on characteristics of patients testing positive in real time could allow public health officials and policymakers to tailor interventions to ensure that patients and communities most in need are receiving adequate testing, mitigation strategies, and treatment. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license.

IMPORTANCE: Nearly 40% of US youth aged 2 to 19 years do not have a body mass index (BMI) in the healthy weight category. However, there are no recent estimates for BMI-associated expenditures using clinical or claims data. OBJECTIVE: To estimate medical expenditures among US youth across all BMI categories along with sex and age groups. DESIGN, SETTING, PARTICIPANTS: This cross-sectional study used IQVIA's ambulatory electronic medical records (AEMR) data set linked with IQVIA's PharMetrics Plus Claims database from January 2018 through December 2018. Analysis was performed from March 25, 2022, through June 20, 2022. It included a convenience sample of a geographically diverse patient population from AEMR and PharMetrics Plus. The study sample included privately insured individuals with a BMI measurement in 2018 and excluded patients with pregnancy-related visits. EXPOSURE: BMI categories. MAIN OUTCOMES AND MEASURES: Total medical expenditures were estimated using generalized linear model regression with γ distribution and log-link function. For out-of-pocket (OOP) expenditures, a 2-part model was used that included logistic regression to estimate the probability of positive expenditures followed by generalized linear model. Estimates were shown with and without accounting for sex, race and ethnicity, payer type, geographic region, age interacted with sex and BMI categories, and confounding conditions. RESULTS: The sample included 20 876 individuals aged 2 to 19 years; 104 066 were male (50.5%) and the median age was 12 years. Compared with those with healthy weight, total and OOP expenditures were higher for all other BMI categories. Differences in total expenditures were highest for those with severe obesity ($909; 95% CI, $600-$1218) followed by underweight ($671; 95% CI, $286-$1055) compared with healthy weight. Differences in OOP expenditures were highest for those with severe obesity ($121; 95% CI, $86-$155) followed by underweight ($117; 95% CI, $78-$157) compared with healthy weight. Having underweight was associated with higher total expenditures at ages 2 to 5 years and 6 to 11 years by $679 (95% CI, $228-$1129) and $1166 (95% CI, $632-$1700), respectively; having severe obesity was associated with higher total expenditures at ages 2 to 5 years, 6 to 11 years, and 12 to 17 years by $1035 (95% CI, $208-$1863), $821 (95% CI, $414-$1227), and $1088 (95% CI, $594-$1582), respectively. CONCLUSIONS AND RELEVANCE: The study team found medical expenditures to be higher for all BMI categories when compared with those with healthy weight. These findings may indicate potential economic value of interventions or treatments aimed at reducing BMI-associated health risks.

This article describes a significant decline in emergency department visits for acute life-threatening conditions during the COVID-19 pandemic, suggesting that patients may be delaying or avoiding care or unable to access care during the pandemic.

Background: Youth with excess weight are at risk of developing type 2 diabetes (T2DM). Guidelines recommend screening for prediabetes and/or T2DM after 10 years of age or after puberty in youth with excess weight who have ≥1 risk factor(s) for T2DM. Electronic health records (EHRs) offer an opportunity to study the use of tests to detect diabetes in youth. Methods: We examined the frequency of (1) diabetes testing and (2) elevated test results among youth aged 10-19 years with at least one BMI measurement in an EHR from 2019 to 2021. We examined the presence of hemoglobin A1C (A1C), fasting plasma glucose (FPG), or oral glucose tolerance test (2-hour plasma glucose [2-hrPG]) results and, among those tested, the frequency of elevated values (A1C ≥6.5%, FPG ≥126 mg/dL, or 2-hrPG ≥200 mg/dL). Patients with pre-existing diabetes (n = 6793) were excluded. Results: Among 1,024,743 patients, 17% had overweight, 21% had obesity, including 8% with severe obesity. Among patients with excess weight, 10% had ≥1 glucose test result. Among those tested, elevated values were more common in patients with severe obesity (27%) and obesity (22%) than in those with healthy weight (8%), and among Black youth (30%) than White youth (13%). Among patients with excess weight, >80% of elevated values fell in the prediabetes range. Conclusions: In youth with excess weight, the use of laboratory tests for prediabetes and T2DM was infrequent. Among youth with test results, elevated FPG, 2hrPG, or A1C levels were most common in those with severe obesity and Black youth.

Background: Data sources for assessing pediatric chronic diseases and associated screening practices are rare. One example is non-alcoholic fatty liver disease (NAFLD), a common chronic liver disease prevalent among children with overweight and obesity. If undetected, NAFLD can cause liver damage. Guidelines recommend screening for NAFLD using alanine aminotransferase (ALT) tests in children ≥9 years with obesity or those with overweight and cardiometabolic risk factors. This study explores how real-world data from electronic health records (EHRs) can be used to study NAFLD screening and ALT elevation. Research Design: Using IQVIA's Ambulatory Electronic Medical Record database, we studied patients 2-19 years of age with body mass index ≥85th percentile. Using a 3-year observation period (January 1, 2019 to December 31, 2021), ALT results were extracted and assessed for elevation (≥1 ALT result ≥22.1 U/L for females and ≥25.8 U/L for males). Patients with liver disease (including NAFLD) or receiving hepatotoxic medications during 2017-2018 were excluded. Results: Among 919,203 patients 9-19 years of age, only 13% had ≥1 ALT result, including 14% of patients with obesity and 17% of patients with severe obesity. ALT results were identified for 5% of patients 2-8 years of age. Of patients with ALT results, 34% of patients 2-8 years of age and 38% of patients 9-19 years of age had ALT elevation. Males 9-19 years of age had a higher prevalence of ALT elevation than females (49% vs. 29%). Conclusions: EHR data offered novel insights into NAFLD screening: despite screening recommendations, ALT results among children with excess weight were infrequent. Among those with ALT results, ALT elevation was common, underscoring the importance of screening for early disease detection.

OBJECTIVE: Many U.S. youth experienced accelerated weight gain during the early COVID-19 pandemic. Using an ambulatory electronic health record dataset, we compared children's rates of BMI change in three periods: prepandemic (January 2018-February 2020), early pandemic (March-December 2020), and later pandemic (January-November 2021). METHODS: We used mixed-effects models to examine differences in rates of change in BMI, weight, and obesity prevalence among the three periods. Covariates included time as a continuous variable; a variable indicating in which period each BMI was taken; sex; age; and initial BMI category. RESULTS: In a longitudinal cohort of 241,600 children aged 2-19years with 4 BMIs, the monthly rates of BMI change (kg/m(2) ) were 0.056 (95%CI: 0.056, 0.057) prepandemic, 0.104 (95%CI: 0.102, 0.106) in the early pandemic, and 0.035 (95%CI: 0.033, 0.036) in the later pandemic. The estimated prevalence of obesity in this cohort was 22.5% by November 2021. CONCLUSIONS: In this large geographically-diverse cohort of U.S. youth, accelerated rates of BMI change observed during 2020 were largely attenuated in 2021. Positive rates indicate continued weight gain rather than loss, albeit at a slower rate. Childhood obesity prevalence remained high, which raises concern about long-term consequences of excess weight and underscores the importance of healthy lifestyle interventions. This article is protected by copyright. All rights reserved.

IMPORTANCE: The American Academy of Pediatrics (AAP) recommends laboratory screening for diabetes, dyslipidemia, and liver disease every 2 years among children aged 10 years and older with obesity. Routine screening for hypothyroidism or hyperinsulinemia is not recommended. National data on rates of adherence to AAP-recommended screening and rates of potentially unnecessary endocrine testing are unavailable. OBJECTIVE: To assess rates of AAP-adherent screening and potentially unnecessary endocrine testing among privately and publicly insured children diagnosed with obesity at well-child visits. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study used data from the 2018-2019 IBM MarketScan Commercial Database (which contains claims from privately insured patients across the US) and the 2018-2019 IBM MarketScan Multi-State Medicaid Database (which contains claims from Medicaid patients in multiple states). A total of 156773 children aged 10 to 18 years with obesity diagnosis codes at a well-child visit from December 1, 2018, through November 30, 2019, were included. Analysis was performed from May 1 to October 31, 2021. MAIN OUTCOMES AND MEASURES: Primary outcomes were the proportion of children who received AAP-adherent screening during the 729 days before to 30 days after a well-child visit and the proportion of children who received 1 or more potentially unnecessary thyroid or insulin tests during the same period. Proportions of children by payer type were compared using logistic regression models adjusted for age and sex. To assess screening that was potentially ordered by primary care clinicians, the proportion of children without AAP-adherent screening before visits who received this screening within 30 days was calculated. RESULTS: Of 156773 children, the mean (SD) age was 13.5 years (2.5) years; 83 305 (53.1%) were male, and 97595 (62.3%) were publicly insured. Among publicly insured children, 13167 (13.5%) were Hispanic or Latino, 34792 (35.6%) were non-Hispanic Black, 42029 (43.1%) were non-Hispanic White, 3850 (3.9%) were of other race and/or ethnicity (specific races and ethnicities were not available in the database), and 3757 (3.8%) were of unknown race and ethnicity. Race and ethnicity were not available for privately insured children because these data are not reported in the commercial claims database. During the 729 days before to 30 days after well-child visits, 42849 patients (27.3%) received AAP-adherent screening, including 13939 (23.6%) of 59 178 privately insured children and 28910 (29.6%) of 97 595 publicly insured children (average marginal effect for public insurance: 6.8 [95% CI, 6.3-7.2] percentage points). In addition, 46592 children (29.7%) received potentially unnecessary thyroid or insulin tests, including 12 834 (21.7%) of 59 178 privately insured children and 23 198 (23.8%) of 97 595 publicly insured children (average marginal effect for public insurance: 2.4 [95% CI, 2.0-2.8] percentage points). Among 129104 children who did not receive AAP-adherent screening before visits, 15 090 (11.7%) received this screening within 30 days. CONCLUSIONS AND RELEVANCE: In this cross-sectional study, similar proportions of children diagnosed with obesity at well-child visits received recommended and nonrecommended screening tests for obesity-related co-occurring conditions, suggesting that specific actionable guidelines and interventions are needed to prevent overuse and underuse of screening tests among children with obesity.

OBJECTIVE: To assess the association of body mass index (BMI) with inpatient care cost, duration, and acute complications among patients hospitalized for COVID-19 at 273 U.S. hospitals. METHODS: Children (2-17 years) and adults (≥18 years) hospitalized for COVID-19 during March 2020-July 2021 and measured BMI in a large electronic administrative healthcare database were included. We used generalized linear models to assess the association of BMI categories with the cost and duration of inpatient care. RESULTS: Among 108,986 adults and 409 children hospitalized for COVID-19, obesity prevalence was 53.4% and 45.0%, respectively. Among adults, overweight and obesity were associated with higher costs of care, and obesity was associated with longer hospital stays. Children with severe obesity had a higher cost of care, but not significantly longer hospital stays, compared to those with healthy weights. Children with severe obesity were 3.7 times (95% CI: 1.5 to 9.5) as likely to have invasive mechanical ventilation and 62% more likely to have an acute complication (95% CI, 39-90), compared to children with healthy weight. CONCLUSIONS: These findings show that patients with high BMIs experience significant healthcare burden during inpatient COVID-19 care. This article is protected by copyright. All rights reserved.

OBJECTIVE: Self-efficacy is a crucial factor in enabling pediatric primary care providers (PCPs) to deliver recommended care to children with overweight and obesity. This study, conducted with a large, national sample of PCPs, aimed to identify key factors which may contribute to PCP self-efficacy for obesity-related care, from a list of previously reported barriers and facilitators. METHODS: A national random sample of American Academy of Pediatrics members were surveyed in 2017 (analytic n=704). Factor analysis was used to identify self-efficacy variables from relevant indicators and assess fit. Multivariable linear regression analyses were conducted to identify key predictors of PCP self-efficacy from reported facilitators or barriers to care, including characteristics of the PCP, practice, community, and payment systems. RESULTS: Two PCP self-efficacy variables were identified: health risk assessment and patient-centered counseling. Both were positively predicted by relevant training, the belief that pediatricians play an important role in obesity, and awareness of barriers to payment for dietitians or weight management programs. Both were negatively predicted by a perceived lack of available PCP time for counseling and inadequacy of available referral resources to assist with treatment. Additional predictors of counseling self-efficacy included PCP beliefs that they are paid for treatment (+) and that patients/families lack time for healthy behaviors (-). Electronic health record clinical decision supports or registries and patient social disadvantage were not predictive. CONCLUSIONS: Results suggest multiple potential roles and strategies for local and national organizations seeking to facilitate improvements to PCP self-efficacy in caring for children with overweight and obesity.

BACKGROUND: In 2019, the United States experienced a nationwide outbreak of e-cigarette, or vaping, product use-associated lung injury (EVALI). More than half of these patients required admission to an intensive care unit (ICU). METHODS: To synthesize information critical to pulmonary/critical care specialists in the care of patients with EVALI, we examined data available from patients hospitalized with EVALI between August 2019 and January 2020; reviewed the clinical course and critical care experience with those patients admitted to the ICU; and compiled opinion of national experts. RESULTS: Of the 2,708 confirmed or probable EVALI patients requiring hospitalization as of January 21, 2020, 1,604 (59.2%) had data available on ICU admission; of these, 705 (44.0%) were admitted to the ICU and are included in this analysis. The majority of ICU patients required respiratory support (88.5%), and in severe cases required intubation (36.1%), or extracorporeal membrane oxygenation (ECMO) (6.7%). The majority (93.0%) of these ICU patients survived to discharge. Review of the clinical course and expert opinion provided insight into: imaging; considerations for bronchoscopy; medical treatment, including use of empiric antibiotics, antivirals, and corticosteroids; respiratory support, including considerations for intubation, positioning maneuvers, and ECMO; and patient outcomes. CONCLUSIONS: Review of the clinical course of EVALI patients requiring ICU admission and compilation of expert opinion provided critical insight into pulmonary/critical care-specific considerations for this patient population. As a large proportion of patients hospitalized with EVALI required ICU admission, it is important to remain prepared to care for patients with EVALI.

IMPORTANCE: New symptoms and conditions can develop following SARS-CoV-2 infection. Whether they occur more frequently among persons with SARS-CoV-2 infection compared with those without is unclear. OBJECTIVE: To compare the prevalence of new diagnoses of select symptoms and conditions between 31 and 150 days after testing among persons who tested positive vs negative for SARS-CoV-2. DESIGN, SETTING, AND PARTICIPANTS: This cohort study analyzed aggregated electronic health record data from 40 health care systems, including 338 024 persons younger than 20 years and 1 790 886 persons aged 20 years or older who were tested for SARS-CoV-2 during March to December 2020 and who had medical encounters between 31 and 150 days after testing. MAIN OUTCOMES AND MEASURES: International Statistical Classification of Diseases, Tenth Revision, Clinical Modification codes were used to capture new symptoms and conditions that were recorded 31 to 150 days after a SARS-CoV-2 test but absent in the 18 months to 7 days prior to testing. The prevalence of new symptoms and conditions was compared between persons with positive and negative SARS-CoV-2 tests stratified by age (20 years or older and young than 20 years) and care setting (nonhospitalized, hospitalized, or hospitalized and ventilated). RESULTS: A total of 168 701 persons aged 20 years or older and 26 665 younger than 20 years tested positive for SARS-CoV-2, and 1 622 185 persons aged 20 years or older and 311 359 younger than 20 years tested negative. Shortness of breath was more common among persons with a positive vs negative test result among hospitalized patients (≥20 years: prevalence ratio [PR], 1.89 [99% CI, 1.79-2.01]; <20 years: PR, 1.72 [99% CI, 1.17-2.51]). Shortness of breath was also more common among nonhospitalized patients aged 20 years or older with a positive vs negative test result (PR, 1.09 [99% CI, 1.05-1.13]). Among hospitalized persons aged 20 years or older, the prevalence of new fatigue (PR, 1.35 [99% CI, 1.27-1.44]) and type 2 diabetes (PR, 2.03 [99% CI, 1.87-2.19]) was higher among those with a positive vs a negative test result. Among hospitalized persons younger than 20 years, the prevalence of type 2 diabetes (PR, 2.14 [99% CI, 1.13-4.06]) was higher among those with a positive vs a negative test result; however, the prevalence difference was less than 1%. CONCLUSIONS AND RELEVANCE: In this cohort study, among persons hospitalized after a positive SARS-CoV-2 test result, diagnoses of certain symptoms and conditions were higher than among those with a negative test result. Health care professionals should be aware of symptoms and conditions that may develop after SARS-CoV-2 infection, particularly among those hospitalized after diagnosis.

The COVID-19 pandemic has disproportionately affected people with diabetes, who are at increased risk of severe COVID-19.* Increases in the number of type 1 diabetes diagnoses (1,2) and increased frequency and severity of diabetic ketoacidosis (DKA) at the time of diabetes diagnosis (3) have been reported in European pediatric populations during the COVID-19 pandemic. In adults, diabetes might be a long-term consequence of SARS-CoV-2 infection (4-7). To evaluate the risk for any new diabetes diagnosis (type 1, type 2, or other diabetes) >30 days(†) after acute infection with SARS-CoV-2 (the virus that causes COVID-19), CDC estimated diabetes incidence among patients aged <18 years (patients) with diagnosed COVID-19 from retrospective cohorts constructed using IQVIA health care claims data from March 1, 2020, through February 26, 2021, and compared it with incidence among patients matched by age and sex 1) who did not receive a COVID-19 diagnosis during the pandemic, or 2) who received a prepandemic non-COVID-19 acute respiratory infection (ARI) diagnosis. Analyses were replicated using a second data source (HealthVerity; March 1, 2020-June 28, 2021) that included patients who had any health care encounter possibly related to COVID-19. Among these patients, diabetes incidence was significantly higher among those with COVID-19 than among those 1) without COVID-19 in both databases (IQVIA: hazard ratio [HR] = 2.66, 95% CI = 1.98-3.56; HealthVerity: HR = 1.31, 95% CI = 1.20-1.44) and 2) with non-COVID-19 ARI in the prepandemic period (IQVIA, HR = 2.16, 95% CI = 1.64-2.86). The observed increased risk for diabetes among persons aged <18 years who had COVID-19 highlights the importance of COVID-19 prevention strategies, including vaccination, for all eligible persons in this age group,(§) in addition to chronic disease prevention and management. The mechanism of how SARS-CoV-2 might lead to incident diabetes is likely complex and could differ by type 1 and type 2 diabetes. Monitoring for long-term consequences, including signs of new diabetes, following SARS-CoV-2 infection is important in this age group.

OBJECTIVE: This study compared the importance of age at adiposity rebound versus childhood BMI to subsequent BMI levels in a longitudinal analysis. METHODS: From the electronic health records of 4.35 million children, a total of 12,228 children were selected who were examined at least once each year between ages 2 and 7 years and reexamined after age 14 years. The minimum number of examinations per child was six. Each child's rebound age was estimated using locally weighted regression (lowess), a smoothing technique. RESULTS: Children who had a rebound age < 3 years were, on average, 7 kg/m(2) heavier after age 14 years than were children with a rebound age ≥ 7 years. However, BMI after age 14 years was more strongly associated with BMI at the rebound than with rebound age (r = 0.57 vs. -0.44). Furthermore, a child's BMI at age 3 years provided more information on BMI after age 14 years than did rebound age. In addition, rebound age provided no information on subsequent BMI if a child's BMI at age 6 years was known. CONCLUSIONS: Although rebound age is related to BMI after age 14 years, a child's BMI at age 3 years provides more information and is easier to obtain.

Fourteen million US children are affected by obesity, including 4.4 million with severe obesity.1,2 Excess weight can put children and adolescents at risk for serious and costly short- and long-term adverse health outcomes, including, but not limited to, cardiovascular disease, type 2 diabetes mellitus, and nonalcoholic fatty liver disease.3,4 Disparities in prevalence of obesity exist among different populations of children and adolescents. From 2015 to 2018, non-Hispanic black children and Mexican American youth 6–11 years of age had a higher prevalence of obesity (22.7% and 28.2%, respectively) than non-Hispanic white children (15.5%).5 These disparities are often related to contextual differences and social determinants of health, including poverty and socioeconomic status, parental education, early adverse childhood events, and access to healthier food options and safe and affordable physical activity opportunities.6–9

Obesity is a serious health concern in the United States, affecting more than one in six children (1) and putting their long-term health and quality of life at risk.* During the COVID-19 pandemic, children and adolescents spent more time than usual away from structured school settings, and families who were already disproportionally affected by obesity risk factors might have had additional disruptions in income, food, and other social determinants of health.(†) As a result, children and adolescents might have experienced circumstances that accelerated weight gain, including increased stress, irregular mealtimes, less access to nutritious foods, increased screen time, and fewer opportunities for physical activity (e.g., no recreational sports) (2,3). CDC used data from IQVIA's Ambulatory Electronic Medical Records database to compare longitudinal trends in body mass index (BMI, kg/m(2)) among a cohort of 432,302 persons aged 2-19 years before and during the COVID-19 pandemic (January 1, 2018-February 29, 2020 and March 1, 2020-November 30, 2020, respectively). Between the prepandemic and pandemic periods, the rate of BMI increase approximately doubled, from 0.052 (95% confidence interval [CI] = 0.051-0.052 to 0.100 (95% CI = 0.098-0.101) kg/m(2)/month (ratio = 1.93 [95% CI = 1.90-1.96]). Persons aged 2-19 years with overweight or obesity during the prepandemic period experienced significantly higher rates of BMI increase during the pandemic period than did those with healthy weight. These findings underscore the importance of efforts to prevent excess weight gain during and following the COVID-19 pandemic, as well as during future public health emergencies, including increased access to efforts that promote healthy behaviors. These efforts could include screening by health care providers for BMI, food security, and social determinants of health, increased access to evidence-based pediatric weight management programs and food assistance resources, and state, community, and school resources to facilitate healthy eating, physical activity, and chronic disease prevention.

Long-term symptoms often associated with COVID-19 (post-COVID conditions or long COVID) are an emerging public health concern that is not well understood. Prevalence of post-COVID conditions has been reported among persons who have had COVID-19 (range = 5%-80%), with differences possibly related to different study populations, case definitions, and data sources (1). Few studies of post-COVID conditions have comparisons with the general population of adults with negative test results for SARS-CoV-2, the virus that causes COVID-19, limiting ability to assess background symptom prevalence (1). CDC used a nonprobability-based Internet panel established by Porter Novelli Public Services* to administer a survey to a nationwide sample of U.S. adults aged ≥18 years to compare the prevalence of long-term symptoms (those lasting >4 weeks since onset) among persons who self-reported ever receiving a positive SARS-CoV-2 test result with the prevalence of similar symptoms among persons who reported always receiving a negative test result. The weighted prevalence of ever testing positive for SARS-CoV-2 was 22.2% (95% confidence interval [CI] = 20.6%-23.8%). Approximately two thirds of respondents who had received a positive test result experienced long-term symptoms often associated with SARS-CoV-2 infection. Compared with respondents who received a negative test result, those who received a positive test result reported a significantly higher prevalence of any long-term symptom (65.9% versus 42.9%), fatigue (22.5% versus 12.0%), change in sense of smell or taste (17.3% versus 1.7%), shortness of breath (15.5% versus 5.2%), cough (14.5% versus 4.9%), headache (13.8% versus 9.9%), and persistence (>4 weeks) of at least one initially occurring symptom (76.2% versus 69.6%). Compared with respondents who received a negative test result, a larger proportion of those who received a positive test result reported believing that receiving a COVID-19 vaccine made their long-term symptoms better (28.7% versus 15.7%). Efforts to address post-COVID conditions should include helping health care professionals recognize the most common post-COVID conditions and optimize care for patients with persisting symptoms, including messaging on potential benefits of COVID-19 vaccination.

CONTEXT: We describe a participatory framework that enhanced and implemented innovative changes to an existing distributed health data network (DHDN) infrastructure to support linkage across sectors and systems. Our processes and lessons learned provide a potential framework for other multidisciplinary infrastructure development projects that engage in a participatory decision-making process. PROGRAM: The Childhood Obesity Data Initiative (CODI) provides a potential framework for local and national stakeholders with public health, clinical, health services research, community intervention, and information technology expertise to collaboratively develop a DHDN infrastructure that enhances data capacity for patient-centered outcomes research and public health surveillance. CODI utilizes a participatory approach to guide decision making among clinical and community partners. IMPLEMENTATION: CODI's multidisciplinary group of public health and clinical scientists and information technology experts collectively defined key components of CODI's infrastructure and selected and enhanced existing tools and data models. We conducted a pilot implementation with 3 health care systems and 2 community partners in the greater Denver Metro Area during 2018-2020. EVALUATION: We developed an evaluation plan based primarily on the Good Evaluation Practice in Health Informatics guideline. An independent third party implemented the evaluation plan for the CODI development phase by conducting interviews to identify lessons learned from the participatory decision-making processes. DISCUSSION: We demonstrate the feasibility of rapid innovation based upon an iterative and collaborative process and existing infrastructure. Collaborative engagement of stakeholders early and iteratively was critical to ensure a common understanding of the research and project objectives, current state of technological capacity, intended use, and the desired future state of CODI architecture. Integration of community partners' data with clinical data may require the use of a trusted third party's infrastructure. Lessons learned from our process may help others develop or improve similar DHDNs.

CONTEXT: Integrating longitudinal data from community-based organizations (eg, physical activity programs) with electronic health record information can improve capacity for childhood obesity research. OBJECTIVE: A governance framework that protects individual privacy, accommodates organizational data stewardship requirements, and complies with laws and regulations was developed and implemented to support the harmonization of data from disparate clinical and community information systems. PARTICIPANTS AND SETTING: Through the Childhood Obesity Data Initiative (CODI), 5 Colorado-based organizations collaborated to expand an existing distributed health data network (DHDN) to include community-generated data and assemble longitudinal patient records for research. DESIGN: A governance work group expanded an existing DHDN governance infrastructure with CODI-specific data use and exchange policies and procedures that were codified in a governance plan and a delegated-authority, multiparty, reciprocal agreement. RESULTS: A CODI governance work group met from January 2019 to March 2020 to conceive an approach, develop documentation, and coordinate activities. Governance requirements were synthesized from the CODI use case, and a customized governance approach was constructed to address governance gaps in record linkage, a procedure to request data, and harmonizing community and clinical data. A Master Sharing and Use Agreement (MSUA) and Memorandum of Understanding were drafted and executed to support creation of linked longitudinal records of clinical- and community-derived childhood obesity data. Furthermore, a multiparty infrastructure protocol was approved by the local institutional review board (IRB) to expedite future CODI research by simplifying IRB research applications. CONCLUSION: CODI implemented a clinical-community governance strategy that built trust between organizations and allowed efficient data exchange within a DHDN. A thorough discovery process allowed CODI stakeholders to assess governance capacity and reveal regulatory and organizational obstacles so that the governance infrastructure could effectively leverage existing knowledge and address challenges. The MSUA and complementary governance documents can inform similar efforts.

As of June 30, 2021, 33.5 million persons in the United States had received a diagnosis of COVID-19 (1). Although most patients infected with SARS-CoV-2, the virus that causes COVID-19, recover within a few weeks, some experience post-COVID-19 conditions. These range from new or returning to ongoing health problems that can continue beyond 4 weeks. Persons who were asymptomatic at the time of infection can also experience post-COVID-19 conditions. Data on post-COVID-19 conditions are emerging and information on rehabilitation needs among persons recovering from COVID-19 is limited. Using data acquired during January 2020-March 2021 from Select Medical* outpatient rehabilitation clinics, CDC compared patient-reported measures of health, physical endurance, and health care use between patients who had recovered from COVID-19 (post-COVID-19 patients) and patients needing rehabilitation because of a current or previous diagnosis of a neoplasm (cancer) who had not experienced COVID-19 (control patients). All patients had been referred to outpatient rehabilitation. Compared with control patients, post-COVID-19 patients had higher age- and sex-adjusted odds of reporting worse physical health (adjusted odds ratio [aOR] = 1.8), pain (aOR = 2.3), and difficulty with physical activities (aOR = 1.6). Post-COVID-19 patients also had worse physical endurance, measured by the 6-minute walk test(†) (6MWT) (p<0.001) compared with control patients. Among patients referred to outpatient rehabilitation, those recovering from COVID-19 had poorer physical health and functional status than those who had cancer, or were recovering from cancer but not COVID-19. Patients recovering from COVID-19 might need additional clinical support, including tailored physical and mental health rehabilitation services.

INTRODUCTION: Severe COVID-19 illness in adults has been linked to underlying medical conditions. This study identified frequent underlying conditions and their attributable risk of severe COVID-19 illness. METHODS: We used data from more than 800 US hospitals in the Premier Healthcare Database Special COVID-19 Release (PHD-SR) to describe hospitalized patients aged 18 years or older with COVID-19 from March 2020 through March 2021. We used multivariable generalized linear models to estimate adjusted risk of intensive care unit admission, invasive mechanical ventilation, and death associated with frequent conditions and total number of conditions. RESULTS: Among 4,899,447 hospitalized adults in PHD-SR, 540,667 (11.0%) were patients with COVID-19, of whom 94.9% had at least 1 underlying medical condition. Essential hypertension (50.4%), disorders of lipid metabolism (49.4%), and obesity (33.0%) were the most common. The strongest risk factors for death were obesity (adjusted risk ratio [aRR] = 1.30; 95% CI, 1.27-1.33), anxiety and fear-related disorders (aRR = 1.28; 95% CI, 1.25-1.31), and diabetes with complication (aRR = 1.26; 95% CI, 1.24-1.28), as well as the total number of conditions, with aRRs of death ranging from 1.53 (95% CI, 1.41-1.67) for patients with 1 condition to 3.82 (95% CI, 3.45-4.23) for patients with more than 10 conditions (compared with patients with no conditions). CONCLUSION: Certain underlying conditions and the number of conditions were associated with severe COVID-19 illness. Hypertension and disorders of lipid metabolism were the most frequent, whereas obesity, diabetes with complication, and anxiety disorders were the strongest risk factors for severe COVID-19 illness. Careful evaluation and management of underlying conditions among patients with COVID-19 can help stratify risk for severe illness.

IMPORTANCE: Information on underlying conditions and severe COVID-19 illness among children is limited. OBJECTIVE: To examine the risk of severe COVID-19 illness among children associated with underlying medical conditions and medical complexity. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study included patients aged 18 years and younger with International Statistical Classification of Diseases, Tenth Revision, Clinical Modification code U07.1 (COVID-19) or B97.29 (other coronavirus) during an emergency department or inpatient encounter from March 2020 through January 2021. Data were collected from the Premier Healthcare Database Special COVID-19 Release, which included data from more than 800 US hospitals. Multivariable generalized linear models, controlling for patient and hospital characteristics, were used to estimate adjusted risk of severe COVID-19 illness associated with underlying medical conditions and medical complexity. EXPOSURES: Underlying medical conditions and medical complexity (ie, presence of complex or noncomplex chronic disease). MAIN OUTCOMES AND MEASURES: Hospitalization and severe illness when hospitalized (ie, combined outcome of intensive care unit admission, invasive mechanical ventilation, or death). RESULTS: Among 43 465 patients with COVID-19 aged 18 years or younger, the median (interquartile range) age was 12 (4-16) years, 22 943 (52.8%) were female patients, and 12 491 (28.7%) had underlying medical conditions. The most common diagnosed conditions were asthma (4416 [10.2%]), neurodevelopmental disorders (1690 [3.9%]), anxiety and fear-related disorders (1374 [3.2%]), depressive disorders (1209 [2.8%]), and obesity (1071 [2.5%]). The strongest risk factors for hospitalization were type 1 diabetes (adjusted risk ratio [aRR], 4.60; 95% CI, 3.91-5.42) and obesity (aRR, 3.07; 95% CI, 2.66-3.54), and the strongest risk factors for severe COVID-19 illness were type 1 diabetes (aRR, 2.38; 95% CI, 2.06-2.76) and cardiac and circulatory congenital anomalies (aRR, 1.72; 95% CI, 1.48-1.99). Prematurity was a risk factor for severe COVID-19 illness among children younger than 2 years (aRR, 1.83; 95% CI, 1.47-2.29). Chronic and complex chronic disease were risk factors for hospitalization, with aRRs of 2.91 (95% CI, 2.63-3.23) and 7.86 (95% CI, 6.91-8.95), respectively, as well as for severe COVID-19 illness, with aRRs of 1.95 (95% CI, 1.69-2.26) and 2.86 (95% CI, 2.47-3.32), respectively. CONCLUSIONS AND RELEVANCE: This cross-sectional study found a higher risk of severe COVID-19 illness among children with medical complexity and certain underlying conditions, such as type 1 diabetes, cardiac and circulatory congenital anomalies, and obesity. Health care practitioners could consider the potential need for close observation and cautious clinical management of children with these conditions and COVID-19.

BACKGROUND: Late sequelae of COVID-19 have been reported; however, few studies have investigated the time-course or incidence of late new COVID-19-related health conditions (post-COVID conditions) after COVID-19 diagnosis. Studies distinguishing post-COVID conditions from late conditions caused by other etiologies are lacking. Using data from a large administrative all-payer database, we assessed the type, association, and timing of post-COVID conditions following COVID-19 diagnosis. METHODS: Using the Premier Healthcare Database Special COVID-19 Release (PHD-SR) (release date, October 20, 2020) data, during March-June 2020, 27,589 inpatients and 46,857 outpatients diagnosed with COVID-19 (case-patients) were 1:1 matched with patients without COVID-19 through the 4-month follow-up period (control-patients) by using propensity score matching. In this matched-cohort study, adjusted odds ratios were calculated to assess for late conditions that were more common in case-patients compared with control-patients. Incidence proportion was calculated for conditions that were more common in case-patients than control-patients during 31-120 days following a COVID-19 encounter. RESULTS: During 31-120 days after an initial COVID-19 inpatient hospitalization, 7.0% of adults experienced at least one of five post-COVID conditions. Among adult outpatients with COVID-19, 7.7% experienced at least one of ten post-COVID conditions. During 31-60 days after an initial outpatient encounter, adults with COVID-19 were 2.8 times as likely to experience acute pulmonary embolism as outpatient control-patients and were also more likely to experience a range of conditions affecting multiple body systems (e.g. nonspecific chest pain, fatigue, headache, and respiratory, nervous, circulatory, and gastrointestinal system symptoms) than outpatient control-patients. Children with COVID-19 were not more likely to experience late conditions than children without COVID-19. CONCLUSIONS: These findings add to the evidence of late health conditions possibly related to COVID-19 in adults following COVID-19 diagnosis and can inform health care practice and resource planning for follow-up COVID-19 care.

This cohort study uses data from the Premier Healthcare Database Special COVID-19 Release to assess the association of demographic and clinical characteristics with severe COVID-19 illness among hospitalized US pediatric patients with COVID-19.

Obesity* is a recognized risk factor for severe COVID-19 (1,2), possibly related to chronic inflammation that disrupts immune and thrombogenic responses to pathogens (3) as well as to impaired lung function from excess weight (4). Obesity is a common metabolic disease, affecting 42.4% of U.S. adults (5), and is a risk factor for other chronic diseases, including type 2 diabetes, heart disease, and some cancers.(†) The Advisory Committee on Immunization Practices considers obesity to be a high-risk medical condition for COVID-19 vaccine prioritization (6). Using data from the Premier Healthcare Database Special COVID-19 Release (PHD-SR),(§) CDC assessed the association between body mass index (BMI) and risk for severe COVID-19 outcomes (i.e., hospitalization, intensive care unit [ICU] or stepdown unit admission, invasive mechanical ventilation, and death). Among 148,494 adults who received a COVID-19 diagnosis during an emergency department (ED) or inpatient visit at 238 U.S. hospitals during March-December 2020, 28.3% had overweight and 50.8% had obesity. Overweight and obesity were risk factors for invasive mechanical ventilation, and obesity was a risk factor for hospitalization and death, particularly among adults aged <65 years. Risks for hospitalization, ICU admission, and death were lowest among patients with BMIs of 24.2 kg/m(2), 25.9 kg/m(2), and 23.7 kg/m(2), respectively, and then increased sharply with higher BMIs. Risk for invasive mechanical ventilation increased over the full range of BMIs, from 15 kg/m(2) to 60 kg/m(2). As clinicians develop care plans for COVID-19 patients, they should consider the risk for severe outcomes in patients with higher BMIs, especially for those with severe obesity. These findings highlight the clinical and public health implications of higher BMIs, including the need for intensive COVID-19 illness management as obesity severity increases, promotion of COVID-19 prevention strategies including continued vaccine prioritization (6) and masking, and policies to ensure community access to nutrition and physical activities that promote and support a healthy BMI.

OBJECTIVE: The current CDC BMI z-scores are inaccurate for BMIs ≥ 97(th) percentile. We, therefore, considered 5 alternatives that can be used across the entire BMI distribution: modified BMIz, %CDC95th percentile, extended BMIz, %median, and %median adjusted for the dispersion of BMIs. STUDY DESIGN: We illustrate the behavior of the metrics among children of different ages and BMIs. We then compared the longitudinal tracking of the BMI metrics in electronic health record (EHR) data from 1.17 million children in PEDSnet using the intraclass correlation coefficient (ICC) to determine if one metric was superior. RESULTS: Our examples show that using CDC BMIz for high BMIs can result in nonsensical results. All alternative metrics showed higher tracking than CDC BMIz among children with obesity. Of the alternatives, modified BMIz performed poorly among children with severe obesity, and %median performed poorly among children who did not have obesity at their first visit. The highest ICCs were generally seen for extended BMIz, adjusted %median, and %CDC95(th) percentile. CONCLUSIONS: Based on the examples of differences in the BMI metrics, the longitudinal tracking results, and current familiarity BMI z-scores and percentiles, extended BMIz and extended BMI percentile may be suitable replacements for the current z-scores and percentiles. These metrics are identical to those in the CDC growth charts for BMIs < 95(th) percentile and are superior for very high BMIs. Researchers' familiarity with the current CDC z-scores and clinicians with the CDC percentiles may ease the transition to the extended BMI scale.

BACKGROUND: Older adults and people from certain racial and ethnic groups are disproportionately represented in coronavirus disease 2019 (COVID-19) hospitalizations and deaths. METHODS: Using data from the Premier Healthcare Database on 181( )813 hospitalized adults diagnosed with COVID-19 during March-September 2020, we applied multivariable log-binomial regression to assess the associations between age and race/ethnicity and COVID-19 clinical severity (intensive care unit [ICU] admission, invasive mechanical ventilation [IMV], and death) and to determine whether the impact of age on clinical severity differs by race/ethnicity. RESULTS: Overall, 84( )497 (47%) patients were admitted to the ICU, 29( )078 (16%) received IMV, and 27( )864 (15%) died in the hospital. Increased age was strongly associated with clinical severity when controlling for underlying medical conditions and other covariates; the strength of this association differed by race/ethnicity. Compared with non-Hispanic White patients, risk of death was lower among non-Hispanic Black patients (adjusted risk ratio, 0.96; 95% CI, 0.92-0.99) and higher among Hispanic/Latino patients (risk ratio [RR], 1.15; 95% CI, 1.09-1.20), non-Hispanic Asian patients (RR, 1.16; 95% CI, 1.09-1.23), and patients of other racial and ethnic groups (RR, 1.13; 95% CI, 1.06-1.21). Risk of ICU admission and risk of IMV were elevated among some racial and ethnic groups. CONCLUSIONS: These results indicate that age is a driver of poor outcomes among hospitalized persons with COVID-19. Additionally, clinical severity may be elevated among patients of some racial and ethnic minority groups. Public health strategies to reduce severe acute respiratory syndrome coronavirus 2 infection rates among older adults and racial and ethnic minorities are essential to reduce poor outcomes.