The relative impact of 13 chronic conditions across three different outcomes
The relative impact of 13 chronic conditions across three different outcomes
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DOI：
10.1136/jech.2006.047308
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发表时间：
2007-12-01
影响因子：
6.3
通讯作者：
Badley, Elizabeth M.
中科院分区：
文献类型：
--
作者：
Perruccio, Anthony V.;Power, J. Denise;Badley, Elizabeth M.
研究目的：先前对慢性疾病所致不良结局的个体和人群归因风险的估计仅考虑了有限数量的疾病和结局，一些研究使用了不适当的公式或估计方法。本研究重新审视了广泛的条件和各种健康outcome.Design的个人和人口归因风险的大小：对数泊松回归被用来计算患病率作为一个指标的个人风险和人口相关的13个慢性疾病的分数，检查活动的限制，自我评价的健康和医生就诊。研究对象：加拿大，2000- 01年。参与者：全国12岁以上的加拿大代表性样本（n = 130 880）。主要结果：在个人层面上，纤维肌痛/慢性疲劳综合征和癌症，以及在较小程度上中风和心脏病，与活动受限和自我评定的健康状况一般或较差的风险增加相关;高血压与过去12个月内4次或4次以上的医生就诊相关。相反，在所有结局中，关节炎/风湿病、心脏病、背部问题和高血压的人群归因分数很大。调整多因素导致患病率显着下降ratios.Conclusions：不同疾病和结果的个体风险和人群归因分数的排名差异是巨大的。在确定优先事项时需要考虑到这一点，因为干预措施可能需要针对不同的条件，这取决于所考虑的健康方面，以及重点是个人，如临床护理，还是改善人口的健康。
Study objective: Previous estimates of individual and population attributable risks for adverse outcomes due to chronic conditions have considered only a limited number of conditions and outcomes, with some studies using inappropriate formulae or methods of estimation. This study re-examines the magnitude of individual and population attributable risks for a wide range of conditions and various health outcomes.Design: Log-Poisson regression was used to calculate prevalence ratios as an indicator of individual risk and population-associated fractions of 13 chronic conditions, examining activity limitations, self-rated health and physician visits. The effect of multimorbidity on prevalence ratios was examined.Setting: Canada, 2000-01.Participants: Nationally representative sample of Canadians aged 12+ years (n = 130 880).Main results: At the individual level, fibromyalgia/chronic fatigue syndrome and cancer, and to a lesser extent stroke and heart disease, were associated with an increased risk of both activity limitations and a self-rated health status of fair or poor; high blood pressure was associated with four or more physician visits in the previous 12 months. In contrast, population attributable fractions were substantial for arthritis/rheumatism, heart disease, back problems and high blood pressure across all outcomes. Adjustment for multimorbidity resulted in a marked decreases in prevalence ratios.Conclusions: Differences in the ranking of individual risks and population attributable fractions for different diseases and outcomes are substantial. This needs to be taken into account when setting priorities, as interventions may need to be targeted to different conditions depending on which aspects of health are being considered, and whether the focus is on individuals, such as in clinical care, or improving the health of the population.