Dao An T M, Do Loc G, Stormon Nicole, Dhanapriyanka Manori, Ha Diep H
School of Dentistry, Faculty of Health and Behavioural Sciences, The University of Queensland, Brisbane, Queensland, Australia.
Hanoi Medical University, Hanoi, Vietnam.
Community Dent Oral Epidemiol. 2025 Feb;53(1):7-16. doi: 10.1111/cdoe.13002. Epub 2024 Sep 9.
Causal analysis including causal inference and causal mediation is pivotal to inform effective interventions. In modern epidemilogy, causal analysis involves four key steps: formulating causal questions, employing directed acyclic graphs (DAGs), conducting data management and selecting statistical strategies. Our objective was to conduct a scoping review to assess how longitudinal observational studies (LOSs) in dental field have integrated these four steps to contribute leverage evidence that inform oral public health interventions.
LOSs focusing on determinants of dental caries published from 2012 to 2024 were systematically retrieved from five major databases. The Joanna Briggs Institute-scoping review guidance and the Covidence application were employed to identify eligible LOSs for being reviewed.
Out of the 85 eligible LOSs, none formulated causal hypothesis by applying 'what if' question or investigated mediation across three levels of the determinants of oral health. A minority (18 studies, ~21.2%) employed DAGs to visualise relationships among study variables, while only one third (33 studies, ~39%) clearly defined confounders. The majority (64 studies, ~75%) incorporated a time-varying feature of their data, yet only a few (11 studies) fully leveraged this advanced aspect. Among these studies that fully utilised time-varying data, more than half encountered challenges in employing robust statistics to address confounders arising from such data dynamics.
Dental LOSs have, to date, mostly focused on investigating associations over causality, often neglecting the four-step causal analysis and not fully utilising time-varying data. Researchers necessitate to shift their focus to causal inference and prioritise building capacity in causal analysis with a consistent four-step approach to advance the field. Studies exploring mechanisms linking determinants of dental caries across levels and leveraging time-varying data are strongly encouraged.
因果分析，包括因果推断和因果中介，对于指导有效的干预措施至关重要。在现代流行病学中，因果分析涉及四个关键步骤：提出因果问题、使用有向无环图（DAG）、进行数据管理和选择统计策略。我们的目的是进行一项范围综述，以评估牙科领域的纵向观察性研究（LOS）如何整合这四个步骤，以提供有助于为口腔公共卫生干预措施提供依据的证据。
从五个主要数据库中系统检索2012年至2024年发表的关注龋齿决定因素的纵向观察性研究。采用乔安娜·布里格斯研究所范围综述指南和Covidence应用程序来确定符合条件的纵向观察性研究进行综述。
在85项符合条件的纵向观察性研究中，没有一项通过应用“如果……会怎样”的问题来提出因果假设，也没有一项研究在口腔健康决定因素的三个层面上研究中介作用。少数研究（18项研究，约21.2%）使用有向无环图来可视化研究变量之间的关系，而只有三分之一（33项研究，约39%）明确界定了混杂因素。大多数研究（64项研究，约75%）纳入了其数据的时变特征，但只有少数研究（11项研究）充分利用了这一先进方面。在这些充分利用时变数据的研究中，超过一半的研究在采用稳健统计方法来解决此类数据动态产生的混杂因素方面遇到了挑战。
迄今为止，牙科纵向观察性研究大多侧重于研究关联性而非因果关系，常常忽视四步因果分析，且未充分利用时变数据。研究人员需要将重点转移到因果推断上，并优先采用一致的四步方法来建立因果分析能力，以推动该领域的发展。强烈鼓励开展探索龋齿决定因素跨层面联系机制并利用时变数据的研究。
