Trends of Antihypertensive Prescription Among US Adults From 2010 to 2019 and Changes Following Treatment Guidelines: Analysis of Multicenter Electronic Health Records.

BACKGROUND: Guidelines for the use of antihypertensives changed in 2014 and 2017. To understand the effect of these guidelines, we examined trends in antihypertensive prescriptions in the United States from 2010 to 2019 using a repeated cross-sectional design. METHODS AND RESULTS: Using electronic health records from 15 health care institutions for adults (20-85 years old) who had ≥1 antihypertensive prescription, we assessed whether (1) prescriptions of beta blockers decreased after the 2014 Eighth Joint National Committee (JNC 8) report discouraged use for first-line treatment, (2) prescriptions for calcium channel blockers and thiazide diuretics increased among Black patients after the JNC 8 report encouraged use as first-line therapy, and (3) prescriptions for dual therapy and fixed-dose combination among patients with blood pressure ≥140/90 mm Hg increased after recommendations in the 2017 Hypertension Clinical Practice Guidelines. The study included 1 074 314 patients with 2 133 158 prescription episodes. After publication of the JNC 8 report, prescriptions for beta blockers decreased (3% lower in 2018-2019 compared to 2010-2014), and calcium channel blockers increased among Black patients (20% higher in 2015-2017 and 41% higher in 2018-2019, compared to 2010-2014), in accordance with guideline recommendations. However, contrary to guidelines, dual therapy and fixed-dose combination decreased after publication of the 2017 Hypertension Clinical Practice Guidelines (9% and 11% decrease in 2018-2019 for dual therapy and fixed-dose combination, respectively, compared to 2015-2017), and thiazide diuretics decreased among Black patients after the JNC 8 report (6% lower in 2018-2019 compared to 2010-2014). CONCLUSIONS: Adherence to guidelines on prescribing antihypertensive medication was inconsistent, presenting an opportunity for interventions to achieve better blood pressure control in the US population.

Association between SARS-CoV-2 infection and select symptoms and conditions 31 to 150 days after testing among children and adults.

BACKGROUND: An increasing number of studies have described new and persistent symptoms and conditions as potential post-acute sequelae of SARS-CoV-2 infection (PASC). However, it remains unclear whether certain symptoms or conditions occur more frequently among persons with SARS-CoV-2 infection compared with those never infected with SARS-CoV-2. We compared the occurrence of specific COVID-associated symptoms and conditions as potential PASC 31- to 150-day following a SARS-CoV-2 test among adults and children with positive and negative test results. METHODS: We conducted a retrospective cohort study using electronic health record (EHR) data from 43 PCORnet sites participating in a national COVID-19 surveillance program. This study included 3,091,580 adults (316,249 SARS-CoV-2 positive; 2,775,331 negative) and 675,643 children (62,131 positive; 613,512 negative) who had a SARS-CoV-2 laboratory test during March 1, 2020-May 31, 2021 documented in their EHR. We used logistic regression to calculate the odds of having a symptom and Cox models to calculate the risk of having a newly diagnosed condition associated with a SARS-CoV-2 positive test. RESULTS: After adjustment for baseline covariates, hospitalized adults and children with a positive test had increased odds of being diagnosed with ≥ 1 symptom (adults: adjusted odds ratio[aOR], 1.17[95% CI, 1.11-1.23]; children: aOR, 1.18[95% CI, 1.08-1.28]) or shortness of breath (adults: aOR, 1.50[95% CI, 1.38-1.63]; children: aOR, 1.40[95% CI, 1.15-1.70]) 31-150 days following a SARS-CoV-2 test compared with hospitalized individuals with a negative test. Hospitalized adults with a positive test also had increased odds of being diagnosed with ≥ 3 symptoms or fatigue compared with those testing negative. The risks of being newly diagnosed with type 1 or type 2 diabetes (adjusted hazard ratio[aHR], 1.25[95% CI, 1.17-1.33]), hematologic disorders (aHR, 1.19[95% CI, 1.11-1.28]), or respiratory disease (aHR, 1.44[95% CI, 1.30-1.60]) were higher among hospitalized adults with a positive test compared with those with a negative test. Non-hospitalized adults with a positive test also had higher odds or increased risk of being diagnosed with certain symptoms or conditions. CONCLUSIONS: Patients with SARS-CoV-2 infection, especially those who were hospitalized, were at higher risk of being diagnosed with certain symptoms and conditions after acute infection.

A Narrative Review of Public Health Interventions for Childhood Obesity.

PURPOSE OF REVIEW: Public health interventions that intervene on macrolevel systems hold the promise of reducing childhood obesity at the population level through prevention. The purpose of this review is to highlight some of the recent and best scientific evidence related to public health interventions for the prevention of childhood obesity. We provide a narrative review of scientific evidence for six categories of public health interventions and their impact on childhood obesity: federal nutrition assistance programs, programs implemented in early care and education centers, interventions to support healthy nutrition and physical activity in schools, community-based programs and policies, labeling policies and marketing to children, and taxes on sugar sweetened beverages (SSB). RECENT FINDINGS: Federal nutrition assistance programs have the strongest evidence to support reduction in childhood obesity and serve populations with the highest prevalence of childhood obesity. Other interventions including SSB taxes, community-wide interventions, and interventions at schools and early care and education centers also show significant improvements in child weight status. Overall public health interventions have strong evidence to support widespread implementation in service of reducing childhood obesity rates at the population level. To effectively address the recalcitrant childhood obesity epidemic, multi-pronged solutions are needed. The current evidence for public health obesity interventions is consistent with the paradigm that recognizes the importance of macrolevel systems influences on childhood obesity: interventions that are most effective intervene at macrolevels.

Cost Effectiveness of Calorie Labeling at Large Fast-Food Chains Across the U.S.

INTRODUCTION: Calorie labeling of standard menu items has been implemented at large restaurant chains across the U.S. since 2018. The objective of this study was to evaluate the cost effectiveness of calorie labeling at large U.S. fast-food chains. METHODS: This study evaluated the national implementation of calorie labeling at large fast-food chains from a modified societal perspective and projected its cost effectiveness over a 10-year period (2018-2027) using the Childhood Obesity Intervention Cost-Effectiveness Study microsimulation model. Using evidence from over 67 million fast-food restaurant transactions between 2015 and 2019, the impact of calorie labeling on calorie consumption and obesity incidence was projected. Benefits were estimated across all racial, ethnic, and income groups. Analyses were performed in 2022. RESULTS: Calorie labeling is estimated to be cost saving; prevent 550,000 cases of obesity in 2027 alone (95% uncertainty interval=518,000; 586,000), including 41,500 (95% uncertainty interval=33,700; 50,800) cases of childhood obesity; and save $22.60 in healthcare costs for every $1 spent by society in implementation costs. Calorie labeling is also projected to prevent cases of obesity across all racial and ethnic groups (range between 126 and 185 cases per 100,000 people) and all income groups (range between 152 and 186 cases per 100,000 people). CONCLUSIONS: Calorie labeling at large fast-food chains is estimated to be a cost-saving intervention to improve long-term population health. Calorie labeling is a low-cost intervention that is already implemented across the U.S. in large chain restaurants.

Implementation of a Scalable Online Weight Management Programme in Clinical Settings: Protocol for the PROPS 2.0 Programme (Partnerships for Reducing Overweight and Obesity with Patient-Centered Strategies 2.0).

INTRODUCTION: There is an urgent need for scalable strategies for treating overweight and obesity in clinical settings. PROPS 2.0 (Partnerships for Reducing Overweight and Obesity with Patient-Centered Strategies 2.0) aims to adapt and implement the combined intervention from the PROPS Study at scale, in a diverse cross-section of patients and providers. METHODS AND ANALYSIS: We are implementing PROPS 2.0 across a variety of clinics at Brigham and Women's Hospital, targeting enrolment of 5000 patients. Providers can refer patients or patients can self-refer. Eligible patients must be ≥20 years old and have a body mass index (BMI) of ≥30 kg/m2 or a BMI of 25-29.9 kg/m2 plus another cardiovascular risk factor or obesity-related condition. After enrolment, patients register for the RestoreHealth online programme/app (HealthFleet Inc.) and participate for 12 months. Patients can engage with the programme and receive personalized feedback from a coach. Patient navigators help to enrol patients, enter updates in the electronic health record, and refer patients to additional resources. The RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework is guiding the evaluation. ETHICS AND DISSEMINATION: The Mass General Brigham Human Research Committee approved this protocol. An implementation guide will be created and disseminated, to help other sites adopt the intervention in the future. TRIAL REGISTRATION NUMBER: NCT0555925.

The impact of the federal menu labeling law on the sentiment of Twitter discussions about restaurants and food retailers: An interrupted time series analysis.

The US federal menu labeling law, implemented on May 7 th 2018, required that restaurant chains post calorie counts on menu items. The purpose of this study was to analyze the change in public sentiment, using Twitter data, regarding eight restaurant chains before and after the calorie labeling law's implementation. Twitter data was mined from Twitter's application programming interface (API) for this study from the calendar year 2018; 2016 and was collected as a control. We selected restaurant chains that had a range of compliance dates with the law. Tweets about each chain were filtered by brand-specific keywords, and Valence Aware Dictionary and sEntiment Reasoner (VADER) sentiment analysis was applied to receive a continuous compound score (-1-1) of how positive (1) or negative (-1) each tweet was. Controlled Interrupted Time Series (CITS) was performed with Ordinary Least Squares (OLS) Regression on 2018 and 2016 series of compound scores for each brand, and level and trend changes were calculated. Most restaurant chains that implemented the federal menu calorie labeling law experienced no change or a small change in level or trend in sentiment after they implemented labeling. Chains experienced mildly more negative sentiment right after the law was implemented, with attenuation of this effect over time. Calorie labeling did not have a strong effect on the public's perception of food brands over the long-term on Twitter and may imply the need for greater efforts to change the sentiment towards unhealthy restaurant chains.

Association Between Hypertension and Diabetes Control and COVID-19 Severity: National Patient-Centered Clinical Research Network, United States, March 2020 to February 2022.

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.

A Technology-Driven, Healthcare-Based Intervention to Improve Family Beverage Choices: Results from a Pilot Randomized Trial in the United States.

Background: Healthcare-based interventions to address sugary beverage intake could achieve broad reach, but intensive in-person interventions are unsustainable in clinical settings. Technology-based interventions may provide an alternative, scalable approach. Methods: Within an academic health system in the United States that already performs electronic health record-based sugary drink screening, we conducted a pilot randomized trial of a technology-driven family beverage choice intervention. The goal of the intervention was to reduce sugar-sweetened beverage (SSB) and fruit juice (FJ) consumption in 60 parent-child dyads, in which children were 1-8 years old. The pediatrician-initiated intervention consisted of a water promotion toolkit, a video, a mobile phone application, and 14 interactive voice-response phone calls to parents over 6 months. The study was conducted between June 2021 and May 2022. The aim of the pilot study was to assess the potential feasibility and efficacy of the newly developed intervention. Results: Intervention fidelity was excellent, and acceptability was high for all intervention components. Children in both the intervention and the control groups substantially decreased their consumption of SSB and FJ over follow-up (mean combined baseline 2.5 servings/day vs. 1.4/day at 6 months) and increased water consumption, but constrained linear mixed-effects models showed no differences between groups on these measures. Compared to parents in the control group, intervention parents had larger decreases in SSB intake at 3 months (-0.80 (95% CI: -1.54, -0.06, p = 0.03) servings daily), but these differences were not sustained at 6 months. Conclusion: These findings suggest that, though practical to implement in a clinical care setting and acceptable to a diverse participant group, our multicomponent intervention may not be universally necessary to achieve meaningful behavior changes around family beverage choice. A lower-intensity intervention, such as EHR-based clinical screening alone, might be a less resource-intense way for health systems to achieve similar behavioral outcomes. Future studies might therefore explore whether, instead of applying a full intervention to all families whose children overconsume SSB or FJ, a stepped approach, starting with clinical screening and brief counseling, could be a better use of health system resources.

Developing Effective Strategies for Obesity Prevention.

Nutrition policies can work with clinical treatments to address the obesity epidemic. The United States has passed beverage taxes at the local level and calorie labeling mandates at the federal level to encourage healthier consumption. Nutritional changes to federal nutrition programs have been either implemented or suggested; evidence shows that the changes that have been implemented have resulted in improvements in diet quality and are cost-effective in decreasing the increase in obesity prevalence. A comprehensive policy agenda that addresses risk of obesity on multiple levels of the food supply will have meaningful long-term effects on obesity prevalence.

Data-driven analysis to understand long COVID using electronic health records from the RECOVER initiative.

Recent studies have investigated post-acute sequelae of SARS-CoV-2 infection (PASC, or long COVID) using real-world patient data such as electronic health records (EHR). Prior studies have typically been conducted on patient cohorts with specific patient populations which makes their generalizability unclear. This study aims to characterize PASC using the EHR data warehouses from two large Patient-Centered Clinical Research Networks (PCORnet), INSIGHT and OneFlorida+, which include 11 million patients in New York City (NYC) area and 16.8 million patients in Florida respectively. With a high-throughput screening pipeline based on propensity score and inverse probability of treatment weighting, we identified a broad list of diagnoses and medications which exhibited significantly higher incidence risk for patients 30-180 days after the laboratory-confirmed SARS-CoV-2 infection compared to non-infected patients. We identified more PASC diagnoses in NYC than in Florida regarding our screening criteria, and conditions including dementia, hair loss, pressure ulcers, pulmonary fibrosis, dyspnea, pulmonary embolism, chest pain, abnormal heartbeat, malaise, and fatigue, were replicated across both cohorts. Our analyses highlight potentially heterogeneous risks of PASC in different populations.

Obesity prevention across the US: A review of state-level policies from 2009 to 2019.

Objective: Uniquely, state legislators may enact obesity prevention policies tailored to each state's needs and take diverse policy approaches to address obesity prevalence. The objective of this study was to identify and describe state-level obesity-related policies between 2009 and 2019. Methods: Using a database of legislation covering 2009-2019, researchers categorized obesity-related legislation by status (proposed/enacted), topic, and environment impacted. Researchers determined the number of policies proposed; enacted, by political party control; obesity prevalence, by states over time. Results: 3256 obesity-related policies were proposed among 50 states and Washington DC between 2009 and 2019. Collectively, 18% (593) of policies were enacted; California (96), New and Jersey (57) enacted the most. Across environment and topics, the most enacted policies categorized in school environment (226) and school nutrition (150) topic area. Most policies were proposed (496) and enacted (77) in 2011. On average, Democrat-controlled states had higher enactment rates than Republican-controlled states, as did states with lower (vs. higher) obesity prevalence. Conclusions: States have actively pursued obesity-related legislation across multiple topics and environments from 2009 to 2019, with mixed enactment rates. Evaluating the impact of these policies, alone and in combination, will be important to determine whether these state-level efforts reduce obesity.

Changes in Dental Outcomes After Implementation of the Philadelphia Beverage Tax.

INTRODUCTION: Beverage taxes are associated with declines in sugar-sweetened beverage sales and consumption, but few studies have evaluated the associations of these taxes with health outcomes. This study analyzed changes in dental decay after the implementation of the Philadelphia sweetened beverage tax. METHODS: Electronic dental record data were obtained on 83,260 patients living in Philadelphia and control areas from 2014 to 2019. Difference-in-differences analyses compared the number of new Decayed, Missing, and Filled Teeth with that of new Decayed, Missing, and Filled Surfaces before (January 2014-December 2016) and after (January 2019-December 2019) tax implementation in Philadelphia and control patients. Analyses were conducted in older children/adults (aged ≥15 years) and younger children (aged <15 years). Subgroup analyses stratified by Medicaid status. Analyses were conducted in 2022. RESULTS: The number of new Decayed, Missing, and Filled Teeth did not change after tax implementation in Philadelphia in panel analyses of older children/adults (difference-in-differences= -0.02, 95% CI= -0.08, 0.03) or younger children (difference-in-differences=0.07, 95% CI= -0.08, 0.23). There were similarly no post-tax changes in the number of new Decayed, Missing, and Filled Surfaces. However, in cross-sectional samples of patients on Medicaid, the number of new Decayed, Missing, and Filled Teeth was lower after tax implementation in older children/adults (difference-in-differences= -0.18, 95% CI= -0.34, -0.03; -22% decline) and younger children (difference-in-differences= -0.22, 95% CI= -0.46, 0.01; -30% decline), with similar results for number of new Decayed, Missing, and Filled Surfaces. CONCLUSIONS: The Philadelphia beverage tax was not associated with reduced tooth decay in the general population, but it was associated with reduced tooth decay in adults and children on Medicaid, suggesting potential health benefits for low-income populations.

Excess burden of respiratory and abdominal conditions following COVID-19 infections during the ancestral and Delta variant periods in the United States: An EHR-based cohort study from the RECOVER Program.

Importance: The frequency and characteristics of post-acute sequelae of SARS-CoV-2 infection (PASC) may vary by SARS-CoV-2 variant. Objective: To characterize PASC-related conditions among individuals likely infected by the ancestral strain in 2020 and individuals likely infected by the Delta variant in 2021. Design: Retrospective cohort study of electronic medical record data for approximately 27 million patients from March 1, 2020-November 30, 2021. Setting: Healthcare facilities in New York and Florida. Participants: Patients who were at least 20 years old and had diagnosis codes that included at least one SARS-CoV-2 viral test during the study period. Exposure: Laboratory-confirmed COVID-19 infection, classified by the most common variant prevalent in those regions at the time. Main Outcomes and Measures: Relative risk (estimated by adjusted hazard ratio [aHR]) and absolute risk difference (estimated by adjusted excess burden) of new conditions, defined as new documentation of symptoms or diagnoses, in persons between 31-180 days after a positive COVID-19 test compared to persons with only negative tests during the 31-180 days after the last negative test. Results: We analyzed data from 560,752 patients. The median age was 57 years; 60.3% were female, 20.0% non-Hispanic Black, and 19.6% Hispanic. During the study period, 57,616 patients had a positive SARS-CoV-2 test; 503,136 did not. For infections during the ancestral strain period, pulmonary fibrosis, edema (excess fluid), and inflammation had the largest aHR, comparing those with a positive test to those with a negative test, (aHR 2.32 [95% CI 2.09 2.57]), and dyspnea (shortness of breath) carried the largest excess burden (47.6 more cases per 1,000 persons). For infections during the Delta period, pulmonary embolism had the largest aHR comparing those with a positive test to a negative test (aHR 2.18 [95% CI 1.57, 3.01]), and abdominal pain carried the largest excess burden (85.3 more cases per 1,000 persons). Conclusions and Relevance: We documented a substantial relative risk of pulmonary embolism and large absolute risk difference of abdomen-related symptoms after SARS-CoV-2 infection during the Delta variant period. As new SARS-CoV-2 variants emerge, researchers and clinicians should monitor patients for changing symptoms and conditions that develop after infection.

Understanding pediatric long COVID using a tree-based scan statistic approach: an EHR-based cohort study from the RECOVER Program.

Objectives: Post-acute sequalae of SARS-CoV-2 infection (PASC) is not well defined in pediatrics given its heterogeneity of presentation and severity in this population. The aim of this study is to use novel methods that rely on data mining approaches rather than clinical experience to detect conditions and symptoms associated with pediatric PASC. Materials and Methods: We used a propensity-matched cohort design comparing children identified using the new PASC ICD10CM diagnosis code (U09.9) (N = 1309) to children with (N = 6545) and without (N = 6545) SARS-CoV-2 infection. We used a tree-based scan statistic to identify potential condition clusters co-occurring more frequently in cases than controls. Results: We found significant enrichment among children with PASC in cardiac, respiratory, neurologic, psychological, endocrine, gastrointestinal, and musculoskeletal systems, the most significant related to circulatory and respiratory such as dyspnea, difficulty breathing, and fatigue and malaise. Discussion: Our study addresses methodological limitations of prior studies that rely on prespecified clusters of potential PASC-associated diagnoses driven by clinician experience. Future studies are needed to identify patterns of diagnoses and their associations to derive clinical phenotypes. Conclusion: We identified multiple conditions and body systems associated with pediatric PASC. Because we rely on a data-driven approach, several new or under-reported conditions and symptoms were detected that warrant further investigation.

Risk Factors and Predictive Modeling for Post-Acute Sequelae of SARS-CoV-2 Infection: Findings from EHR Cohorts of the RECOVER Initiative.

Background: Patients who were SARS-CoV-2 infected could suffer from newly incidental conditions in their post-acute infection period. These conditions, denoted as the post-acute sequelae of SARS-CoV-2 infection (PASC), are highly heterogeneous and involve a diverse set of organ systems. Limited studies have investigated the predictability of these conditions and their associated risk factors. Method: In this retrospective cohort study, we investigated two large-scale PCORnet clinical research networks, INSIGHT and OneFlorida+, including 11 million patients in the New York City area and 16.8 million patients from Florida, to develop machine learning prediction models for those who are at risk for newly incident PASC and to identify factors associated with newly incident PASC conditions. Adult patients aged 20 with SARS-CoV-2 infection and without recorded infection between March 1st, 2020, and November 30th, 2021, were used for identifying associated factors with incident PASC after removing background associations. The predictive models were developed on infected adults. Results: We find several incident PASC, e.g., malnutrition, COPD, dementia, and acute kidney failure, were associated with severe acute SARS-CoV-2 infection, defined by hospitalization and ICU stay. Older age and extremes of weight were also associated with these incident conditions. These conditions were better predicted (C-index >0.8). Moderately predictable conditions included diabetes and thromboembolic disease (C-index 0.7-0.8). These were associated with a wider variety of baseline conditions. Less predictable conditions included fatigue, anxiety, sleep disorders, and depression (C-index around 0.6). Conclusions: This observational study suggests that a set of likely risk factors for different PASC conditions were identifiable from EHRs, predictability of different PASC conditions was heterogeneous, and using machine learning-based predictive models might help in identifying patients who were at risk of developing incident PASC.

Racial/Ethnic Disparities in Post-acute Sequelae of SARS-CoV-2 Infection in New York: an EHR-Based Cohort Study from the RECOVER Program.

BACKGROUND: Compared to white individuals, Black and Hispanic individuals have higher rates of COVID-19 hospitalization and death. Less is known about racial/ethnic differences in post-acute sequelae of SARS-CoV-2 infection (PASC). OBJECTIVE: Examine racial/ethnic differences in potential PASC symptoms and conditions among hospitalized and non-hospitalized COVID-19 patients. DESIGN: Retrospective cohort study using data from electronic health records. PARTICIPANTS: 62,339 patients with COVID-19 and 247,881 patients without COVID-19 in New York City between March 2020 and October 2021. MAIN MEASURES: New symptoms and conditions 31-180 days after COVID-19 diagnosis. KEY RESULTS: The final study population included 29,331 white patients (47.1%), 12,638 Black patients (20.3%), and 20,370 Hispanic patients (32.7%) diagnosed with COVID-19. After adjusting for confounders, significant racial/ethnic differences in incident symptoms and conditions existed among both hospitalized and non-hospitalized patients. For example, 31-180 days after a positive SARS-CoV-2 test, hospitalized Black patients had higher odds of being diagnosed with diabetes (adjusted odds ratio [OR]: 1.96, 95% confidence interval [CI]: 1.50-2.56, q<0.001) and headaches (OR: 1.52, 95% CI: 1.11-2.08, q=0.02), compared to hospitalized white patients. Hospitalized Hispanic patients had higher odds of headaches (OR: 1.62, 95% CI: 1.21-2.17, q=0.003) and dyspnea (OR: 1.22, 95% CI: 1.05-1.42, q=0.02), compared to hospitalized white patients. Among non-hospitalized patients, Black patients had higher odds of being diagnosed with pulmonary embolism (OR: 1.68, 95% CI: 1.20-2.36, q=0.009) and diabetes (OR: 2.13, 95% CI: 1.75-2.58, q<0.001), but lower odds of encephalopathy (OR: 0.58, 95% CI: 0.45-0.75, q<0.001), compared to white patients. Hispanic patients had higher odds of being diagnosed with headaches (OR: 1.41, 95% CI: 1.24-1.60, q<0.001) and chest pain (OR: 1.50, 95% CI: 1.35-1.67, q < 0.001), but lower odds of encephalopathy (OR: 0.64, 95% CI: 0.51-0.80, q<0.001). CONCLUSIONS: Compared to white patients, patients from racial/ethnic minority groups had significantly different odds of developing potential PASC symptoms and conditions. Future research should examine the reasons for these differences.

Food Allergy Management for Adolescents Using Behavioral Incentives: A Randomized Trial.

OBJECTIVE: We sought to evaluate the use of behavioral economics approaches to promote the carrying of epinephrine auto-injectors (EAIs) among adolescents with food allergies. We hypothesized that adolescents who receive frequent text message nudges (Intervention 1) or frequent text message nudges plus modest financial incentives (Intervention 2) would be more likely to carry their epinephrine than members of the usual care control group. METHODS: We recruited 131 adolescents ages 15 to 19 with a food allergy and a current prescription for epinephrine to participate in a cohort multiple randomized controlled trial. Participants were randomly assigned to participate in Intervention 1, Intervention 2, or to receive usual care. The primary outcome was consistency of epinephrine-carrying, measured as the proportion of checkpoints at which a participant could successfully demonstrate they were carrying their EAI, with photo-documentation of the device. RESULTS: During Intervention 1, participants who received the intervention carried their EAI 28% of the time versus 38% for control group participants (P = .06). During Intervention 2, participations who received the intervention carried their EAI 45% of the time versus 23% for control group participants (P = .002). CONCLUSIONS: Text message nudges alone were unsuccessful at promoting EAI-carrying but text message nudges combined with modest financial incentives almost doubled EAI-carriage rates among those who received the intervention compared with the control group. However, even with the intervention, adolescents with food allergies carried their EAI <50% of the time. Alternative strategies for making EAIs accessible to adolescents at all times should be implemented.

Nutritional Composition and Purchasing Patterns of Supermarket Prepared Foods Over Time.

INTRODUCTION: Prepared (ready-to-eat) foods are sold in >90% of U.S. supermarkets, but little is known about their nutritional quality. This study examined trends in purchases of supermarket prepared foods and compared their nutritional profile with that of supermarket packaged foods and restaurant foods. METHODS: Nutrition data were obtained on prepared foods sold from 2015 to 2019 in 2 supermarket chains (∼1,200 stores). One chain (193 stores) provided transaction-level sales data from 2015 to 2017. Analyses (conducted in 2021-2022) examined trends in the number of different prepared foods offered by the chains and trends in purchases of calories, total sugar, saturated fat, and sodium from prepared foods. Calorie and nutrient densities (i.e., per 100 g of food) and prevalence of being high in calories or nutrients (on the basis of Chilean standards) were analyzed among supermarket prepared foods, supermarket packaged foods, and restaurant foods consumed in the National Health and Nutrition Examination Surveys 2015-2018. RESULTS: The number of different prepared foods offered at supermarket chains increased from 1,930 in 2015 to 4,113 in 2019. Calories per transaction purchased from supermarket prepared foods increased by 1.0 calories/month (95% CI=0.8, 1.1), a ∼3% annual increase, with similar trends for other nutrients. At supermarkets, >90% of prepared bakery and deli items and 61% of prepared entrees/sides were high in calories or another nutrient of concern, similar to supermarket packaged foods and restaurant foods. CONCLUSIONS: Supply of and demand for supermarket prepared foods have grown substantially over time. These trends are concerning given these foods' overall poor nutritional quality.

Data-driven identification of post-acute SARS-CoV-2 infection subphenotypes.

The post-acute sequelae of SARS-CoV-2 infection (PASC) refers to a broad spectrum of symptoms and signs that are persistent, exacerbated or newly incident in the period after acute SARS-CoV-2 infection. Most studies have examined these conditions individually without providing evidence on co-occurring conditions. In this study, we leveraged the electronic health record data of two large cohorts, INSIGHT and OneFlorida+, from the national Patient-Centered Clinical Research Network. We created a development cohort from INSIGHT and a validation cohort from OneFlorida+ including 20,881 and 13,724 patients, respectively, who were SARS-CoV-2 infected, and we investigated their newly incident diagnoses 30-180 days after a documented SARS-CoV-2 infection. Through machine learning analysis of over 137 symptoms and conditions, we identified four reproducible PASC subphenotypes, dominated by cardiac and renal (including 33.75% and 25.43% of the patients in the development and validation cohorts); respiratory, sleep and anxiety (32.75% and 38.48%); musculoskeletal and nervous system (23.37% and 23.35%); and digestive and respiratory system (10.14% and 12.74%) sequelae. These subphenotypes were associated with distinct patient demographics, underlying conditions before SARS-CoV-2 infection and acute infection phase severity. Our study provides insights into the heterogeneity of PASC and may inform stratified decision-making in the management of PASC conditions.

Cleaning of anthropometric data from PCORnet electronic health records using automated algorithms.

Objective: To demonstrate the utility of growthcleanr, an anthropometric data cleaning method designed for electronic health records (EHR). Materials and Methods: We used all available pediatric and adult height and weight data from an ongoing observational study that includes EHR data from 15 healthcare systems and applied growthcleanr to identify outliers and errors and compared its performance in pediatric data with 2 other pediatric data cleaning methods: (1) conditional percentile (cp) and (2) PaEdiatric ANthropometric measurement Outlier Flagging pipeline (peanof). Results: 687 226 children (<20 years) and 3 267 293 adults contributed 71 246 369 weight and 51 525 487 height measurements. growthcleanr flagged 18% of pediatric and 12% of adult measurements for exclusion, mostly as carried-forward measures for pediatric data and duplicates for adult and pediatric data. After removing the flagged measurements, 0.5% and 0.6% of the pediatric heights and weights and 0.3% and 1.4% of the adult heights and weights, respectively, were biologically implausible according to the CDC and other established cut points. Compared with other pediatric cleaning methods, growthcleanr flagged the most measurements for exclusion; however, it did not flag some more extreme measurements. The prevalence of severe pediatric obesity was 9.0%, 9.2%, and 8.0% after cleaning by growthcleanr, cp, and peanof, respectively. Conclusion: growthcleanr is useful for cleaning pediatric and adult height and weight data. It is the only method with the ability to clean adult data and identify carried-forward and duplicates, which are prevalent in EHR. Findings of this study can be used to improve the growthcleanr algorithm.