Suchergebnisse

This paper draws attention to the narrative potential of longitudinal studies such as the British Birth Cohort Studies (BBCS), and explores the possibility of creating narrative case histories and conducting narrative analysis based on information available from the studies. The BBCS have historically adopted a quantitative research design and used structured interviews and questionnaires to collect data from large samples of individuals born in specific years. However, the longitudinal nature of these studies means that they follow the same sample of individuals from birth through childhood into adult life, and this leads to the creation of data that can be understood as a quantitative auto/biography.

IntroductionNovel data platforms are needed to expedite the linkage of geospatial and natural environment data with longitudinal population study(ies) (LPS) data. However, the intrinsic relationship between geospatial data and participant identities raises confidentiality concerns amongst participants which need to be accommodated within platform designs to ensure acceptable data use.
Objectives and ApproachWe aimed to establish generalisable mechanisms for linking spatial records into a cohort study LPS databank. Using 'Data Safe Haven' (Burton et al. 2015) approaches we developed a pipeline of technical processes (e.g. geocoding participants' residential and school address records, developing an 'engine' for linking exposure data to LPS data), which we tested for participant acceptability (through a focus group testing acceptable use of personal identifiers in this context) and tuned to meet regulatory requirements (e.g. privacy impact assessments, information security accreditation). We demonstrated our approach through an exemplar investigation assessing in utero NO2 exposure with later childhood respiratory outcomes.
ResultsParticipants' expressed clear expectations that the research use of location data should be restricted to trusted study staff (as distinct from the wider research community), although this expectation is context specific and does not represent a carte blanche for using granular information (e.g. GPS tracing data). This necessitated a 'split stage' protocol, where personal identifiers are handled separately from data/analysis. Daily NO2 exposure was modeled using road, other local and regional records; with validation exposure data collected from city-based sensors. Participants' location information was geocoded and linked to NO2 using the ALGAE (ALorithms for Generating address histories and Exposures) privacy-preserving geocoding engine. We will summarise participant views, our exemplar findings, and describe the linkage engine we have developed and its availability via an open-source repository.
Conclusion/ImplicationsParticipants' expect that studies control for confidentiality risks introduced by research using spatial identifiers. It is not realistic to expect that all LPS have the capacity to undertake specialist spatial linkages. Our generalisable approaches and open-source software could provide the basis for geospatial and natural environment epidemiology platforms in LPS.

IntroductionPooling data from cohort studies can be used to increase sample size. However, individual datasets may contain variables that measure the same construct differently, posing challenges in the usefulness of combined datasets. Variable harmonization (an effort that provides comparable view of data from different studies) may address this issue.
Objectives and ApproachThis study harmonized existing datasets from two prospective pregnancy cohort studies in Alberta Canada (All Our Families (n=3,351) and Alberta Pregnancy Outcome and Nutrition (n=2,187)). Given the comparability of the characteristics of the two cohorts and similarities of the core data elements of interest, data harmonization was justifiable. Data harmonization was performed considering multiple factors, such as complete or partial variable matching regarding question asked/responded, the response coded (value level, value definition, data type), the frequency of measurement, the pregnancy time-period of measurement, and missing values. Multiple imputation was used to address missing data resulting from the data harmonization process.
ResultsSeveral variables such as ethnicity, income, parity, gestational age, anxiety, and depression were harmonized using different procedures. If the question asked/answered and the response recorded was the same in both datasets, no variable manipulation was done. If the response recorded was different, the response was re-categorized/re-organized to optimize comparability of data from both datasets. Missing values were created for each resulting unmatched variables and were replaced using multiple imputation if the same construct was measured in both datasets but using different ways/scales. A scale that was used in both datasets was identified as a reference standard. If the variables were measured in multiple times and/or different time-periods, variables were synchronized using pregnancy trimesters data. Finally, harmonized datasets were then combined/pooled into a single dataset (n=5,588).
Conclusion/ImplicationsVariable harmonization is an important aspect of conducting research using multiple datasets. It provides an opportunity to increase study power through maximizing sample size, permitting more sophisticated statistical analyses, and to answer novel research questions that could not be addressed using a single study.

Highly prevalent and typically beginning in childhood, asthma is a burdensome disease, yet the risk factors for this condition are not clarified. To enhance understanding, this study assessed the cohort-specific and pooled risk of maternal education on asthma in children aged 3-8 across 10 European countries. Data on 47,099 children were obtained from prospective birth cohort studies across 10 European countries. We calculated cohort-specific prevalence difference in asthma outcomes using the relative index of inequality (RII) and slope index of inequality (SII). Results from all countries were pooled using random-effects meta-analysis procedures to obtain mean RII and SII scores at the European level. Final models were adjusted for child sex, smoking during pregnancy, parity, mothers age and ethnicity. The higher the score the greater the magnitude of relative (RII, reference 1) and absolute (SII, reference 0) inequity. The pooled RII estimate for asthma risk across all cohorts was 1.46 (95% CI 1.26, 1.71) and the pooled SII estimate was 1.90 (95% CI 0.26, 3.54). Of the countries examined, France, the United Kingdom and the Netherlands had the highest prevalences of childhood asthma and the largest inequity in asthma risk. Smaller inverse associations were noted for all other countries except Italy, which presented contradictory scores, but with small effect sizes. Tests for heterogeneity yielded significant results for SII scores. Overall, offspring of mothers with a low level of education had an increased relative and absolute risk of asthma compared to offspring of high-educated mothers. ; Funding Agencies|European Unions Seventh Framework Programme as part of The Determinants to Reduce Health Inequity Via Early Childhood, Realising Fair Employment [278350]; Social Protection (DRIVERS) research programme; Ministry of Education of the Czech Republic: CETOCOEN plus project [CZ02101/00/00/15_003/0000469]; RECETOX Research Infrastructure [LM2015051]; Academy of Finland [FI-NFBC8586]; Biocenter, University of Oulu, Finland; European Commission EUROBLCS, Framework 5 Award [QLG1-CT-2000-01643]; EU [FP7 EurHEALTHAgeing-277849]; Medical Research Council, UK (PrevMetSyn/SALVE); MRC Centenary Early Career Award; Netherlands Organization for Health Research and Development (ZonMw) Grant (TOP) [40-00812-98-11010]; Juvenile Diabetes Research Foundation; Swedish Child Diabetes Foundation (Barndiabetesfonden); Research Council of South-east Sweden (FORSS); Swedish Research Council [K2005-72X-11242-11A]; ALF/County Council of Ostergotland; European Union, Spain (Instituto de Salud Carlos III) [FP7-ENV-2011-282957, HEALTH. 2010.2.4.5-1]; European Union, Spain (Ministry of Health) [FP7-ENV-2011-282957, HEALTH. 2010.2.4.5-1]; Conselleria de Sanitat of the Generalitat Valenciana; Department of Health of the Basque Government; Provincial Government of Gipuzkoa; Generalitat de Catalunya-CIRIT; US NIH Fogarty International Center; National Academy of Medical Sciences of Ukraine; Medical Research Council UK doctoral training studentship

(1) Background: accident rates prove the uneven development of the member countries in the area of work safety. Remedial actions and structural programmes should take into account, e.g., the level of work safety in all European Union (EU) countries. Aim: the identification of differences in the level of work safety in the production sector of EU countries, especially the so-called "old" and "new" EU countries. (2) Methods: for each country UE (in 2008–2018), the relative risk (RR) of an accident at work was determined and a comparative analysis was conducted. (3) Results: an increase in the RR of an accident at work was observed along with an increase in the GDP of a given country. It was found that the level of occupational safety in Sweden and the United Kingdom is higher than in other countries, and lower in Spain and Portugal. In the three largest economies of the EU, Germany, France, and Italy, the RR of the accident in the industrial sector in relation to the national data is one of the lowest in the entire EU, not exceeding 1.3. In The Netherlands, an increase of 1.7 RR of fatal accidents in the industrial sector was observed between 2008 and 2018. (4) Conclusions: RR in the manufacturing sector of the so-called "old" EU is higher than in the so-called "new" EU, which may result from the implementation of Industry 4.0 assumptions in the "old" EU. The presented results and conclusions may be useful in shaping the EU policy in the field of sustainable development of production sectors of individual member countries.

Acknowledgments We thank Dorit Naot and Susannah O'Sullivan for providing the animal raw data used in the simulations. Funding This research received no specific funding. MB is a recipient of an HRC Clinical Practitioners Fellowship. The Health Services Research Unit is funded by the Chief Scientist Office of the Scottish Government Health and Social Care Directorates. The authors are independent of the HRC. The HRC had no role in design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. ; Peer reviewed ; Postprint

Using data from three British birth cohort studies, we examine patterns of social mobility over three generations of family members. For both men and women, absolute mobility rates (i.e., total, upward, downward, and outflow mobility rates) in the partial parents-children mobility tables vary substantially by grandparents' social class. In terms of relative mobility patterns, we find a statistically significant association between grandparents' and grandchildren's class positions, after parents' social class is taken into account. The net grandparents-grandchildren association can be summarized by a single uniform association parameter. Net of parents' social class, the odds of grandchildren entering the professional-managerial class rather than the unskilled manual class are at least two and a half times better if the grandparents were themselves in professional-managerial rather than unskilled manual-class positions. This grandparents effect in social mobility persists even when parents' education, income, and wealth are taken into account.

Highly prevalent and typically beginning in childhood, asthma is a burdensome disease, yet the risk factors for this condition are not clarified. To enhance understanding, this study assessed the cohort-specific and pooled risk of maternal education on asthma in children aged 3–8 across 10 European countries. Data on 47,099 children were obtained from prospective birth cohort studies across 10 European countries. We calculated cohort-specific prevalence difference in asthma outcomes using the relative index of inequality (RII) and slope index of inequality (SII). Results from all countries were pooled using random-effects meta-analysis procedures to obtain mean RII and SII scores at the European level. Final models were adjusted for child sex, smoking during pregnancy, parity, mother's age and ethnicity. The higher the score the greater the magnitude of relative (RII, reference 1) and absolute (SII, reference 0) inequity. The pooled RII estimate for asthma risk across all cohorts was 1.46 (95% CI 1.26, 1.71) and the pooled SII estimate was 1.90 (95% CI 0.26, 3.54). Of the countries examined, France, the United Kingdom and the Netherlands had the highest prevalence's of childhood asthma and the largest inequity in asthma risk. Smaller inverse associations were noted for all other countries except Italy, which presented contradictory scores, but with small effect sizes. Tests for heterogeneity yielded significant results for SII scores. Overall, offspring of mothers with a low level of education had an increased relative and absolute risk of asthma compared to offspring of high-educated mothers. ; All phases of this study were supported by a European Union's Seventh Framework Programme grant, 278350, as part of The Determinants to Reduce Health Inequity Via Early Childhood, Realising Fair Employment, and Social Protection (DRIVERS) research programme. The Czech ELSPAC Study (CZ-ELSPAC) was supported by the Ministry of Education of the Czech Republic: CETOCOEN plus project (CZ02101/00/00/15_003/0000469) and RECETOX Research Infrastructure (LM2015051). The Northern Finland Birth Cohort (FI-NFBC8586) received financial support from the Academy of Finland; Biocenter, University of Oulu, Finland; the European Commission EUROBLCS, Framework 5 Award QLG1-CT-2000-01643); EU FP7 EurHEALTHAgeing-277849; the Medical Research Council, UK (PrevMetSyn/SALVE); and the MRC Centenary Early Career Award. The Amsterdam Born Children and their Development Study (NLABCD) received funding from the Netherlands Organization for Health Research and Development (ZonMw) Grant (TOP, 40-00812-98-11010). The All Babies in Southeast Sweden Study (SE-ABIS) has received financial support from the Juvenile Diabetes Research Foundation, Swedish Child Diabetes Foundation (Barndiabetesfonden), The Research Council of South-east Sweden (FORSS), Swedish Research Council K2005-72X-11242-11A, and ALF/County Council of O ̈stergo ̈tland. The INMA study was funded in part by grants from the European Union (FP7-ENV-2011-282957 and HEALTH.2010.2.4.5-1), Spain (Instituto de Salud Carlos III and The Ministry of Health), the Conselleria de Sanitat of the Generalitat Valenciana, department of Health of the Basque Government, the Provincial Government of Gipuzkoa, and the Generalitat de Catalunya-CIRIT. Family and Children of Ukraine (UA-FCOU) study was supported by US NIH Fogarty International Center and National Academy of Medical Sciences of Ukraine. KML is funded by a Medical Research Council UK doctoral training studentship.

Abstract

Background
The results of studies on the relationship between secondhand smoking and neurological disease remain controversial. We conducted a meta-analysis to explore the association between secondhand smoking and risk of neurological disease.


Methods
Literature search was performed in PubMed, Embase and Web of Science through December 2019. We included cohort studies which examined the association between secondhand smoking and risk of neurological disease. According to the type of neurological disease, summary relative risks (RRs) with 95% confidence intervals (CIs) of stroke, cognitive impairment and Parkinson disease (PD) for secondhand smoking exposure were calculated.


Results
A total of 14 unique articles (n=697,185 participants) were eventually included in the analysis. When all studies were pooled, the RR of stroke for secondhand smoking exposure was 1.20 (95% CI: 1.04, 1.38). When studies included only non-smokers, the pooled RR of stroke was 1.20 (95% CI: 1.05, 1.37). Summary RRs of cognitive impairment and PD for secondhand smoking exposure were 1.43 (95% CI: 1.02, 2.00) and 0.83 (95% CI: 0.72, 0.95), respectively. Summary RRs did not change significantly when excluding one study at a time.


Conclusions
Secondhand smoking was found to be positively associated with risks of stroke and cognitive impairment, while inversely associated with risk of PD. Overall, our finding is a reminder of the need to step up smoking bans to prevent health damage, and also suggests that more researches on biological mechanisms whereby secondhand smoking affect PD may be beneficial to PD prevention and treatment.

AbstractThe Keio Twin Research Center (KoTReC) was established in 2009 at Keio University to combine two longitudinal cohort projects — the Keio Twin Study (KTS) for adolescence and adulthood and the Tokyo Twin Cohort Project (ToTCoP) for infancy and childhood. KoTReC also conducted a two-time panel study of self-control and psychopathology in twin adolescence in 2012 and 2013 and three independent anonymous cross-sectional twin surveys (ToTcross) before 2012 — the ToTCross, the Junior and Senior High School Survey and the High School Survey. This article introduces the recent research designs of KoTReC and its publications.

AbstractBenchmark dose (BMD) methodology has been employed as a default dose–response modeling approach to determine the toxicity value of chemicals to support regulatory chemical risk assessment. Especially, a relatively standardized BMD analysis framework has been established for modeling toxicological data regarding the formats of input data, dose–response models, definitions of benchmark response, and model uncertainty consideration. However, the BMD approach has not been well developed for epidemiological data mainly because of the diverse designs of epidemiological studies and various formats of data reported in the literature. Although most of the epidemiological BMD analyses were developed to solve a particular question, the methods proposed in two recent studies are able to handle cohort and case–control studies using summary data with consideration of adjustments for confounders. Therefore, the purpose of the present study is to investigate and compare the "effective count"‐based BMD modeling approach and adjusted relative risk (RR)‐based BMD analysis approach to identify an appropriate BMD modeling framework that can be generalized for analyzing published data of prospective cohort studies for BMD analysis. The two methods were applied to the same set of studies that investigated the association between bladder and lung cancer and inorganic arsenic exposure for BMD estimation. The results suggest that estimated BMDs and BMDLs are relatively consistent; however, with the consideration of established common practice in BMD analysis, modeling adjusted RR values as continuous data for BMD estimation is a more generalizable approach harmonized with the BMD approach using toxicological data.