Suppr超能文献

肥胖症中的因果模型和因果建模:基础、方法和证据。

Causal models and causal modelling in obesity: foundations, methods and evidence.

机构信息

Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, Bloomington, IN, 47405-7000, USA.

University of Cambridge, Cambridge, CW3 OWB, UK.

出版信息

Philos Trans R Soc Lond B Biol Sci. 2023 Oct 23;378(1888):20220227. doi: 10.1098/rstb.2022.0227. Epub 2023 Sep 4.

Abstract

, if we are to do so in a way that is sensible, begins at the root. All too often, we jump to discussing specific postulated causes but do not first consider what we mean by, for example, of obesity or how we discern whether something is a cause. In this paper, we address what we mean by a cause, discuss what might and might not constitute a reasonable causal model in the abstract, speculate about what the causal structure of obesity might be like overall and the types of things we should be looking for, and finally, delve into methods for evaluating postulated causes and estimating causal effects. We offer the view that different meanings of the concept of causal factors in obesity research are regularly being conflated, leading to confusion, unclear thinking and sometimes nonsense. We emphasize the idea of different kinds of studies for evaluating various aspects of causal effects and discuss experimental methods, assumptions and evaluations. We use analogies from other areas of research to express the plausibility that only inelegant solutions will be truly informative. Finally, we offer comments on some specific postulated causal factors. This article is part of a discussion meeting issue 'Causes of obesity: theories, conjectures and evidence (Part II)'.

摘要

如果我们要以明智的方式做到这一点,就必须从根本出发。我们常常急于讨论具体假设的原因,但却没有首先考虑我们所说的肥胖的“原因”是什么,或者我们如何辨别某件事是否是原因。在本文中,我们将讨论我们所说的原因,讨论在抽象意义上可能和不可能构成合理因果模型的内容,推测肥胖的整体因果结构可能是什么样的,以及我们应该寻找的东西的类型,最后,深入探讨评估假设原因和估计因果效应的方法。我们认为,肥胖研究中因果因素概念的不同含义经常被混淆,导致混淆、思维不清晰,有时甚至是无意义。我们强调了评估因果效应各个方面的不同类型研究的想法,并讨论了实验方法、假设和评估。我们使用来自其他研究领域的类比来表达这样一种可能性,即只有不优雅的解决方案才真正具有信息性。最后,我们对一些特定的假设因果因素进行了评论。本文是“肥胖的原因:理论、推测和证据(第二部分)”讨论专题的一部分。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c37d/10475873/56c1addd13ce/rstb20220227f01.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验