Fitness versus fatness: Disentangling their effects on disease outcomes and estimating the population burden of disease
Fitness versus fatness: Disentangling their effects on disease outcomes and estimating the population burden of disease
批准号:
nhmrc : 436866
负责人:
Prof Andrew Forbes
金额:
$12.57万
依托单位:
依托单位国家:
澳大利亚
项目类别:
NHMRC Project Grants
财政年份:
2007
资助国家:
澳大利亚
项目状态:
已结题
起止时间:
2007-01-01 至 2008-12-31
中文摘要
超重和缺乏身体活动是心血管疾病和糖尿病的两个主要危险因素。随着人口超重水平的增加,政府越来越多地提倡旨在增加体育活动水平或以其他方式减轻体重的公共卫生措施。关于这些因素中的哪一个是不良健康结果的关键预后因素,已经进行了大量研究,但由于研究结果一直缺乏明确性,导致预防保健战略和人口生活方式改变建议的方向不确定。此外,超重的风险尤其被指责在科学和非专业文献中都被夸大了。这通常是由于难以适当地处理时变混杂因素,这些混杂因素也是中间因素(如高血压)。迄今为止,还没有研究对缺乏身体活动和超重对心血管事件和糖尿病的联合影响进行仔细的纵向建模,同时考虑到高血压或动脉粥样硬化等因素的影响,这些因素既影响身体活动和超重,也影响疾病,同时也是这些风险因素的后果。众所周知,标准统计方法在这些情况下会产生有偏差的估计,但我们将应用最近开发的统计技术来提供对这些影响的改进估计。在统计建模阶段之后,我们将对糖尿病、心血管疾病的负担以及与给定超重和缺乏身体活动水平相关的死亡率进行建模。这些数据将与超重和缺乏活动的人口水平相结合,以确定当前和未来由这些风险因素造成的疾病负担的比例。
英文摘要
Overweight and physical inactivity are two of the major risk factors for cardiovascular disease and diabetes. With increasing population levels of overweight, governments are increasingly advocating public health measures aimed at increasing physical activity levels or otherwise decreasing weight. There has been much research concerning which of these factors is the key prognostic factor for adverse health outcomes, but an ongoing lack of clarity of research findings has led to uncertainty as to the direction of recommendations for preventive health strategies and population lifestyle changes. In addition, the risks of overweight, in particular, have been accused of being exaggerated in both the scientific and lay literature. This is often due to the difficulty of dealing appropriately with time varying confounders which are also intermediate factors (such as hypertension). To date, no studies have performed careful longitudinal modelling of the joint effects of physical inactivity and overweight on cardiovascular events and diabetes while taking into account the effects of factors, such as hypertension or atherosclerosis, that influence both physical activity and overweight as well as disease, and simultaneously are consequences of these risk factors. Standard statistical methods are known to produce biased estimates in these situations but we will apply more recently developed statistical techniques to provide much improved estimation of these effects. After the statistical modelling stage, we will model the burden of diabetes, cardiovascular disease and mortality associated with given levels of overweight and physical inactivity. These will be combined with population levels of overweight and inactivity to identify the fraction of the current and future burden of disease attributable to these risk factors.
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