Traditional epidemiological studies have identified a number of risk factors for various diseases using regression-based methods that examine the association between an exposure and an outcome (i.e., one-to-one correspondences). One of the major limitations of this approach is the “black-box” aspect of the analysis, in the sense that this approach cannot fully explain complex relationships such as biological pathways. With high-throughput data in current epidemiology, comprehensive analyses are needed. The network approach can help to integrate multi-omics data, visualize their interactions or relationships, and make inferences in the context of biological mechanisms. This review aims to introduce network analysis for systems epidemiology, its procedures, and how to interpret its findings.
Summary
Korean summary
본 리뷰는 시스템역학연구에 활용할 수 있는 네트워크 분석의 간략한 개념과 분석 절차 그리고 결과 해석에 대하여 소개하고 있다. 기존 역학연구의 주요 한계점은 생물학적 기전과 같은 복잡한 관계를 충분히 설명하지 못한다는 것이다. 최근 역학 연구에서 대규모의 오믹스 데이터가 활용 가능하게 됨에 따라 통합적 분석의 필요성이 제기되고 있고, 네트워크 분석 기법이 이런 다중 오믹스 데이터들을 포괄적으로 분석하는데 활용 될 수 있을 것이다.
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A blueprint for a new commercial driving epidemiology: An emerging paradigm grounded in integrative exposome and network epistemologies Yorghos Apostolopoulos, Sevil Sönmez, Matthew S. Thiese, Mubo Olufemi, Lazaros K. Gallos American Journal of Industrial Medicine.2024;[Epub] CrossRef
A network analysis of nutritional markers and maternal perinatal mental health in the French EDEN cohort Bethany Knox, Cédric Galera, Anne-Laure Sutter-Dallay, Barbara Heude, Blandine de Lauzon-Guillain, Judith van der Waerden BMC Pregnancy and Childbirth.2023;[Epub] CrossRef
Applying the exposome concept to working life health Anjoeka Pronk, Miranda Loh, Eelco Kuijpers, Maria Albin, Jenny Selander, Lode Godderis, Manosij Ghosh, Roel Vermeulen, Susan Peters, Ingrid Sivesind Mehlum, Michelle C. Turner, Vivi Schlünssen, Marcel Goldberg, Manolis Kogevinas, Barbara N. Harding, Svetl Environmental Epidemiology.2022; 6(2): e185. CrossRef
Reconstruction of the Temporal Correlation Network of All-Cause Mortality Fluctuation across Italian Regions: The Importance of Temperature and Among-Nodes Flux Guido Gigante, Alessandro Giuliani Entropy.2022; 25(1): 21. CrossRef
Network Analysis of Demographics, Dietary Intake, and Comorbidity Interactions Tung Hoang, Jeonghee Lee, Jeongseon Kim Nutrients.2021; 13(10): 3563. CrossRef
Objectives To assess the current public participation in-local health policy and its implications through the analysis of policy networks in health center programs.
Methods We examined the decision-making process in sub-health center installations and the implementation process in metabolic syndrome management program cases in two districts (‘gu’s) of Seoul. Participants of the policy network were selected by the snowballing method and completed self-administered questionnaires. Actors, the interactions among actors, and the characteristics of the network were analyzed by Netminer.
Results The results showed that the public is not yet actively participating in the local public health policy processes of decision-making and implementation. In the decision-making process, most of the network actors were in the public sector, while the private sector was a minor actor and participated in only a limited number of issues after the major decisions were made. In the implementation process, the program was led by the health center, while other actors participated passively.
Conclusions Public participation in Korean public health policy is not yet well activated. Preliminary discussions with various stakeholders, including civil society, are needed before making important local public health policy decisions. In addition, efforts to include local institutions and residents in the implementation process with the public officials are necessary to improve the situation.