Stress and anxiety during pregnancy and length of gestation: a federated study using data from five Canadian and European birth cohorts.

While its etiology is not fully elucidated, preterm birth represents a major public health concern as it is the leading cause of child mortality and morbidity. Stress is one of the most common perinatal conditions and may increase the risk of preterm birth. In this paper we aimed to investigate the association of maternal perceived stress and anxiety with length of gestation. We used harmonized data from five birth cohorts from Canada, France, and Norway. A total of 5297 pregnancies of singletons were included in the analysis of perceived stress and gestational duration, and 55,775 pregnancies for anxiety. Federated analyses were performed through the DataSHIELD platform using Cox regression models within intervals of gestational age. The models were fit for each cohort separately, and the cohort-specific results were combined using random effects study-level meta-analysis. Moderate and high levels of perceived stress during pregnancy were associated with a shorter length of gestation in the very/moderately preterm interval [moderate: hazard ratio (HR) 1.92 (95%CI 0.83, 4.48); high: 2.04 (95%CI 0.77, 5.37)], albeit not statistically significant. No association was found for the other intervals. Anxiety was associated with gestational duration in the very/moderately preterm interval [1.66 (95%CI 1.32, 2.08)], and in the early term interval [1.15 (95%CI 1.08, 1.23)]. Our findings suggest that perceived stress and anxiety are associated with an increased risk of earlier birth, but only in the earliest gestational ages. We also found an association in the early term period for anxiety, but the result was only driven by the largest cohort, which collected information the latest in pregnancy. This raised a potential issue of reverse causality as anxiety later in pregnancy could be due to concerns about early signs of a possible preterm birth.

Maternal stress during pregnancy and gestational duration: A cohort study from the Danish National Birth Cohort.

BACKGROUND: Preterm birth is one of the most important contributors to neonatal mortality and morbidity. Experiencing stress during pregnancy may increase the risk of adverse birth outcomes, including preterm birth. This association has been observed in previous studies, but differences in measures used limit comparability. OBJECTIVE: The objective of the study was to investigate the association between two measures of maternal stress during pregnancy, life stress and emotional distress, and gestation duration. METHODS: Women recruited in the Danish National Birth Cohort from 1996 to 2002, who provided information on their stress level during pregnancy and expecting a singleton baby, were included in the study. We assessed the associations between the level of life stress and emotional distress in quartiles, both collected at 31 weeks of pregnancy on average, and the rate of giving birth using Cox regression within intervals of the gestational period. RESULTS: A total of 80,991 pregnancies were included. Women reporting moderate or high levels of life stress vs no stress had a higher rate of giving birth earlier within all intervals of gestational age (e.g. high level: 27-33 weeks: hazard ratio (HR) 1.38, 95% confidence interval (CI) 1.04, 1.84; 34-36 weeks: 1.10, 95% CI 0.97, 1.25; 37-38 weeks: 1.21, 95% CI 1.15, 1.28). These associations between life stress and preterm birth were mainly driven by pregnancy worries. For emotional distress, a high level of distress was associated with shorter length of gestation in the preterm (27-33 weeks: 1.38, 95% CI 1.02, 1.86; 34-36 weeks: 1.05, 95% CI 0.91, 1.19) and early term (1.11, 95% CI 1.04, 1.17) intervals. CONCLUSIONS: Emotional distress and life stress were shown to be associated with gestational age at birth, with pregnancy-related stress being the single stressor driving the association. This suggests that reverse causality may, at least in parts, explain the earlier findings of stress as a risk factor for preterm birth.

A harmonized analysis of five Canadian pregnancy cohort studies: exploring the characteristics and pregnancy outcomes associated with prenatal alcohol exposure.

BACKGROUND: As a teratogen, alcohol exposure during pregnancy can impact fetal development and result in adverse birth outcomes. Despite the clinical and social importance of prenatal alcohol use, limited routinely collected information or epidemiological data exists in Canada. The aim of this study was to pool data from multiple Canadian cohort studies to identify sociodemographic characteristics before and during pregnancy that were associated with alcohol consumption during pregnancy and to assess the impact of different patterns of alcohol use on birth outcomes. METHODS: We harmonized information collected (e.g., pregnant women's alcohol intake, infants' gestational age and birth weight) from five Canadian pregnancy cohort studies to consolidate a large sample (n = 11,448). Risk factors for any alcohol use during pregnancy, including any alcohol use prior to pregnancy recognition, and binge drinking, were estimated using binomial regressions including fixed effects of pregnancy cohort membership and multiple maternal risk factors. Impacts of alcohol use during pregnancy on birth outcomes (preterm birth and low birth weight for gestational) were also estimated using binomial regression models. RESULTS: In analyses adjusting for multiple risk factors, women's alcohol use during pregnancy, both any use and any binge drinking, was associated with drinking prior to pregnancy, smoking during pregnancy, and white ethnicity. Higher income level was associated with any drinking during pregnancy. Neither drinking during pregnancy nor binge drinking during pregnancy was significantly associated with preterm delivery or low birth weight for gestational age in our sample. CONCLUSIONS: Pooling data across pregnancy cohort studies allowed us to create a large sample of Canadian women and investigate the risk factors for alcohol consumption during pregnancy. We suggest that future pregnancy and birth cohorts should always include questions related to the frequency and amount of alcohol consumed before and during pregnancy that are prospectively harmonized to support data reusability and collaborative research.

Latent variable models for harmonization of test scores: A case study on memory.

Combining data from different studies has a long tradition within the scientific community. It requires that the same information is collected from each study to be able to pool individual data. When studies have implemented different methods or used different instruments (e.g., questionnaires) for measuring the same characteristics or constructs, the observed variables need to be harmonized in some way to obtain equivalent content information across studies. This paper formulates the main concepts for harmonizing test scores from different observational studies in terms of latent variable models. The concepts are formulated in terms of calibration, invariance, and exchangeability. Although similar ideas are present in measurement reliability and test equating, harmonization is different from measurement invariance and generalizes test equating. In addition, if a test score needs to be transformed to another test score, harmonization of variables is only possible under specific conditions. Observed test scores that connect all of the different studies, are necessary to be able to test the underlying assumptions of harmonization. The concepts of harmonization are illustrated on multiple memory test scores from three different Canadian studies.

Air pollution, lung function and COPD: results from the population-based UK Biobank study.

Ambient air pollution increases the risk of respiratory mortality, but evidence for impacts on lung function and chronic obstructive pulmonary disease (COPD) is less well established. The aim was to evaluate whether ambient air pollution is associated with lung function and COPD, and explore potential vulnerability factors.We used UK Biobank data on 303 887 individuals aged 40-69 years, with complete covariate data and valid lung function measures. Cross-sectional analyses examined associations of land use regression-based estimates of particulate matter (particles with a 50% cut-off aerodynamic diameter of 2.5 and 10 µm: PM2.5 and PM10, respectively; and coarse particles with diameter between 2.5 µm and 10 µm: PMcoarse) and nitrogen dioxide (NO2) concentrations with forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), the FEV1/FVC ratio and COPD (FEV1/FVC

A framework for measurement and harmonization of pediatric multiple sclerosis etiologic research studies: The Pediatric MS Tool-Kit.

BACKGROUND: While studying the etiology of multiple sclerosis (MS) in children has several methodological advantages over studying etiology in adults, studies are limited by small sample sizes. OBJECTIVE: Using a rigorous methodological process, we developed the Pediatric MS Tool-Kit, a measurement framework that includes a minimal set of core variables to assess etiological risk factors. METHODS: We solicited input from the International Pediatric MS Study Group to select three risk factors: environmental tobacco smoke (ETS) exposure, sun exposure, and vitamin D intake. To develop the Tool-Kit, we used a Delphi study involving a working group of epidemiologists, neurologists, and content experts from North America and Europe. RESULTS: The Tool-Kit includes six core variables to measure ETS, six to measure sun exposure, and six to measure vitamin D intake. The Tool-Kit can be accessed online ( www.maelstrom-research.org/mica/network/tool-kit ). CONCLUSION: The goals of the Tool-Kit are to enhance exposure measurement in newly designed pediatric MS studies and comparability of results across studies, and in the longer term to facilitate harmonization of studies, a methodological approach that can be used to circumvent issues of small sample sizes. We believe the Tool-Kit will prove to be a valuable resource to guide pediatric MS researchers in developing study-specific questionnaire.

The Canadian Partnership for Tomorrow Project: a pan-Canadian platform for research on chronic disease prevention.

BACKGROUND: Understanding the complex interaction of risk factors that increase the likelihood of developing common diseases is challenging. The Canadian Partnership for Tomorrow Project (CPTP) is a prospective cohort study created as a population-health research platform for assessing the effect of genetics, behaviour, family health history and environment (among other factors) on chronic diseases. METHODS: Volunteer participants were recruited from the general Canadian population for a confederation of 5 regional cohorts. Participants were enrolled in the study and core information obtained using 2 approaches: attendance at a study assessment centre for all study measures (questionnaire, venous blood sample and physical measurements) or completion of the core questionnaire (online or paper), with later collection of other study measures where possible. Physical measurements included height, weight, percentage body fat and blood pressure. Participants consented to passive follow-up through linkage with administrative health databases and active follow-up through recontact. All participant data across the 5 regional cohorts were harmonized. RESULTS: A total of 307 017 participants aged 30-74 from 8 provinces were recruited. More than half provided a venous blood sample and/or other biological sample, and 33% completed physical measurements. A total of 709 harmonized variables were created; almost 25% are available for all participants and 60% for at least 220 000 participants. INTERPRETATION: Primary recruitment for the CPTP is complete, and data and biosamples are available to Canadian and international researchers through a data-access process. The CPTP will support research into how modifiable risk factors, genetics and the environment interact to affect the development of cancer and other chronic diseases, ultimately contributing evidence to reduce the global burden of chronic disease.

MINDMAP: establishing an integrated database infrastructure for research in ageing, mental well-being, and the urban environment.

BACKGROUND: Urbanization and ageing have important implications for public mental health and well-being. Cities pose major challenges for older citizens, but also offer opportunities to develop, test, and implement policies, services, infrastructure, and interventions that promote mental well-being. The MINDMAP project aims to identify the opportunities and challenges posed by urban environmental characteristics for the promotion and management of mental well-being and cognitive function of older individuals. METHODS: MINDMAP aims to achieve its research objectives by bringing together longitudinal studies from 11 countries covering over 35 cities linked to databases of area-level environmental exposures and social and urban policy indicators. The infrastructure supporting integration of this data will allow multiple MINDMAP investigators to safely and remotely co-analyse individual-level and area-level data. Individual-level data is derived from baseline and follow-up measurements of ten participating cohort studies and provides information on mental well-being outcomes, sociodemographic variables, health behaviour characteristics, social factors, measures of frailty, physical function indicators, and chronic conditions, as well as blood derived clinical biochemistry-based biomarkers and genetic biomarkers. Area-level information on physical environment characteristics (e.g. green spaces, transportation), socioeconomic and sociodemographic characteristics (e.g. neighbourhood income, residential segregation, residential density), and social environment characteristics (e.g. social cohesion, criminality) and national and urban social policies is derived from publically available sources such as geoportals and administrative databases. The linkage, harmonization, and analysis of data from different sources are being carried out using piloted tools to optimize the validity of the research results and transparency of the methodology. DISCUSSION: MINDMAP is a novel research collaboration that is combining population-based cohort data with publicly available datasets not typically used for ageing and mental well-being research. Integration of various data sources and observational units into a single platform will help to explain the differences in ageing-related mental and cognitive disorders both within as well as between cities in Europe, the US, Canada, and Russia and to assess the causal pathways and interactions between the urban environment and the individual determinants of mental well-being and cognitive ageing in older adults.

Long-term exposure to road traffic noise, ambient air pollution, and cardiovascular risk factors in the HUNT and lifelines cohorts.

AIMS: Blood biochemistry may provide information on associations between road traffic noise, air pollution, and cardiovascular disease risk. We evaluated this in two large European cohorts (HUNT3, Lifelines). METHODS AND RESULTS: Road traffic noise exposure was modelled for 2009 using a simplified version of the Common Noise Assessment Methods in Europe (CNOSSOS-EU). Annual ambient air pollution (PM10, NO2) at residence was estimated for 2007 using a Land Use Regression model. The statistical platform DataSHIELD was used to pool data from 144 082 participants aged ≥20 years to enable individual-level analysis. Generalized linear models were fitted to assess cross-sectional associations between pollutants and high-sensitivity C-reactive protein (hsCRP), blood lipids and for (Lifelines only) fasting blood glucose, for samples taken during recruitment in 2006-2013. Pooling both cohorts, an inter-quartile range (IQR) higher day-time noise (5.1 dB(A)) was associated with 1.1% [95% confidence interval (95% CI: 0.02-2.2%)] higher hsCRP, 0.7% (95% CI: 0.3-1.1%) higher triglycerides, and 0.5% (95% CI: 0.3-0.7%) higher high-density lipoprotein (HDL); only the association with HDL was robust to adjustment for air pollution. An IQR higher PM10 (2.0 µg/m3) or NO2 (7.4 µg/m3) was associated with higher triglycerides (1.9%, 95% CI: 1.5-2.4% and 2.2%, 95% CI: 1.6-2.7%), independent of adjustment for noise. Additionally for NO2, a significant association with hsCRP (1.9%, 95% CI: 0.5-3.3%) was seen. In Lifelines, an IQR higher noise (4.2 dB(A)) and PM10 (2.4 µg/m3) was associated with 0.2% (95% CI: 0.1-0.3%) and 0.6% (95% CI: 0.4-0.7%) higher fasting glucose respectively, with both remaining robust to adjustment for air/noise pollution. CONCLUSION: Long-term exposures to road traffic noise and ambient air pollution were associated with blood biochemistry, providing a possible link between road traffic noise/air pollution and cardio-metabolic disease risk.

Ambient air pollution, traffic noise and adult asthma prevalence: a BioSHaRE approach.

We investigated the effects of both ambient air pollution and traffic noise on adult asthma prevalence, using harmonised data from three European cohort studies established in 2006-2013 (HUNT3, Lifelines and UK Biobank).Residential exposures to ambient air pollution (particulate matter with aerodynamic diameter ≤10 µm (PM10) and nitrogen dioxide (NO2)) were estimated by a pan-European Land Use Regression model for 2007. Traffic noise for 2009 was modelled at home addresses by adapting a standardised noise assessment framework (CNOSSOS-EU). A cross-sectional analysis of 646 731 participants aged ≥20 years was undertaken using DataSHIELD to pool data for individual-level analysis via a "compute to the data" approach. Multivariate logistic regression models were fitted to assess the effects of each exposure on lifetime and current asthma prevalence.PM10 or NO2 higher by 10 µg·m-3 was associated with 12.8% (95% CI 9.5-16.3%) and 1.9% (95% CI 1.1-2.8%) higher lifetime asthma prevalence, respectively, independent of confounders. Effects were larger in those aged ≥50 years, ever-smokers and less educated. Noise exposure was not significantly associated with asthma prevalence.This study suggests that long-term ambient PM10 exposure is associated with asthma prevalence in western European adults. Traffic noise is not associated with asthma prevalence, but its potential to impact on asthma exacerbations needs further investigation.

MOLGENIS/connect: a system for semi-automatic integration of heterogeneous phenotype data with applications in biobanks.

MOTIVATION: While the size and number of biobanks, patient registries and other data collections are increasing, biomedical researchers still often need to pool data for statistical power, a task that requires time-intensive retrospective integration. RESULTS: To address this challenge, we developed MOLGENIS/connect, a semi-automatic system to find, match and pool data from different sources. The system shortlists relevant source attributes from thousands of candidates using ontology-based query expansion to overcome variations in terminology. Then it generates algorithms that transform source attributes to a common target DataSchema. These include unit conversion, categorical value matching and complex conversion patterns (e.g. calculation of BMI). In comparison to human-experts, MOLGENIS/connect was able to auto-generate 27% of the algorithms perfectly, with an additional 46% needing only minor editing, representing a reduction in the human effort and expertise needed to pool data. AVAILABILITY AND IMPLEMENTATION: Source code, binaries and documentation are available as open-source under LGPLv3 from http://github.com/molgenis/molgenis and www.molgenis.org/connect CONTACT: : m.a.swertz@rug.nl SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Comparison of Standardization Methods for the Harmonization of Phenotype Data: An Application to Cognitive Measures.

Standardization procedures are commonly used to combine phenotype data that were measured using different instruments, but there is little information on how the choice of standardization method influences pooled estimates and heterogeneity. Heterogeneity is of key importance in meta-analyses of observational studies because it affects the statistical models used and the decision of whether or not it is appropriate to calculate a pooled estimate of effect. Using 2-stage individual participant data analyses, we compared 2 common methods of standardization, T-scores and category-centered scores, to create combinable memory scores using cross-sectional data from 3 Canadian population-based studies (the Canadian Study on Health and Aging (1991-1992), the Canadian Community Health Survey on Healthy Aging (2008-2009), and the Quebec Longitudinal Study on Nutrition and Aging (2004-2005)). A simulation was then conducted to assess the influence of varying the following items across population-based studies: 1) effect size, 2) distribution of confounders, and 3) the relationship between confounders and the outcome. We found that pooled estimates based on the unadjusted category-centered scores tended to be larger than those based on the T-scores, although the differences were negligible when adjusted scores were used, and that most individual participant data meta-analyses identified significant heterogeneity. The results of the simulation suggested that in terms of heterogeneity, the method of standardization played a smaller role than did different effect sizes across populations and differential confounding of the outcome measure across studies. Although there was general consistency between the 2 types of standardization methods, the simulations identified a number of sources of heterogeneity, some of which are not the usual sources considered by researchers.

Road traffic noise, blood pressure and heart rate: Pooled analyses of harmonized data from 88,336 participants.

INTRODUCTION: Exposure to road traffic noise may increase blood pressure and heart rate. It is unclear to what extent exposure to air pollution may influence this relationship. We investigated associations between noise, blood pressure and heart rate, with harmonized data from three European cohorts, while taking into account exposure to air pollution. METHODS: Road traffic noise exposure was assessed using a European noise model based on the Common Noise Assessment Methods in Europe framework (CNOSSOS-EU). Exposure to air pollution was estimated using a European-wide land use regression model. Blood pressure and heart rate were obtained by trained clinical professionals. Pooled cross-sectional analyses of harmonized data were conducted at the individual level and with random-effects meta-analyses. RESULTS: We analyzed data from 88,336 participants, across the three participating cohorts (mean age 47.0 (±13.9) years). Each 10dB(A) increase in noise was associated with a 0.93 (95% CI 0.76;1.11) bpm increase in heart rate, but with a decrease in blood pressure of 0.01 (95% CI -0.24;0.23) mmHg for systolic and 0.38 (95% CI -0.53; -0.24) mmHg for diastolic blood pressure. Adjustments for PM10 or NO2 attenuated the associations, but remained significant for DBP and HR. Results for BP differed by cohort, with negative associations with noise in LifeLines, no significant associations in EPIC-Oxford, and positive associations with noise >60dB(A) in HUNT3. CONCLUSIONS: Our study suggests that road traffic noise may be related to increased heart rate. No consistent evidence for a relation between noise and blood pressure was found.

The prevalence of metabolic syndrome and metabolically healthy obesity in Europe: a collaborative analysis of ten large cohort studies.

BACKGROUND: Not all obese subjects have an adverse metabolic profile predisposing them to developing type 2 diabetes or cardiovascular disease. The BioSHaRE-EU Healthy Obese Project aims to gain insights into the consequences of (healthy) obesity using data on risk factors and phenotypes across several large-scale cohort studies. Aim of this study was to describe the prevalence of obesity, metabolic syndrome (MetS) and metabolically healthy obesity (MHO) in ten participating studies. METHODS: Ten different cohorts in seven countries were combined, using data transformed into a harmonized format. All participants were of European origin, with age 18-80 years. They had participated in a clinical examination for anthropometric and blood pressure measurements. Blood samples had been drawn for analysis of lipids and glucose. Presence of MetS was assessed in those with obesity (BMI ≥ 30 kg/m2) based on the 2001 NCEP ATP III criteria, as well as an adapted set of less strict criteria. MHO was defined as obesity, having none of the MetS components, and no previous diagnosis of cardiovascular disease. RESULTS: Data for 163,517 individuals were available; 17% were obese (11,465 men and 16,612 women). The prevalence of obesity varied from 11.6% in the Italian CHRIS cohort to 26.3% in the German KORA cohort. The age-standardized percentage of obese subjects with MetS ranged in women from 24% in CHRIS to 65% in the Finnish Health2000 cohort, and in men from 43% in CHRIS to 78% in the Finnish DILGOM cohort, with elevated blood pressure the most frequently occurring factor contributing to the prevalence of the metabolic syndrome. The age-standardized prevalence of MHO varied in women from 7% in Health2000 to 28% in NCDS, and in men from 2% in DILGOM to 19% in CHRIS. MHO was more prevalent in women than in men, and decreased with age in both sexes. CONCLUSIONS: Through a rigorous harmonization process, the BioSHaRE-EU consortium was able to compare key characteristics defining the metabolically healthy obese phenotype across ten cohort studies. There is considerable variability in the prevalence of healthy obesity across the different European populations studied, even when unified criteria were used to classify this phenotype.

International network of twin registries (INTR): building a platform for international collaboration.

The International Network of Twin Registries (INTR) aims to foster scientific collaboration and promote twin research on a global scale by working to expand the resources of twin registries around the world and make them available to researchers who adhere to established guidelines for international collaboration. Our vision is to create an unprecedented scientific network of twin registries that will advance knowledge in ways that are impossible for individual registries, and includes the harmonization of data. INTR will also promote a broad range of activities, including the development of a website, formulation of data harmonization protocols, creation of a library of software tools for twin studies, design of a search engine to identify research partners, establishment of searchable inventories of data and biospecimens, development of templates for informed consent and data sharing, organization of symposia at International Society of Twin Studies conferences, support for scholar exchanges, and writing grant proposals.

Data harmonization and federated analysis of population-based studies: the BioSHaRE project.

BACKGROUND: Individual-level data pooling of large population-based studies across research centres in international research projects faces many hurdles. The BioSHaRE (Biobank Standardisation and Harmonisation for Research Excellence in the European Union) project aims to address these issues by building a collaborative group of investigators and developing tools for data harmonization, database integration and federated data analyses. METHODS: Eight population-based studies in six European countries were recruited to participate in the BioSHaRE project. Through workshops, teleconferences and electronic communications, participating investigators identified a set of 96 variables targeted for harmonization to answer research questions of interest. Using each study's questionnaires, standard operating procedures, and data dictionaries, harmonization potential was assessed. Whenever harmonization was deemed possible, processing algorithms were developed and implemented in an open-source software infrastructure to transform study-specific data into the target (i.e. harmonized) format. Harmonized datasets located on server in each research centres across Europe were interconnected through a federated database system to perform statistical analysis. RESULTS: Retrospective harmonization led to the generation of common format variables for 73% of matches considered (96 targeted variables across 8 studies). Authenticated investigators can now perform complex statistical analyses of harmonized datasets stored on distributed servers without actually sharing individual-level data using the DataSHIELD method. CONCLUSION: New Internet-based networking technologies and database management systems are providing the means to support collaborative, multi-center research in an efficient and secure manner. The results from this pilot project show that, given a strong collaborative relationship between participating studies, it is possible to seamlessly co-analyse internationally harmonized research databases while allowing each study to retain full control over individual-level data. We encourage additional collaborative research networks in epidemiology, public health, and the social sciences to make use of the open source tools presented herein.

Enteral supplementation with high-dose docosahexaenoic acid on the risk of bronchopulmonary dysplasia in very preterm infants: a collaborative study protocol for an individual participant data meta-analysis.

INTRODUCTION: Severe bronchopulmonary dysplasia (BPD) is a well-known factor consistently associated with impaired cognitive outcomes. Regarding reported benefits on long-term neurodevelopmental outcomes, the potential adverse effects of high-dose docosahexaenoic acid (DHA) supplementation on this short-term neonatal morbidity need further investigations in infants born very preterm. This study will determine whether high-dose DHA enteral supplementation during the neonatal period is associated with the risk of severe BPD at 36 weeks' postmenstrual age (PMA) compared with control, in contemporary cohorts of preterm infants born at less than 29 weeks of gestation. METHODS AND ANALYSIS: As part of an Australian-Canadian collaboration, we will conduct an individual participant data (IPD) meta-analysis of randomised controlled trials targeting infants born at less than 29 weeks of gestation and evaluating the effect of high-dose DHA enteral supplementation in the neonatal period compared with a control. Primary outcome will be severe grades of BPD (yes/no) at 36 weeks' PMA harmonised according to a recent definition that predicts early childhood morbidities. Other outcomes will be survival without severe BPD, death, BPD severity grades, serious brain injury, severe retinopathy of prematurity, patent ductus arteriosus and necrotising enterocolitis requiring surgery, sepsis, combined neonatal morbidities and growth. Severe BPD will be compared between groups using a multivariate generalised estimating equations log-binomial regression model. Subgroup analyses are planned for gestational age, sex, small-for-gestational age, presence of maternal chorioamnionitis and mode of delivery. ETHICS AND DISSEMINATION: The conduct of each trial was approved by institutional research ethics boards and written informed consent was obtained from participating parents. A collaboration and data sharing agreement will be signed between participating authors and institutions. This IPD meta-analysis will document the role of DHA in nutritional management of BPD. Findings will be disseminated through conferences, media interviews and publications to peer-reviewed journals. PROSPERO REGISTRATION NUMBER: CRD42023431063. TRIAL REGISTRATION NUMBER: NCT05915806.

Life course of retrospective harmonization initiatives: key elements to consider.

Optimizing research on the developmental origins of health and disease (DOHaD) involves implementing initiatives maximizing the use of the available cohort study data; achieving sufficient statistical power to support subgroup analysis; and using participant data presenting adequate follow-up and exposure heterogeneity. It also involves being able to undertake comparison, cross-validation, or replication across data sets. To answer these requirements, cohort study data need to be findable, accessible, interoperable, and reusable (FAIR), and more particularly, it often needs to be harmonized. Harmonization is required to achieve or improve comparability of the putatively equivalent measures collected by different studies on different individuals. Although the characteristics of the research initiatives generating and using harmonized data vary extensively, all are confronted by similar issues. Having to collate, understand, process, host, and co-analyze data from individual cohort studies is particularly challenging. The scientific success and timely management of projects can be facilitated by an ensemble of factors. The current document provides an overview of the 'life course' of research projects requiring harmonization of existing data and highlights key elements to be considered from the inception to the end of the project.

Self-reported Severe and Nonsevere Hypoglycemia in Type 1 Diabetes: Population Surveillance Through the BETTER Patient Engagement Registry: Development and Baseline Characteristics.

OBJECTIVES: The BETTER (BEhaviors, Therapies, TEchnologies and hypoglycemic Risk in Type 1 diabetes) registry is a type 1 diabetes population surveillance system codeveloped with patient partners to address the burden of hypoglycemia and assess the impact of new therapies and technologies. The aim of this report was to describe the baseline characteristics of the BETTER registry cohort. METHODS: A cross-sectional baseline evaluation was performed of a Canadian clinical cohort established after distribution of an online questionnaire. Participants were recruited through clinics, public foundations, advertising and social media. As of February 2021, 1,430 persons ≥14 years of age and living with type 1 diabetes or latent-autoimmune diabetes (LADA) were enrolled. The trial was registered on ClinicalTrials.gov (NCT03720197). RESULTS: Participants were (mean ± standard deviation) 41.2±15.7 years old with a diabetes duration of 22.0±14.7 years, 62.0% female, 92.1% Caucasian and 7.8% self-reporting as LADA, with 40.9% using a continuous subcutaneous insulin infusion (CSII) system and 78.0% using a continuous glucose monitoring (CGM) system. The most recent glycated hemoglobin ≤7% was reported by 29.7% of participants. At least 1 episode of hypoglycemia <3.0 mmol/L (level 2-H) in the last month was reported by 78.4% of participants, with a median (interquartile range) of 5 (3, 10) episodes. The occurrence of severe hypoglycemia (level 3-H) in the last 12 months was reported by 13.3% of participants. Among these, the median number of episodes was 2 (1, 3). CONCLUSIONS: We have established the first surveillance registry for people living with type 1 diabetes in Canada relying on patient-reported outcomes and experiences. Hypoglycemia is a highly prevalent burden despite a relatively wide adoption of CSII and CGM use.