Grupo Latinoamericano de Investigaciones Epidemiológicas, Organización Latinoamericana para el Fomento de la Investigación en Salud, Bucaramanga, Colombia.
BMC Med Res Methodol. 2012 Feb 15;12:14. doi: 10.1186/1471-2288-12-14.
Odds ratios (OR) significantly overestimate associations between risk factors and common outcomes. The estimation of relative risks (RR) or prevalence ratios (PR) has represented a statistical challenge in multivariate analysis and, furthermore, some researchers do not have access to the available methods.
To propose and evaluate a new method for estimating RR and PR by logistic regression.
A provisional database was designed in which events were duplicated but identified as non-events. After, a logistic regression was performed and effect measures were calculated, which were considered RR estimations. This method was compared with binomial regression, Cox regression with robust variance and ordinary logistic regression in analyses with three outcomes of different frequencies.
ORs estimated by ordinary logistic regression progressively overestimated RRs as the outcome frequency increased. RRs estimated by Cox regression and the method proposed in this article were similar to those estimated by binomial regression for every outcome. However, confidence intervals were wider with the proposed method.
This simple tool could be useful for calculating the effect of risk factors and the impact of health interventions in developing countries when other statistical strategies are not available.
比值比（OR）显著高估了危险因素与常见结局之间的关联。在多变量分析中，相对风险（RR）或患病率比（PR）的估计一直是一个统计学挑战，此外，一些研究人员无法获得可用的方法。
提出并评估一种通过逻辑回归估计 RR 和 PR 的新方法。
设计了一个临时数据库，其中事件被重复但被标识为非事件。然后，进行逻辑回归并计算效应度量，这被认为是 RR 估计值。该方法与二项式回归、具有稳健方差的 Cox 回归和普通逻辑回归在三种不同频率结局的分析中进行了比较。
普通逻辑回归估计的 OR 随着结局频率的增加而逐渐高估 RR。Cox 回归和本文提出的方法估计的 RR 与二项式回归在每种结局下都相似。然而，该方法的置信区间更宽。
当没有其他统计策略可用时，这个简单的工具可以在发展中国家计算危险因素的影响和健康干预措施的效果。
