Estimating cost-effectiveness of diet and physical activity interventions for the primary prevention of non-communicable disease at the Local Authorit

可预防的疾病约占英国疾病负担的40%，主要是非传染性疾病，如心脏病和中风。这些疾病的病因，如肥胖，是可以预防的，这为避免残疾和死亡提供了机会。知道每花费一英镑可能预防多少疾病是有用的。为了计算出这笔钱的价值，使用了称为模型的复杂总和。目前，地方当局还没有考虑到当地特征的模型，比如人们的年龄、体重或锻炼水平。这就造成了翻译上的差距，阻碍了最佳干预措施的持续应用。该博士项目将开发一个慢性疾病预防模型，可以比较地方当局改善饮食和身体活动方法的性价比。这不仅将有助于地方决策者作出供资决定，而且还可以估计国家公共卫生政策对地方的影响。建模通过估计从干预到疾病结果的每一步的效果来工作。目前，模型对整个英格兰进行了估计，但无法估计不同地区的差异。例如，如果一个地方委员会为糖尿病患者的健身房会员花钱，模型可以估计这些人在现实世界中活动的增加，他们减轻的体重和糖尿病控制的改善；所有这些都是基于已发表的临床研究和标准的卫生经济学方法。更富裕的地区往往对健康促进有更好的反应，而且疾病和风险的模式也非常不同（例如，肥胖率较低），因此，在一个地区有效和物有所值的方法可能在另一个地区并不适用。地方估计也将有助于估计对卫生不平等的影响。该建模方法被称为比例多状态生命表模型，它模拟了一个种群的时间迁移、衰老和发展疾病。从那里，可以估计NHS的成本。通过并行进行两次，可以估计基线和干预之间的差异。为了使建模过程对本地输出具有灵活性，将增加两个额外步骤。首先，输入的风险因素概况需要反映当地，其次，结果将根据当地的年龄和性别构成进行标准化。由于当地收集的数据较差，估计了当地的风险因素概况。这一过程使用回归模型，根据人口统计和国家风险因素数据估计一个地区的风险因素概况。标准化工作将以人口普查数据为基础。将对两种情况进行建模。第一项研究将评估英国公共卫生部报告《儿童肥胖：行动计划》第2章（2018年）中卡路里减少计划的地方影响，该计划对成年人的健康有重大溢出影响。第二份报告将评估英国最近减少食盐摄入对当地的影响。第二种情景将比较废弃的行业责任协议（2011年）下的进展，以及从2000年开始到2011年之前食品标准局的减盐战略下的趋势。随后将进行验证和敏感性分析。将根据慢性病情景模型的国际实例进行验证。确定性敏感性分析将基于风险因素概况估计中产生的不确定性区间，概率敏感性分析将基于通过蒙特卡洛分析的相对风险周围的不确定性。该提案涉及MRC战略技能优先领域，包括定量技能（应用统计、计算机建模）和跨学科技能（流行病学、临床应用、卫生经济学、政策分析）。

Preventable disease is responsible for approximately 40% of the UK's disease burden, largely in the form of non-communicable diseases such as heart disease and stroke. Causes of these diseases, such as obesity, can be prevented, providing an opportunity to avert disability and deaths. It is useful to know how much disease is likely to be prevented for each pound of spending. To work out this value for money, complicated sums called models are used. At present, Local Authorities have no models that account for the characteristics of the local area, such as people's ages, weights or exercise levels. This acts as a translational gap, preventing the consistent application of the best interventions. This DPhil will develop a model for chronic disease prevention that can compare value for money across Local Authorities for approaches to improving diet and physical activity. This will not only help local decision-makers with funding decisions but also allow the local impacts of national public health policy to be estimated. Modelling works by estimating the effect of each step that leads from an intervention to a disease outcome. At present, models produce an estimate for England as a whole, without being able to estimate how this might vary for different areas. For example, if a local council spends money on gym memberships for diabetic patients, modelling could estimate the increase in activity those individuals do in the real world, the weight they lose and improvement in diabetes control; all based on published clinical research and standard health economic methods. More affluent areas tend to have better responses to health promotion, as well as very different patterns of diseases and risks (eg, having lower obesity rates), so an approach that is effective and good value for money in one area may not be in another. Local area estimates will also allow impacts on health inequalities to be estimated.The modelling method is called proportionate multistate lifetable modelling, which simulates a population moving through time, aging and developing disease. From there, NHS costs can be estimated. By doing this twice in parallel, the difference between a baseline and an intervention can be estimated. To make the modelling process flexible for local outputs, two additional steps will be added. Firstly, the input risk factor profiles need to reflect local areas, and secondly the results will be standardised to local area age and sex composition. Local risk factor profiles are estimated as locally-collected data are poor. This process uses regression modelling to estimate an area's risk factor profile based on demographics and national risk factor data. Standardisation will be performed based on census data. Two scenarios will be modelled. The first will estimate local implications of the calorie reduction plan from Public Health England's report Childhood Obesity: A Plan for Action, Chapter 2 (2018), which has major spillover health implications for adults. The second will estimate the local impacts of recent salt reduction in the UK. This second scenario will compare progress under the scrapped industry Responsibility Deal (2011) against the trend under the previous Food Standards Agency's Salt Reduction Strategy from its initiation in 2000 to 2011. Validation and sensitivity analyses will follow. Validation will be performed against international examples of chronic disease scenario models. Deterministic sensitivity analyses will be based on the uncertainty intervals produced in the risk factor profile estimates and probabilistic sensitivity analyses will be based uncertainty around the Relative Risks through Monte Carlo Analysis. This proposal involves MRC Strategic Skill Priority areas in quantitative skills (applied statistics, computer modelling) and interdisciplinary skills (epidemiology, clinical application, health economics, policy analysis).