Browsing by Subject "Lifecourse epidemiology"

Sort by: Order: Results:

Now showing items 1-2 of 2
  • Jia, Peng; Yu, Chao; Remais, Justin; Stein, Alfred; Liu, Yu; Brownson, Ross C.; Lakerveld, Jeroen; Wu, Tong; Yang, Lijian; Smith, Melody; Amer, Sherif; Pearce, Jamie; Kestens, Yan; Kwan, Mei-Po; Lai, Shengjie; Xu, Fei; Chen, Xi; Rundle, Andrew; Xiao, Qian; Xue, Hong; Luo, Miyang; Zhao, Li; Cheng, Guo; Yang, Shujuan; Zhou, Xiaolu; Li, Yan; Panter, Jenna; Kingham, Simon; Jones, Andy; Johnson, Blair T.; Shi, Xun; Zhang, Lin; Wang, Limin; Wu, Jianguo; Mavoa, Suzanne; Toivonen, Tuuli; Mwenda, Kevin M.; Wang, Youfa; Verschuren, W. M. Monique; Vermeulen, Roel; James, Peter (2020)
    Spatial lifecourse epidemiology is an interdisciplinary field that utilizes advanced spatial, location-based, and artificial intelligence technologies to investigate the long-term effects of environmental, behavioural, psycho-social, and biological factors on health-related states and events and the underlying mechanisms. With the growing number of studies reporting findings from this field and the critical need for public health and policy decisions to be based on the strongest science possible, transparency and clarity in reporting in spatial lifecourse epidemiologic studies is essential. A task force supported by the International Initiative on Spatial Lifecourse Epidemiology (ISLE) identified a need for guidance in this area and developed a Spatial Lifecourse Epidemiology Reporting Standards (ISLE-ReSt) Statement. The aim is to provide a checklist of recommendations to improve and make more consistent reporting of spatial lifecourse epidemiologic studies. The STrengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement for cohort studies was identified as an appro-priate starting point to provide initial items to consider for inclusion. Reporting standards for spatial data and methods were then integrated to form a single comprehensive checklist of reporting recommendations. The strength of our approach has been our international and multidisciplinary team of content experts and con-tributors who represent a wide range of relevant scientific conventions, and our adherence to international norms for the development of reporting guidelines. As spatial, location-based, and artificial intelligence technologies used in spatial lifecourse epidemiology continue to evolve at a rapid pace, it will be necessary to revisit and adapt the ISLE-ReSt at least every 2-3 years from its release.
  • LifeCycle Project Group; Pinot de Moira, Angela; Haakma, Sido; Strandberg-Larsen, Katrine; Eriksson, Johan G.; Mikkola, Tuija M.; Nybo Andersen, Anne-Marie (2021)
    The Horizon2020 LifeCycle Project is a cross-cohort collaboration which brings together data from multiple birth cohorts from across Europe and Australia to facilitate studies on the influence of early-life exposures on later health outcomes. A major product of this collaboration has been the establishment of a FAIR (findable, accessible, interoperable and reusable) data resource known as the EU Child Cohort Network. Here we focus on the EU Child Cohort Network’s core variables. These are a set of basic variables, derivable by the majority of participating cohorts and frequently used as covariates or exposures in lifecourse research. First, we describe the process by which the list of core variables was established. Second, we explain the protocol according to which these variables were harmonised in order to make them interoperable. Third, we describe the catalogue developed to ensure that the network’s data are findable and reusable. Finally, we describe the core data, including the proportion of variables harmonised by each cohort and the number of children for whom harmonised core data are available. EU Child Cohort Network data will be analysed using a federated analysis platform, removing the need to physically transfer data and thus making the data more accessible to researchers. The network will add value to participating cohorts by increasing statistical power and exposure heterogeneity, as well as facilitating cross-cohort comparisons, cross-validation and replication. Our aim is to motivate other cohorts to join the network and encourage the use of the EU Child Cohort Network by the wider research community.