Mapping predictors of physical morbidity and mortality in schizophrenia

精神分裂症使预期寿命缩短20年。这种过早死亡主要是由于心血管和呼吸系统疾病，而不是自杀，这是由吸烟、不良饮食、缺乏运动、久坐不动的生活方式和抗精神病药物的代谢影响造成的。在最近的普通人群调查中，对久坐生活方式的粗略测量预测了与剧烈运动无关的死亡率。精神分裂症患者很少运动，负面症状和镇静可能也使他们特别久坐。我们假设，这将成为一个基于两阶段调查的先进风险统计模型的关键因素，该模型采用了一种新颖的措施组合。该项目的第一个实验将评估8名使用MAHSC和大曼彻斯特西部（GMW）服务的精神分裂症患者一周内的活动记录仪和一般活动和昼夜节律（CR）日记测量的可行性和可接受性。在第二个实验中，300名精神分裂症患者将被要求完成一项调查，以收集有关吸烟、运动、每天坐着的时间、CR和困倦、家族史、发病率和药物依从性的信息。然后，这些数据将与索尔福德独特的单一电子服务记录中的代谢和临床数据以及关键工作人员对症状严重程度的估计相关联。在最后的实验中，将确定并招募一个子样本，以详细评估发病率、适应性、活动和CR的活动记录仪测量以及阴性症状。这些数据将用于构建身体死亡率和发病率风险的人口模型。该项目将研究CR、久坐生活方式、症状和可逆风险因素的作用。然后，这些新的度量和分析技术可以应用于一系列人群，对活动等关键变量进行精确测量。了解风险预测因素的相互作用将指导干预措施，并展示哪些目标具有最大价值，包括减少坐着的时间。学生将能够很好地应用这些技术来调查其他群体或支持干预措施的评估。

Schizophrenia reduces life expectancy by 20 years. Rather than than suicide, this premature mortality is mainly due to cardiovascular and respiratory disease, driven by smoking, poor diet, lack of exercise, sedentary lifestyle and the metabolic effects of antipsychotic medication. Crude measures of sedentary lifestyle predict mortality independent of vigorous exercise in recent general population surveys. Schizophrenia sufferers exercise little, with negative symptoms and sedation probably also make them particularly sedentary. We hypothesise that this will emerge as a key element in an advanced statistical model of risk based on a two phase survey with a novel combination of measures.The project's first experiment will assess feasibility and acceptability of actigraphy and diaries measures of general activity and circadian rhythms (CR) over 1 week in 8 schizophrenia sufferers using MAHSC & Greater Manchester West (GMW) services.In the second experiment, 300 schizophrenia suffers will be asked to complete a survey to gather information on smoking, exercise, daily time spent sitting, CR and sleepiness, family history, morbidity and adherence to medication. This data will then link to metabolic and clinical data from Salford's unique single electronic service records and key worker estimates of symptom severity.During the final experiment, a subsample will be identified and recruited for a detailed assessment of morbidity, fitness, actigraphy measures of activity and CR, and negative symptoms.These data will be used to construct a population model of risk for physical mortality and morbidity. The project will examine the role of CR, sedentary lifestyle, symptoms and reversible risk factors.These new metric and analytic techniques can then be applied to a range of populations, with precise measurement of critical variables like activity. Understanding the interplay of risk predictors will guide interventions and demonstrate what targets have the greatest value, including reducing time spent sitting. The student will be well equipped to apply such techniques to surveying other groups or supporting evaluation of interventions.