Association of Obesity and Diabetes with SARS-Cov-2 Infection and Symptoms in the COVID-19 Community Research Partnership.

OBJECTIVE: Obesity and diabetes are established risk factors for severe SARS-CoV-2 outcomes, but less is known about their impact on susceptibility to COVID-19 infection and general symptom severity. We hypothesized that those with obesity or diabetes would be more likely to self-report a positive SARS-CoV-2 test, and among those with a positive test, have greater symptom severity and duration. METHODS: Among 44,430 COVID-19 Community Research Partnership participants, we evaluated the association of self-reported and electronic health record obesity and diabetes with a self-reported positive COVID-19 test at any time. Among the 2,663 participants with a self-reported positive COVID-19 test during the study, we evaluated the association of obesity and diabetes with self-report of symptom severity, duration, and hospitalization. Logistic regression models were adjusted for age, sex, race/ethnicity, socioeconomic status, and healthcare worker status. RESULTS: We found a positive graded association between Body Mass Index (BMI) category and positive COVID-19 test (Overweight OR = 1.14 [1.05-1.25]; Obesity I OR = 1.29 [1.17-2.42]; Obesity II OR = 1.34 [1.19-1.50]; Obesity III OR = 1.53 [1.35-1.73]), and a similar but weaker association with COVID-19 symptoms and severity among those with a positive test. Diabetes was associated with COVID-19 infection but not symptoms after adjustment, with some evidence of an interaction between obesity and diabetes. CONCLUSIONS: While the limitations of this health system convenience sample include generalizability and selection around test-seeking, the strong graded association of BMI and diabetes with self-reported COVID-19 infection suggests that obesity and diabetes may play a role in risk for symptomatic SARS-CoV-2 beyond co-occurrence with socioeconomic factors.

Breakthrough SARS-CoV-2 Infections after Vaccination in North Carolina.

We characterize the overall incidence and risk factors for breakthrough infection among fully vaccinated participants in the North Carolina COVID-19 Community Research Partnership cohort. Among 15,808 eligible participants, 638 reported a positive SARS-CoV-2 test after vaccination. Factors associated with a lower risk of breakthrough in the time-to-event analysis included older age, prior SARS-CovV-2 infection, higher rates of face mask use, and receipt of a booster vaccination. Higher rates of breakthrough were reported by participants vaccinated with BNT162b2 or Ad26.COV2.S compared to mRNA-1273, in suburban or rural counties compared to urban counties, and during circulation of the Delta and Omicron variants.

Question evaluation for real-time surveys: Lessons from COVID-19 data collection.

The need for high-quality, real-time data has never presented itself as clearly as it did during the COVID-19 pandemic. Responding to the COVID-19 pandemic, from both a policy and a public health perspective, required timely, accurate data about the public's attitudes and behaviors from health surveillance, monitoring, and public opinion surveys. The uniqueness of the COVID-19 pandemic also created particular challenges for survey data collection, specifically, how to develop high quality survey questions on topics that had never been previously fielded. To account for this challenge, the National Center for Health Statistics adopted an iterative, two-component, mixed-method approach to question design and evaluation. The first, a cognitive interviewing study using virtual, online interviews was used to produce interpretative schemata of the response processes underlying the survey questions. The second, a two-round, mixed method survey using a statistically-sampled panel, was designed to further develop the interpretive schemata and to allow for detailed subgroup analyses. To increase the usefulness of the survey's second round, cognitive interview findings and results from the survey's first round were used to develop both open- and close-ended embedded probes. Taken together, the studies reveal the specific problems for question-design during such a novel, quickly-evolving event: 1) a lack of shared understanding of novel concepts and vocabulary, 2) the shifting reference period respondents use to think about attitudes and behaviors during a multi-year event, 3) the pervasive nature of the event that therefore frames how respondents conceptualize and process questions about unrelated topics. This iterative approach to understanding question-design problems not only allowed for the continuing improvement of COVID-19 survey items, going forward, it also provided a methodological foundation for question development for high quality, real-time data collection.

Association of Obesity and Diabetes with SARS-Cov-2 Infection and Symptoms

Background: Obesity and T2D are risk factors for SARS-CoV-2 outcomes, but less is known about non-hospitalized cases. We hypothesized that those with obesity or T2D are more likely to have a positive Covid test, and among those with a positive test, to have symptoms. Methods: Among 31,117 North Carolina Covid Community Research Partnership participants with EHR data, we evaluated the association of self-reported and EHR obesity and T2D with a self-reported positive Covid test at any time. Among 2,418 participants with a positive test during the study, we evaluated the association of obesity and T2D with self-report of symptoms. Logistic regression models were adjusted for age, sex, race/ethnicity, socioeconomic status, and healthcare worker status. Results: We found a positive graded association between BMI category and positive Covid test, and a similar but weaker association with Covid symptoms among those with a positive test (Table) . T2D was associated with Covid infection but not symptoms. Conclusions: While the limitations of this health system convenience sample include generalizability and test seeking selection bias, the strong graded association of BMI and T2D with self-reported Covid infection suggests that obesity and T2D may play a role in risk for symptomatic SARS-CoV-2 beyond co-occurrence with socioeconomic risk factors.

Health Impairments in Children and Adolescents After Hospitalization for Acute COVID-19 or MIS-C.

OBJECTIVES: To evaluate risk factors for postdischarge sequelae in children and adolescents hospitalized for acute coronavirus disease 2019 (COVID-19) or multisystem inflammatory syndrome in children (MIS-C). METHODS: Multicenter prospective cohort study conducted in 25 United States pediatric hospitals. Patients <21-years-old, hospitalized May 2020 to May 2021 for acute COVID-19 or MIS-C with follow-up 2 to 4 months after admission. We assessed readmissions, persistent symptoms or activity impairment, and new morbidities. Multivariable regression was used to calculate adjusted risk ratios (aRR) and 95% confidence intervals (CI). RESULTS: Of 358 eligible patients, 2 to 4 month survey data were available for 119 of 155 (76.8%) with acute COVID-19 and 160 of 203 (78.8%) with MIS-C. Thirteen (11%) patients with acute COVID-19 and 12 (8%) with MIS-C had a readmission. Thirty-two (26.9%) patients with acute COVID-19 had persistent symptoms (22.7%) or activity impairment (14.3%) and 48 (30.0%) with MIS-C had persistent symptoms (20.0%) or activity impairment (21.3%). For patients with acute COVID-19, persistent symptoms (aRR, 1.29 [95% CI, 1.04-1.59]) and activity impairment (aRR, 1.37 [95% CI, 1.06-1.78]) were associated with more organ systems involved. Patients with MIS-C and pre-existing respiratory conditions more frequently had persistent symptoms (aRR, 3.09 [95% CI, 1.55-6.14]) and those with obesity more frequently had activity impairment (aRR, 2.52 [95% CI, 1.35-4.69]). New morbidities were infrequent (9% COVID-19, 1% MIS-C). CONCLUSIONS: Over 1 in 4 children hospitalized with acute COVID-19 or MIS-C experienced persistent symptoms or activity impairment for at least 2 months. Patients with MIS-C and respiratory conditions or obesity are at higher risk of prolonged recovery.

Patient Perspectives With Telehealth Visits in Cardiology During COVID-19: Online Patient Survey Study.

BACKGROUND: The rise of COVID-19 and the issue of a mandatory stay-at-home order in March 2020 led to the use of a direct-to-consumer model for cardiology telehealth in Kentucky. Kentucky has poor health outcomes and limited broadband connectivity. Given these and other practice-specific constraints, the region serves as a unique context to explore the efficacy of telehealth in cardiology. OBJECTIVE: This study aims to determine the limitations of telehealth accessibility, patient satisfaction with telehealth relative to in-person visits, and the perceived advantages and disadvantages to telehealth. Our intent was two-fold. First, we wanted to conduct a rapid postassessment of the mandated overhaul of the health care delivery system, focusing on a representative specialty field, and how it was affecting patients. Second, we intend to use our findings to make suggestions about the future application of a telehealth model in specialty fields such as cardiology. METHODS: We constructed an online survey in Qualtrics following the Patient Assessment of Communication During Telemedicine, a patient self-report questionnaire that has been previously developed and validated. We invited all patients who had a visit scheduled during the COVID-19 telehealth-only time frame to participate. Questions included factors for declining telehealth, patient satisfaction ratings of telehealth and in-person visits, and perceived advantages and disadvantages associated with telehealth. We also used electronic medical records to collect no-show data for in-person versus telehealth visits to check for nonresponse bias. RESULTS: A total of 224 respondents began our survey (11% of our sample of 2019 patients). Our recruitment rate was 86% (n=193) and our completion rate was 62% (n=120). The no-show rate for telehealth visits (345/2019, 17%) was nearly identical to the typical no-show rate for in-person appointments. Among the 32 respondents who declined a telehealth visit, 20 (63%) cited not being aware of their appointment as a primary factor, and 15 (47%) respondents cited their opinion that a telehealth appointment was not medically necessary as at least somewhat of a factor in their decision. Both in-person and telehealth were viewed favorably, but in-person was rated higher across all domains of patient satisfaction. The only significantly lower mean score for telehealth (3.7 vs 4.2, P=.007) was in the clinical competence domain. Reduced travel time, lower visit wait time, and cost savings were seen as big advantages. Poor internet connectivity was rated as at least somewhat of a factor by 33.0% (35/106) of respondents. CONCLUSIONS: This study takes advantage of the natural experiment provided by the COVID-19 pandemic to assess the efficacy of telehealth in cardiology. Patterns of satisfaction are consistent across modalities and show that telehealth appears to be a viable alternative to in-person appointments. However, we found evidence that scheduling of telehealth visits may be problematic and needs additional attention. Additionally, we include a note of caution that patient satisfaction with telehealth may be artificially inflated during COVID-19 due to external health concerns connected with in-person visits.