Objective: Large international comparisons describing the clinical characteristics of patients with COVID-19 are limited. The aim of the study was to perform a large-scale descriptive characterization of COVID-19 patients with asthma. Methods: We included nine databases contributing data from January to June 2020 from the US, South Korea (KR), Spain, UK and the Netherlands. We defined two cohorts of COVID-19 patients (‘diagnosed’ and ‘hospitalized’) based on COVID-19 disease codes. We followed patients from COVID-19 index date to 30 days or death. We performed descriptive analysis and reported the frequency of characteristics and outcomes in people with asthma defined by codes and prescriptions. Results: The diagnosed and hospitalized cohorts contained 666,933 and 159,552 COVID-19 patients respectively. Exacerbation in people with asthma was recorded in 1.6-8.6% of patients at presentation. Asthma prevalence ranged from 6.2% (95% CI 5.7-6.8) to 18.5% (95% CI 18.2-18.8) in the diagnosed cohort and 5.2% (95% CI 4.0-6.8) to 20.5% (95% CI 18.6-22.6) in the hospitalized cohort. Asthma patients with COVID-19 had high prevalence of comorbidity including hypertension, heart disease, diabetes and obesity. Mortality ranged from 2.1% (95% CI 1.8-2.4) to 16.9% (95% CI 13.8-20.5) and similar or lower compared to COVID-19 patients without asthma. Acute respiratory distress syndrome occurred in 15-30% of hospitalized COVID-19 asthma patients. Conclusion: The prevalence of asthma among COVID-19 patients varies internationally. Asthma patients with COVID-19 have high comorbidity. The prevalence of asthma exacerbation at presentation was low. Whilst mortality was similar among COVID-19 patients with and without asthma, this could be confounded by differences in clinical characteristics. Further research could help identify high-risk asthma patients. KEY MESSAGES Asthma prevalence in COVID-19 patients varied internationally (5.2-20.5%).The prevalence of asthma exacerbation at presentation with COVID-19 in diagnosed and hospitalized patients was low.Comorbidities were common in COVID-19 patients with asthma. Supplemental data for this article is available online at https://doi.org/10.1080/02770903.2021.2025392 .

Purpose: Routinely collected real world data (RWD) have great utility in aiding the novel coronavirus disease (COVID-19) pandemic response. Here we present the international Observational Health Data Sciences and Informatics (OHDSI) Characterizing Health Associated Risks and Your Baseline Disease In SARS-COV-2 (CHARYBDIS) framework for standardisation and analysis of COVID19 RWD. Patients and Methods: We conducted a descriptive retrospective database study using a federated network of data partners in the United States, Europe (the Netherlands, Spain, the UK, Germany, France and Italy) and Asia (South Korea and China). The study protocol and analytical package were released on 11th June 2020 and are iteratively updated via GitHub. We identified three non mutually exclusive cohorts of 4,537,153 individuals with a clinical COVID-19 diagnosis or positive test, 886,193 hospitalized with COVID-19, and 113,627 hospitalized with COVID-19 requiring intensive services. Results: We aggregated over 22,000 unique characteristics describing patients with COVID-19. All comorbidities, symptoms, medications, and outcomes are described by cohort in aggregate counts and are readily available online. Globally, we observed similarities in the USA and Europe: more women diagnosed than men but more men hospitalized than women, most diagnosed cases between 25 and 60 years of age versus most hospitalized cases between 60 and 80 years of age. South Korea differed with more women than men hospitalized. Common comorbidities included type 2 diabetes, hypertension, chronic kidney disease and heart disease. Common presenting symptoms were dyspnea, cough and fever. Symptom data availability was more common in hospitalized cohorts than diagnosed. Conclusion: We constructed a global, multi-centre view to describe trends in COVID-19 progression, management and evolution over time. By characterising baseline variability in patients and geography, our work provides critical context that may otherwise be misconstrued as data quality issues. This is important as we perform studies on adverse events of special interest in COVID-19 vaccine surveillance.

Adolescent emotional health and well-being have been of growing interest as a result of the disproportionate impact that the COVID-19 syndemic has had on this population. Currently, most available evidence approaches this problem from an adult-centered perspective. Our study used visual methodology to critically analyze the sociocultural and environmental factors which may promote emotional health in adolescents residing in a crosscultural neighborhood in Barcelona. Photo-elicitation was used to capture the perspective of 86 adolescents aged 15-17 years in a privately-owned but state-funded school. The sample included 43 boys, 42 girls, and 1 person whose gender was not specified. 44 participants had at least one parent born outside of Spain. Each participant submitted a photograph, which was used to share personal narratives by inspiring discussions about the context and significance of the image in group settings and through individual written reflections. The resulting imagetext units were analyzed collaboratively during group discussions, followed by data organization, coding, and thematic analysis. Most photographs were situated in the Barcelona metropolitan area, and the most commonly photographed location was inside the home. Well-being was intricately tied to emotional bonds with family, pets, and, to a lesser extent, friendship. Additionally, well-being was associated with nature, physical activity, and creativity. Important gender differences were observed highlighting the continued influence of conventional gender norms, and the family’s migration history emerged as a relevant axis influencing emotional health. This study highlights the importance of forging participatory spaces for dialogue, both among peers and between adolescents and adults. By amplifying the voices and experiences of adolescents, these findings contribute to a nuanced understanding of the factors influencing emotional well-being and can provide insight into future research and interventions by directly considering the adolescent perspective.

BACKGROUND: Understanding the relationship between serum ferritin levels and cardiovascular outcomes in type 2 diabetes is crucial for improving risk stratification and guiding therapeutic interventions aimed at preventing major adverse cardiovascular events (MACE). This study aimed to identify distinct clusters of individuals with type 2 diabetes who have varying risks of MACE using a data-driven clustering approach. METHODS: This retrospective cohort study analyzed data from 49,506 individuals within a multicenter, population-based primary care registry in Catalonia, Spain. Individuals diagnosed with type 2 diabetes at age 35 or older were recruited between January 2010 and December 2021 and followed for at least 10 years. Biomarkers associated with cardiovascular risk-including serum glucose, HbA1c, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, blood pressure, serum ferritin, leukocyte, and monocyte counts-were examined. Clustering analysis was applied to identify patient subgroups, and Cox proportional hazards models were used to assess associations with cerebrovascular events, coronary events, and composite MACE. RESULTS: Five distinct clusters were identified, characterized by differences in serum glucose, HbA1c, lipid profiles, blood pressure, and serum ferritin levels. Individuals with discordantly high serum ferritin levels relative to their body mass index (BMI) exhibited a lower risk of adverse cardiovascular outcomes. In men, hazard ratios (HR) were 0.68 (95% confidence interval [CI]: 0.53-0.87) for cerebrovascular events, 0.65 (95% CI 0.49-0.88) for coronary events, and 0.68 (95% CI 0.56-0.83) for MACE. In women, HRs were 0.81 (95% CI 0.67-0.92) for cerebrovascular events, 0.73 (95% CI 0.57-0.95) for coronary events, and 0.79 (95% CI 0.67-0.92) for MACE. CONCLUSIONS: Individuals with type 2 diabetes who exhibit higher-than-expected serum ferritin levels relative to their BMI may have a lower risk of cardiovascular events. These findings suggest that ferritin may play a more complex role in cardiovascular risk than previously assumed and highlight the potential for refined risk stratification strategies in type 2 diabetes management.

OBJECTIVES: The Observational Medical Outcomes Partnership common data model (OMOP-CDM) is a useful tool for large-scale network analysis but currently lacks a structured approach to pregnancy episodes. We aimed to develop and implement a perinatal expansion for the OMOP-CDM to facilitate perinatal network research. METHODS: We collaboratively developed a perinatal expansion with input from domain experts and stakeholders to reach consensus. The structure and vocabularies followed the OMOP-CDM ontological framework principles. We tested the expansion using SIDIAP and Norwegian databases. We developed a diagnostics package for quality control assessment and conducted a descriptive analysis on the captured perinatal data mapped to the OMOP-CDM. RESULTS: The perinatal expansion consists of a pregnancy table and an infant table, each with required and optional variables incorporated into standardized vocabularies. Quality assessment of the perinatal expansion table in SIDIAP and Norwegian databases demonstrated accurate capture of perinatal characteristics. Descriptive analysis measured the number of pregnancies (SIDIAP: 646 530; Norway: 746 671), pregnancy outcomes (e.g., 0.5% stillbirths in SIDIAP and 0.4% in Norway), gestational length (median [IQR] in days, SIDIAP: 273 [56-280]; Norway: 280 [273-286]), number of infants (Norway: 758 806), and birth weight (median [IQR] in grams, Norway: 3520 [3175-3860)], among other relevant variables. DISCUSSION AND CONCLUSION: We developed and implemented a perinatal expansion that captures important variables for perinatal research and allows interoperability with existing tables in the OMOP-CDM, which is expected to facilitate future network studies. The publicly available diagnostics package enables testing the implementation of the extension table and the quality and completeness of available data on pregnancy and pregnancy-related outcomes in databases mapped to the OMOP CDM.

This study examines remaining life expectancy (RLE) after a cancer diagnosis, focusing on age, sex, cancer type, and metabolic syndrome (MS) components, using data from the SIDIAP database in Catalonia (2006-2017). RLE was analyzed for 13 cancer types, stratified by sex and MS components. The cohort study includes 183,364 individuals followed from diagnosis until death, transfer, or study end (December 2017). RLE at age 68 (median diagnosis age) was calculated based on MS components (0, 1, 2, and = 3). Men aged 68 with 0 MS components had an RLE of 13.2 years, compared to 8.9 years for those with = 3 MS. Women had an RLE of 15.9 years with 0 MS components versus 11.4 years with = 3 MS. RLE varied by cancer type, with the highest RLE in men seen in prostate cancer and in women in non-Hodgkin lymphoma. The lowest RLE for both sexes was in pancreatic cancer. The largest differences between 0 and = 3 MS components were observed in non-Hodgkin lymphoma and the smallest in pancreatic cancer. Increased MS components were associated with reduced RLE in at least 8 cancer types for men and 9 for women. Prevention strategies targeting MS components could increase RLE in cancer patients.

BACKGROUND: The burden of childhood overweight and obesity attributable to ambient air pollution and a lack of urban green spaces (UGS) remains unknown. This study aimed to estimate the attributable cases of childhood overweight and obesity due to air pollution and insufficient UGS exposure in Barcelona, Spain. METHODS: We applied a quantitative health impact assessment approach. We collected childhood overweight and obesity prevalence levels and exposure data from 69 spatial basic health zones in Barcelona. We estimated particulate matter (PM(2.5)) and nitrogen dioxide (NO(2)) levels using land use regression models, normalized difference vegetation index (NDVI) levels using remote sensing and percentage of green area (%GA) using land use. We estimated relative risks, population attributable fractions, and preventable overweight/obesity cases in children under following scenarios: Compliance of World Health Organization (WHO) air quality guidelines (AQGs) for (1) PM(2.5) and (2) NO(2); achieving (3) city-target NDVI levels and (4) 25% green area (%GA) recommendations. The analyses were stratified by socioeconomic deprivation index (in quintiles). Uncertainty was quantified using Monte Carlos simulations. RESULTS: Compliance of WHO AQGs could prevent 0.4% [253 (95%CI, -604; 1086)] and 4.2% [3000 (95%CI, 1009; 4943)] of childhood overweight/obesity cases due to excess PM(2.5) and NO(2) levels in Barcelona, respectively. Compliance of NDVI and %GA targeted levels could prevent 6% [4094 (95%CI, 1698; 6379)] and 10% [6853 (95%CI, 1440; 12779)] of childhood overweight/obesity cases respectively. The preventable burdens of childhood overweight/obesity cases were slightly higher in middle-class socioeconomic areas due to the higher adverse exposure levels at baseline (high air pollution, less UGS). DISCUSSION: Compliance with WHO AQGs and achieving UGS targets can reduce childhood overweight and obesity levels in Barcelona, and potentially in other locations as well. This underscores the need for policies that foster healthier urban environments of high environmental quality in order to protect child health.

BACKGROUND: The prevalence of mental health disorders in children, teens, and young adults is rising at an alarming rate. This study aims to explore time trends in the incidence of mental disorders among young people in Catalonia, Spain from 2008 to 2022, focusing on the effects of the COVID-19 pandemic and from the perspective of social inequities. METHODS: A cohort study using primary care records from the SIDIAP database was conducted. It included 2,088,641 individuals aged 10 to 24 years. We examined the incidence of depressive, anxiety, eating, and attention deficit/hyperactivity disorders, stratified by sex, age, deprivation, and nationality. RESULTS: All disorders reflected an increasing trend throughout the study period: depressive disorders (IRR: 2.44, 95% CI: 2.31-2.59), anxiety disorders (IRR: 2.33, 95% CI: 2.27-2.39), ADHD (IRR: 2.33, 95%CI: 2.17-2.50), and eating disorders (IRR: 3.29, 95% CI: 3.01-3.59). A significant increase in incidence was observed after the outbreak of the COVID-19 pandemic. In 2022, anxiety disorders were most frequent, with an incidence rate (IR) of 2,537 per 100,000 persons-year (95% CI: 2,503-2,571). Depressive disorders followed with an IR of 471 (95% CI: 458-486), ADHD with an IR of 306 (95% CI: 295-317) and eating disorders with an IR of 249 (95% CI: 239-259). Significant associations were reported with sex, age, deprivation, and nationality. CONCLUSION: The incidence of all studied disorders has steadily increased, reaching unprecedented levels during the pandemic. Understanding these trends is essential for an appropriate healthcare response, while addressing the non-medical determinants, requires action across all sectors of society.