Alicia Abellan Ecija

Objetivos: 1. Estimar la exposición a la adiposidad a lo largo de la vida, incluyendo la edad de inicio y los años vividos con sobrepeso/obesidad, usando una base de datos poblacional longitudinal; 2. Investigar la asociación entre la exposición a la adiposidad a lo largo de la vida y el riesgo y la mortalidad por cáncer; 3. Investigar el papel de las comorbilidades y las intervenciones de pérdida de peso (cirugía bariátrica) en la asociación entre la exposición a la adiposidad a lo largo de la vida y el riesgo de cáncer. Fuente de información y métodos: utilizaremos datos de una base de datos prospectiva poblacional de España (SIDIAP). SIDIAP incluye registros electrónicos de atención primaria de salud pseudoanonimizados para >5,8 millones de personas. Los datos son recogidos por los profesionales de la salud durante visitas médicas desde 2006. Incluiremos personas de =2 años durante al menos un año. Implementaremos un enfoque de imputación múltiple de series temporales para tener información completa sobre el IMC para todos los participantes a diferentes edades. La adiposidad a lo largo de la vida se estimará utilizando valores de IMC repetidos a lo largo del tiempo. Los cocientes de riesgos se calcularán utilizando modelos de Cox y la no linealidad se estudiará utilizando splines cúbicos restringidos. Para el objetivo 3, el riesgo/mortalidad por cáncer estará relacionado en presencia/ausencia de comorbilidad o cirugía bariátrica. Impacto: Este proyecto mejorará sustancialmente nuestra comprensión del impacto de la adiposidad a lo largo del curso de la vida sobre el cáncer. Ayudará a identificar períodos críticos de la vida en los que se deben implementar estrategias de prevención y, por lo tanto, ayudará a mitigar los efectos del cáncer por sobrepeso/obesidad en la salud pública.

Las enfermedades reumáticas inflamatorias (IRMD) incluyendo la artritis reumatoide (AR), el lupus eritematoso sistémico (LES), la artritis psoriásica (APs), la esclerosis sistémica (SSc) y las espondiloartropatías (Spa) entre otras están asociadas con un aumento significativo de la morbilidad y mortalidad. La carga de enfermedad de dichas patologías en nuestro entorno no es bien conocida. Nuestros objetivos son:
1) Evaluar la carga de enfermedad de IRMD en Cataluña, estimando su prevalencia e incidencia,
2) determinar los factores independientes asociados con las complicaciones de las IRMD en comparación a la población sana, incluyendo la enfermedad coronaria, la enfermedad tromboembólica, la diabetes mellitus, las fracturas osteoporóticas, las infecciones graves, el cáncer y la insuficiencia renal crónica y
3) Estimar el impacto de las IRMD sobre la mortalidad en comparación a la población general.
Para ello proponemos un estudio poblacional retrospectivo que incluirá todos los casos identificados mediante códigos ICD-10 del programa del Sistema de Información para el Desarrollo de la Investigación en Atención Primaria (SIDIAP) del 2006 al 2021. El SIDIAP cuenta con información de mas de 5.7 millones de habitantes e incluye datos demográficos, diagnósticos, prescripciones/dispensaciones y fecha de muerte.
Se utilizará una cohorte de control sin IRMD apareada por el año de nacimiento, género, y estado socio-económico como grupo control.

«Rationale and Background
During the evaluation of the safety results of a clinical trial in patients with severe asthma, differences in rates of serious adverse events were observed in the experimental treatment arm compared to the control arm. In order to contextualise these differences, a non-interventional study was required to generate background rates of selected health outcomes in patients with severe asthma, with a disease definition that follows recently conducted clinical trials. The results of this study may inform future drug-related safety assessments in the same population.
The present study is to produce background information on the occurrence of the health outcomes in adolescent and adult patients with severe asthma using recent data.
Research Methods
Study design
Retrospective cohort studies will be conducted using routinely-collected health data from 5 databases.
The incidence rate of mortality and the outcomes of interest will be assessed using Population Level Disease Epidemiology analytical pipelines from the DARWIN EU Complete Catalogue of Standard Data Analyses.
Population
All individuals present in the database in the period between 01/01/2015 and 31/12/2021, with at least 1 year of prior history, being diagnosed with severe asthma and fulfilling inclusion and exclusion criteria.
Variables
Variables of interest will consist of outcomes, comorbidity, lifestyle factors, measurements and drug exposure data.
Data sources
1. Integrated Primary Care Information Project (IPCI), The Netherlands
2. Sistema d’Informació per al Desenvolupament de la Investigació en Atenció Primària (SIDIAP), Spain
3. Clinical Practice Research Datalink GOLD (CPRD GOLD), United Kingdom
4. Parc Salut Mar Barcelona (PSMAR), Hospital del Mar (IMIM) (hospital database), Spain
5. University of Tartu – Estonian Biobank, Estonia»

This project is part of Andrea Pistillo’s PhD thesis project. A part of the project has received funds from Ajuntament de Barcelona «Subvencions extraordinàries per a projectes de recerca i innovació en col·laboració amb la Fundació La Caixa, 2022». We lead the project from IDIAPJGol and other two institution are partners: ISGlobal and ICTA-BCNUEJ.

Environmental exposures may affect people’s lives. In particular heatwaves and peaks in air pollution had been associated with more mortality and hospitalizations, and a worst life quality. In Barcelona and its metropolitan area, these two types of exposures affect the neighbourhoods in a different way, both for geographic reasons (neighbourhoods nearer to the sea had a milder temperature during daytime) and sociodemographics ones (older population, energy poverty, areas with less green spaces, low education). Higher temperature and air pollution had been linked to respiratory, cardiovascular, mental, perinatal problems and infectious diseases. So far, this problems had been studied in hospital settings and a comprehensive study in primary care is needed to understand both the prevalence of the problems due to these environmental exposures and the burden of this on the primary care system. In this project we aim to analyze the relationship among temperature and air pollution on the health of the citizens of Barcelona and its metropolitan area. We will perform a quantitative study using the newest methodologies (case time series), and we will link daily environmental exposures with three types of health indicators (diagnosis, medications registered in primary care and sick leaves). The focus will be on neighborhoods and will take into account gender perspective and multidisciplinarity, justified with the synergy of the three institutions involved. An important part of the project will be dissemination of results, indeed we will publicly publish a risk map with the results in which citizens and policy makers will be able to interactively visualize the results of the project (at a neighborhood scale).

«Background
The current COVID-19 vaccines include mRNA vaccines, non-replicating viral vector vaccines and traditional inactivated whole virus vaccines. All of them have demonstrated their effectiveness against confirmed COVID-19 infection in previous and ongoing clinical trials However, vulnerable populations, such as pregnant women, children, individuals living in nursing homes, those with cancer, autoimmune diseases, immunodeficiencies or organ transplant recipients were systematically excluded from these trials, limiting the available evidence regarding the efficacy of the COVID-19 vaccines on these patients to retrospective observational studies, and small non-randomized trials with surrogate endpoints (e.g. antibody levels).

Objectives
To estimate coverage and the effectiveness of COVID-19 vaccines against COVID-19-related outcomes in vulnerable populations, overall and by sex, age, baseline comorbidities, and socioeconomic status, using electronic health records from Catalonia, Spain.
1- To provide periodic estimates of vaccine coverage in predefined subgroups of population at risk of being excluded from the general vaccine campaigns (i.e individuals with mental disorder), stratified by vaccine type/brand, vaccine dose, sex, age groups, socioeconomic status, and nationality.
2- To assess the effectiveness of COVID-19 vaccines in vulnerable population against COVID-19 related outcomes (COVID-19 infection, hospitalisation, intensive care admission, or death) in:
2.1- pregnant women and infants up to 12 months of age;
2.2- children and adolescents from the age of 5 to 19 years;
2.3- persons living with immunodeficient conditions, namely cancer, autoimmune conditions, primary immunodeficiencies, people living with HIV infection, organ transplant recipients or people taking immunosuppressive drugs;
2.4- persons living in nursing homes.

Methods
We will conduct a population-based matched cohort study using individual-level routinely-collected electronic health records (EHR) data from the Information System for Research in Primary Care (SIDIAP; www.sidiap.org) database in Catalonia mapped to the OMOP-CDM.

Study population
We will include all women with a pregnancy episode during the study period (mother-child linkage), children and adolescents, as well as those with history of cancer, immunodeficient conditions (HIV, autoimmune diseases, organ transplant recipients) and/or use of immunosuppressive drugs (including high chronic use of corticosteroids, biological and non-biological disease modifying drugs, antineoplastic drugs), persons living in nurse home residencies or persons with mental health conditions of any age, registered for at least 365 days in the SIDIAP database prior to the 27th of December 2020 (date of initiation of the vaccination in Spain) and up to December 2022 and December 2023.

Exposures
Four COVID-19 vaccines will be included: ChAdOx1-S, BNT162b2, mRNA-1273, and Ad26.COV2.S.

Outcomes
The main outcomes to evaluate effectiveness of COVID-19 vaccination will include: 1.SARS-CoV-2 infection will be defined as any confirmed infection identified by diagnostic codes and/or a positive RT-PCR or antigen test result, 2.COVID-19-related hospitalisation will be defined as a hospital admission (at least one night) where the individual had a positive RT-PCR test result or a clinical diagnosis of COVID-19 over the 21 days prior to their admission up to the end of their hospital stay,3. COVID-19-related intensive care unit (ICU) admission in those with COVID-19 related hospitalisation, 4.COVID-19-related death will be defined as death (any cause) registered after a COVID-19-related hospitalisation or 28 days after a SARS-CoV-2 infection.

Covariates
Covariates to be considered in the analyses will include demographics, socioeconomic status, nationality and diagnosis of mental health condition (only for coverage), BMI, pre-existing comorbid conditions, history of COVID-19 infection (6 months previous), period of predominant SARS-CoV-2 variants, number of GP visits per year, pregnancy variables (gestational age at vaccination, parity, breastfeeding, maternal lifestyle behaviour factors (when available).

Follow-up
For individuals from the age of 5 and above follow up will be from their index date to occurrence of an event, end of pregnancy (for pregnancy cohort), death, or loss of visibility in the database (e.g., person leaving the practice in electronic health records data). For cohorts that had received a first vaccine dose, we also censored follow-up if a second dose was observed before 21 days for BNT162b2 and before 27 days for mRNA-1273 and ChAdOx1-S.
The index date for exposed children (up to 12 months of age) will be the date of maternal vaccination. Children will be followed from the index date until occurrence of an event of interest, exit from the database, death, end of pre-defined follow-up time (12 months after birth), or end of data availability, whichever comes first.

Statistical analysis
Vaccination uptake rate will be calculated as the number of persons receiving any COVID-19 vaccines in a certain population subgroup divided by all individuals eligible for vaccination in that group.
We will conduct a new user cohort study, to compare the effectiveness of COVID-19 vaccines against COVID-19-related outcomes. We will use propensity score (PS) matching to minimise the risk of confounding. Vaccinated individuals will be matched in a 1:3 ratio (if sample size allows) with eligible non-vaccinated individuals with no prior history of COVID-19 infection in the past 3 months. Matching will be done taking into account age group, sex, calendar time, baseline comorbidities associated with increased risks of severe COVID-19 (e.g., obesity, diabetes, immunosuppression), and smoking. We will also use a large-scale, data-driven approach to identify additional potential confounders to be included in the PS.

We aim to estimate the risks of long-term COVID-19 outcomes among individuals with COVID-19 or exposed to COVID-19 during pregnancy, as well as the effect of vaccines on the development of long COVID and long-term COVID-19 outcomes.
Data will be obtained from SIDIAP, which includes primary care records for approximately 6 million people in Catalonia. To estimate long-term COVID-19 outcomes (Objective 1), we will conduct three population-based matched cohort studies using a target trial emulation design from September 2020 to December 2023. We will match COVID-19 infections to uninfected controls in a 1:5 ratio using propensity score (PS) matching. Cases/controls matched cohorts will include: Objective 1.1: people not vaccinated against COVID-19; Objective 1.2: people vaccinated against COVID-19; and Objective 1.3: newborns (cases: exposed to COVID-19 infection during pregnancy, controls: unexposed). Cohorts will be followed for 2 years. Our outcomes will include autoimmune, cardiovascular, mental, neurological, renal and early-life complications. We will estimate cause-specific Hazard Ratios (HR) for each outcome.To estimate vaccine effectiveness on the development of long COVID, we will first characterise long COVID based on persistent symptoms for >28 days (Objective 2.1). We will then estimate the effect of vaccines on the development of long COVID (Objective 2.2) using a staggered cohort study design. Vaccinated and unvaccinated cohorts will be compared using different PS techniques. We will then calculate HR for long COVID and long-term outcomes.
Our findings will inform preventive strategies and post-acute care pathways, thus contribute to prevent long COVID and improve COVID-19 survivors’ health.

Background:
Understanding the determinants of childhood health inequity has never been more urgent, given its influence on life-long health and lifestyle. It is increasingly recognized that the environment plays an important role in health in/equity and that it provides important potential for community-level intervention. However there are important gaps in the knowledge about the impact of changing environment on childhood health e.g. moving from urban to rural environments and vice versa.

Objectives:
The overarching objective is to examine how changes in the environment (air pollution, green spaces, social environment, built environment, unhealthy food environment) influence childhood health equity by applying artificial intelligence methods to analyse a unique and complex electronic record database of 1.6 million children living in urban and rural environments.

Dataset:
The project will use already existing ECOHCAT dataset, therefore there will be no need to make a new data extraction.

Methodology: The study will exploit the large resource of available primary care data of 1.6 million children (80% of the population) and the extensive individual data already available in a mother-child cohort in Catalonia. It will also collect new data on school children (10-12 years) in one Catalan city, Sabadell, where anthropometric measurements will be combined with questionnaires to obtain data on obesity and important risk factors. Geographical information system technologies will be used to estimate exposure to the different urban environment indicators at census tract level for the whole Catalonia and at home and school address level for Sabadell city. Individual-level mediators including diet, physical activity, and psychological well-being will be evaluated for their role in the association between urban environment indicators and childhood obesity. A health impact assessment will be developed based on this study and available literature. Machine learning methods will be considered to complement epimiology study designs and statistical approaches to uncover spatial and temporal movement patterns and associations with child health outcomes.

Expected results: The study will be novel in modelling multiple community-level urban environment
indicators and by evaluating potential individual-level mediators. A final impact assessment will help decision makers to develop urban environment policies aimed at reducing and preventing childhood obesity in
Catalonia.

Urbanization is one of the leading global trends of the 21st century. Childhood obesity is a key health outcome in childhood and for lifelong health. World-wide childhood obesity rates are alarmingly high. The urban environment provides important opportunities for interventions aimed at alleviating the childhood obesity epidemic. It is increasingly recognized that the urban environment may affect childhood growth and obesity and that it provides important opportunities for community-level prevention.
The aim of UrbanKids is to evaluate how changes in the urban and social environment affect weight gain and obesity in children. For this we will use a large longitudinal cohort of 1 million children and adolescents (aged 0-18 years) in Catalonia, with repeat measures of height and weight, registered in the electronic health records (EHRs) from primary care data between 2011 and 2019. The moving2health approach will focus on children who changed address and who thus provide a unique natural experiment design by changing their neighbourhood environment from one day to the next.
The UrbanKids will tackle key societal changes regarding childhood obesity by identifying which urban exposures could be modified to reduce the obesity epidemic, and by identifying how socioeconomic status may drive environmental health disparities.

El projecte inclou dos estudis:
El primer estudi, ja fet fa una setmana durant 4 dies amb diverses bases de dades internacionals online, ha estudiat el comportament d’infeccions víriques similars que hi ha hagut en el passat: s’han descrit les característiques de les persones amb complicacions d’infeccions víriques com la grip, s’han valorat els predictors de resultats adversos entre els pacients hospitalitzats amb pneumònies virals, s’han generat algoritmes per identificar els pacients amb més risc de complicacions i/o morbimortalitat, i s’ha avaluat la seguretat dels tractaments utilitzats per a un ús potencial en Covid-19.
El segon estudi vol descriure les característiques de les persones amb Covid-19 a Catalunya, així com desenvolupar models predictius de les complicacions de la Covid-19 fent servir els mètodes i resultats obtinguts en el primer estudi. Per això, es farà la integració de la informació dels pacients infectats amb Covid-19 a Catalunya, la transformació de la nova informació a un model de dades internacional, i després de contrastar les dades amb altres bases de dades d’altres països, s’elaboraran uns criteris pronòstic aplicables a les polítiques de control de pandèmia de Covid-19 al nostre país.
Els models predictius de casos greus d’infecció vírica permetran classificar els pacients amb Covid-19 per gestionar-los adequadament, avaluant la necessitat de que el malalt vagi a l’hospital o es quedi a casa, i les condicions necessàries per al seu tractament.

? Study Title
Estimating Short-Term and Long-Term Direct Economic Burden Associated with Osteoporotic Fractures
? Background and Rationale
Osteoporotic fractures (OFs) among adults are considered an important public health concern, with up to 50% of women and 22% of men over the age of 50 years experiencing at least one fragility fracture in their lifetime. Additionally, the risk of osteoporotic fractures increases with age, especially in postmenopausal women among whom decreased estrogen levels are associated with decreased bone mineral density (BMD). Osteoporotic fractures are associated with significant burden both in formal (e.g. hospitalizations, rehabilitative services, long-term care) and informal (e.g. care provided by family and friends) care settings, and increased mortality. Considering the total burden of OFs to both patient and society, it is important to better understand the short- and long-term direct healthcare impact in order to enhance osteoporosis management in the contemporary care setting. This study will focus on evaluating the direct economic burden of OFs, while a companion protocol will evaluate the indirect and humanistic burden of OFs. Moreover, the outputs from the proposed study will inform policy makers, clinicians, and patients about the multi-national burden of OFs in women, and help payers and clinicians understand the importance of treatment advances that can reduce the risk of osteoporotic fractures. This study will have the advantage of estimating the direct economic burden in six countries using the same study population composition and same time period rather than previous studies that have varying study population characteristics at varying time periods.

? Research Question and Objectives
The study aims to evaluate the direct economic burden of OFs in women aged 50 years or older in the short-term (index fracture date to 12 months) and long-term (one year to five years) following the date of the first recorded osteoporotic fracture.
Study Objectives
1. Estimate the short-term and long-term direct, post-index healthcare resource utilization (HCRU) and costs in women who experienced an incident OF and in a matched cohort of women free of any OF.
2. Estimate the short-term and long-term direct HCRU and costs pre- versus post-fracture (before and after osteoporotic fracture) in women who experienced an incident OF.
? Study Design/Type
This is a multi-national, retrospective cohort study to assess direct economic burden of OF between 2013-2018 in women aged 50 years or older in 6 countries (Australia, France, Germany, Japan, Spain, and USA). The direct all-cause HCRU and cost experience of women with an incident OF in each country will be compared with matched women without an OF (i.e. non-OF cohort) during the study period. Because of differences in healthcare systems, provision of services and costs across countries, outcomes will be reported by individual country. Women with an osteoporotic fracture will initially be matched to women in the non-OF cohort using the same birth month and year as the women with an osteoporotic fracture, then matched 1:1 on selected variables as described in Section 9.1.3. Additionally, among women with an OF, pre-fracture and post-fracture HCRU and costs will be compared. Regional or national electronic medical records (EMR), registries, or claims databases will be used in each country as described in section 10.1. For example, the PharMetrics Plus, anonymised patient-level claims database including primary and secondary care data from US commercial payers, will be used for the USA.
The study design is depicted in Figure 1 above; the following time periods/dates have been defined:
1. Index date: The index date for the OF cohort corresponds to the calendar date of the first record of an OF (i.e. incident OF) between January 1, 2013 and November 30, 2018. The index dates of the women with osteoporotic fracture will then be assigned to the corresponding matched non-OF women, in order to ensure there are no temporal differences in the comparisons between the populations.
2. Pre-index period: The pre-index period (i.e. baseline period) corresponds to the 18 months preceding the index date for both the OF and the non-OF cohort. Women must have 18 months of continuous enrollment in the database pre-index to ascertain osteoporotic fracture-free status and comorbidity and medication history.
3. Follow-up period: The follow-up period corresponds to the period extending from the earliest of index date up to December 31, 2018 (study end date), death, fracture event in non-OF woman, or lost to follow-up (drop out of the database). For woman included in the study, the follow-up period can range from a minimum of one month up to six years from the index date.
? Study Population
The study population is women aged ?50 years with or without an osteoporotic fracture. This study will be conducted in six countries: United States, Australia, France, Germany, Spain and Japan.

? Patient Eligibility
Inclusion Criteria:
OF cohort:
1. Women aged ?50 years when experiencing an incident osteoporotic fracture at the following skeletal sites: hip, vertebral (spine), forearm (radius, ulna), humerus, pelvis, proximal femur, tibia, fibula, ribs, clavicle, scapula, and ankle between January 1, 2013 and November 30, 2018.
2. Continuously enrolled in the database for at least 18 months prior to index date and at least 1 month after index date.
3. No osteoporotic fracture in the pre-index period (i.e. 18 months prior to index fracture)
Non-OF cohort:
1. Women aged ?50 years and with no record of osteoporotic fracture in the pre-index period (i.e. 18 months prior to assigned index date).
2. Continuously enrolled in the database for at least 18 months prior to index date and at least 1 month after assigned index date.
Exclusion Criteria for both cohorts:
1. Record of participation in a clinical trial pertaining to an osteoporotic treatment ?18 months before the index date.
2. Cancer (except non-melanoma skin cancer) during the study period (July 1, 2011-December 31, 2018). Patients with cancer will be excluded because of the high healthcare resource utilization and costs of cancer care as well as effect of cancer and chemotherapeutic agents on bone.
3. Paget’s disease of the bone, osteitis deformans, and osteopathies or metabolic bone diseases (e.g., osteomalacia, hyperparathyroidism, osteogenesis imperfecta) during the study period (July 1, 2011-December 31, 2018). Patients with other bone conditions will be excluded to ensure that the outcomes are associated with osteoporosis and not other bone diseases.

? Matching criteria
Women without OF will be matched to women with OF. Women in the non-OF cohort will first be matched to women with OF using their birth month and year. The index date of the women with fracture (i.e. fracture date) will then be assigned to the corresponding matched non-OF women. After identifying an age-matched group of non-OF patients for each OF patient, the closest matching non-OF woman will be identified through propensity score matching using important confounders (e.g. geographic region, race/ethnicity, total months since index date (fracture date), pre-index glucocorticoid use, pre-index hormone replacement therapy, pre-index anti-osteoporosis drug use, selected comorbidities, and pre-index hospitalizations. The OF and non-OF women will be matched 1:3. If a non-OF woman has a fracture during follow-up, then she will be censored on the date of her fracture. A 1:3 matching will be used to optimize follow-up time of women with OF because a non-OF woman may fracture and be censored before the end of follow-up of the matched woman with OF.
? Variables
Study Outcomes
? Direct all-cause healthcare resource utilization: HCRU will include any resource/services directly provided by the healthcare system in each relevant country, including hospitalisations, emergency room (ER) visits, physician visits, diagnostic and/or reimbursed procedures, and prescriptions. Physical and/or occupational therapy services also will be reported.
? Direct all-cause healthcare costs will be estimated using country-specific costs, and include total direct costs (medical + pharmacy), total medical costs (inpatient + outpatient), hospitalizations, ER, physician, and outpatient pharmacy costs.
? Study Sample Size
The half-length of the 95% confidence intervals (CI) for estimated direct costs was calculated based on mean total costs from the multi-national study of Svedbom et al 2013. The half length of the CI was estimated to be 536 for a sample size of 2,000 and 107 for a sample size of 50,000 for the first year cost of approximately $14,335. The half length of the CI was estimated to be 160 (sample size of 2,000) and 71 (sample size of 50,000) for the fifth year cost of approximately $4,421. The half length for the intervening years since fracture (i.e. 2-4 years) fell between the ranges for the first and fifth year. It is estimated that the number of incident fractures may range from about a low of 16,000 in Australia to more than 140,000 in Spain. Due to the large sample size, the CIs will be narrow, and it is believed that the estimate of direct costs will be with very small estimate error and reliable.
? Data Analysis:
All analyses will be country-specific and will not be combined across countries due to differences in healthcare systems. Demographics, baseline clinical characteristics, and pre-index direct all-cause HCRU and costs will be reported for OF and non-OF groups using number and percent within category for categorical variables, and mean (standard deviation [SD]) with 95% confidence interval or median (interquartile range [IQR]), minimum and maximum values for continuous variables as appropriate. Methods for dealing with missing data such as multiple imputation or last observation carried forward (LOCF) will not be applied, and the number with missing data reported.
To evaluate direct all-cause HCRU and costs among the propensity score matched women who experienced an OF and those who did not, descriptive measures including the mean (SD), median (IQR), and range (minimum, maximum) will be reported. Costs will be log-transformed to diminish the effect of outliers. Direct HCRU and costs will be reported by the year since index date (fracture date) (e.g. ?1 year, >1 to ?2 years, >2 to ?3 years, >3 to ?4 years, >4 to ?5 years since index date) and include all patients alive at the start of each annual period to assess short-term and long-term economic burden of OF. The main outcome is the difference between direct all-cause HCRU and costs in OF and non-OF cohorts (incremental costs). Likewise, the mean HCRU and costs among women with an OF will be compared between 1-year pre-fracture versus each year (1 to 5) post-fracture. Rate of HCRU will be calculated for each year since index date (fracture date) as the number of utilizations divided by follow-up time in the year. The rate will be reported for each individual healthcare resource type. Also, the proportion of women with at least 1 utilization for each resource type (e.g. had at least 1 hospitalization, at least 1 ER visit) will be reported
Comparisons will be made for all osteoporotic fracture types combined as well as by individual osteoporotic fracture types. Differences in HCRU and costs between OF and non-OF cohorts and pre-index versus post-index among OF women will be assessed using regression modelling. A linear regression model with log-transformed costs or gamma regression will be considered. Outcomes will be stratified by residence (i.e. community-dwelling or not) at index date, and also by occurrence of subsequent osteoporotic fracture among OF women during follow-up (yes/no).

Background: Understanding the determinants of childhood obesity has never been more urgent, given the rapid rise in obesity worldwide. Individual-level interventions, focused on changing dietary and physical activity behaviours, have had limited success. It is increasingly recognized that the urban environment contributes to the obesity epidemic and that it provides important potential for community-level intervention.

There are important gaps, though, in knowledge about multiple urban exposures and mediators, and there is no data in Catalonia on which to base impact assessments.

Main objective: ECHOCAT aims to examine whether the urban environment (air pollution, green spaces, social environment, built environment, unhealthy food environment) influences childhood obesity across Catalonia in three unique and complementary study populations.

Methodology: ECHOCAT will exploit the large resource of available primary care data of 1.6 million children (80% of the population) and the extensive individual data already available in a mother-child cohort in Catalonia. ECHOCAT will also collect new data on school children (10-12 years) in one Catalan city, Sabadell, where anthropometric measurements will be combined with questionnaires to obtain data on obesity and important risk factors. Geographical information system technologies will be used to estimate exposure to the different urban environment indicators at census tract level for the whole Catalonia and at home and school address level for Sabadell city. Individual-level mediators including diet, physical activity, and psychological well-being will be evaluated for their role in the association between urban environment indicators and childhood obesity. A health impact assessment will be developed based on this study and available literature.

Expected results: ECHOCAT will be novel in modelling multiple community-level urban environment
indicators and by evaluating potential individual-level mediators. A final impact assessment will help decision makers to develop urban environment policies aimed at reducing and preventing childhood obesity in
Catalonia.