Pathways and Levers for prevention of Multi-morbidity from Young and Middle Adulthood

预防青壮年多种疾病的途径和杠杆

• 批准号: MR/V005057/1
• 负责人: Edward Gregg
• 金额: $ 12.84万
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FV005057%2F1
• 关键词: Pathways; Levers; prevention; Multi; morbidity

Multimorbidity is the presence of two or even several more major health condition at the same time within a single person. It is a growing problem in the United Kingdom in part of the combination of increasing lifespans with unhealthy lifestyles. Although multimorbidity is most common in older age, poor diet, physical inactivity, and obesity in young adulthood and middle-age are likely important causes of the tendency to multimorbidity. We suspect that 3 conditions in particular - diabetes, hypertension, and depression - cause a large portion of multimorbidity because of the way that they work together to affect so many systems of the body. If this is the case, then programmes for focused lifestyle interventions could make a big difference in preventing multimorbidity. Unfortunately, it is difficult to know how these conditions in young and middle-age affect multimorbidity and what works to prevent it because no studies track population across many stage of life, while measuring the impact of interventions. This research progamme will tackle these questions with 3 parts. First, it will use long-term data from the UK and London populations to uncover the most common combinations of diseases occurring and whether there are particular steps and pathways in their formation. After finding those combinations and estimating how rapidly they develop at different times in life, we will construct a new computer-based model, called a "life-course simulation model" that can identify the optimal times in life, combinations of behaviors, risk factors, and diseases that cause the greatest illness over life. The computer model will also examine the effect of different ways of preventing the accumulation of multimorbidity, such as using focused support to change lifestyle in people at risk for hypertension, diabetes, and depression. The third part of the research programme will use these data and the computer model to measure the effect of two National Health Service initiatives that support people at risk of diabetes or with diabetes to change lifestyle diabetes. Since lifestyle behaviors are also crucial to hypertension, depression, and other conditions, these "natural experiments" may have a big effect on multimorbidity as well. This work will require a team with expertise in diverse areas - including medical care, epidemiology, behaviour change, mathematics, and computer modeling. This study will answer important questions about what types of conditions are causing the most multimorbidity and what are the best ways to act to prevent them. The computer model and research that results will give doctors, health planners, and the public new way to improve health in communities for the years to come. The work will be first-of-its-kind in the way that it assesses chronic conditions as they form in combination from young adulthood to older adulthood. It will also be new in the way it uses computer models and natural experiments in combination to find out what works best to reduce multimorbidity.

多发病是指一个人同时存在两种或几种以上的主要健康状况。在英国，这是一个日益严重的问题，部分原因是寿命延长与不健康的生活方式相结合。虽然多发性硬化症在老年人中最常见，但年轻人和中年人的不良饮食、缺乏运动和肥胖可能是多发性硬化症倾向的重要原因。我们怀疑有三种疾病-糖尿病，高血压和抑郁症-会导致很大一部分的多发性硬化症，因为它们共同影响身体的许多系统。如果是这样的话，那么有针对性的生活方式干预计划可能会在预防多发性硬化症方面产生很大的影响。不幸的是，很难知道年轻人和中年人的这些情况如何影响多发病，以及如何预防多发病，因为没有研究在衡量干预措施的影响时跟踪人口的许多生命阶段。本研究计划将从三个方面来解决这些问题。首先，它将使用来自英国和伦敦人群的长期数据，以揭示最常见的疾病组合，以及它们的形成是否有特定的步骤和途径。在找到这些组合并估计它们在生命中不同时期的发展速度之后，我们将构建一个新的基于计算机的模型，称为“生命过程模拟模型”，可以识别生命中的最佳时间，行为组合，风险因素和导致一生中最严重疾病的疾病。该计算机模型还将研究不同方法预防多Morphine积累的效果，例如使用集中支持来改变高血压，糖尿病和抑郁症风险人群的生活方式。研究计划的第三部分将使用这些数据和计算机模型来衡量两项国家卫生服务计划的效果，这些计划支持糖尿病风险人群或糖尿病患者改变糖尿病生活方式。由于生活方式行为对高血压、抑郁症和其他疾病也至关重要，这些“自然实验”可能对多Morphine也有很大影响。这项工作将需要一个具有不同领域专业知识的团队-包括医疗保健，流行病学，行为改变，数学和计算机建模。这项研究将回答有关什么类型的条件是导致最多的多发性硬化症和什么是最好的方法来采取行动，以防止他们的重要问题。计算机模型和研究结果将为医生，健康规划师和公众提供新的方式来改善社区的健康状况。这项工作将是第一次在评估慢性疾病的方式，因为它们形成的组合从青年到老年人。它也将是新的方式，它使用计算机模型和自然实验相结合，以找出什么是最有效的，以减少多莫尔。

项目成果

Characterizing Multimorbidity from Type 2 Diabetes: Insights from Clustering Approaches.

• DOI: 10.1016/j.ecl.2021.05.012
• 发表时间: 2021-09
• 期刊: Endocrinology and metabolism clinics of North America
• 影响因子: 4.5
• 作者: Cicek M;Buckley J;Pearson-Stuttard J;Gregg EW
• 通讯作者: Gregg EW