Spatial Lifecourse Epidemiology Reporting Standards (ISLE-ReSt) statement.

Clicks: 301
ID: 104743
2020
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #13 of 15 articles by views in Health & place

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
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, psychosocial, 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 appropriate 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 contributors 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.
Reference Key
jia2020spatialhealth Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Jia, Peng;Yu, Chao;Remais, Justin V;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;
Journal Health & place
Year 2020
DOI
S1353-8292(19)30635-5
URL
Keywords
artificial intelligence big data spatial epidemiology exposome exposomics isle lifecourse epidemiology location-based reporting guideline reporting standard spatial lifecourse epidemiology

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.