A simple method for estimating relative risk using logistic regression

BMC Medical Research Methodology

Fredi A Diaz-Quijano¹ 

[1] Grupo Latinoamericano de Investigaciones Epidemiológicas, Organización Latinoamericana para el Fomento de la Investigación en Salud (OLFIS), Bucaramanga, Colombia

关键词: Relative risk.;    Prevalence ratio;    Odds ratio;    Logistic regression;   

Others  :  1136831
DOI  :  10.1186/1471-2288-12-14

 received in 2011-08-01, accepted in 2012-02-15,  发布年份 2012

【 摘 要 】

Background

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. Objective: To propose and evaluate a new method for estimating RR and PR by logistic regression.

Methods

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.

Results

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.

Conclusion

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.

【 授权许可】

   
2012 Diaz-Quijano; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

【 参考文献 】

• [1]McNutt LA, Wu C, Xue X, Hafner JP: Estimating the relative risk in cohort studies and clinical trials of common outcomes. Am J Epidemiol 2003, 157:940-3.
• [2]Zhang J, Yu KF: What's the Relative Risk? A Method of Correcting the Odds Ratio in Cohort Studies of Common Outcomes. JAMA 1998, 280:1690-1691.
• [3]Pearce N: Effect measure in prevalence studies. Environ Health Perspect 2004, 112:1047-1050.
• [4]Wacholder S: Binomial regression in GLIM: estimating risk ratios and risk differences. Am J Epidemiol 1986, 123:174-184.
• [5]Nijem K, Kristensen P, Al-Khatib A, Bjertness E: Application of different statistical methods to estimate risk for self-reported health complaints among shoe factory workers exposed to organic solvents and plastic compounds. Norsk Epidemiologi 2005, 15:111-116.
• [6]Lee J, Chia KS: Estimation of prevalence rate ratios for cross sectional data: an example in occupational epidemiology. Br J Ind Med 1993, 50:861-862.
• [7]Barros AJD, Hirakata VN: Alternatives for logistic regression in cross-sectional studies: an empirical comparison of models that directly estimate the prevalence ratio. BMC Med Res Methodol 2003, 3:21. BioMed Central Full Text
• [8]Kulathinal S, Karvanen J, Saarela O, Kuulasmaa K: Case-cohort design in practice - experiences from the MORGAM Project. Epidemiol Perspect Innov 2007, 4:15.
• [9]Flanders WD: Limitations of the case-exposure study. Epidemiology 1990, 1:34-38.
• [10]Sato T: Estimation of a common risk ratio in stratified case-cohort studies. Stat Med 1992, 11:1599-605.
• [11]Sato T: Risk ratio estimation in case-cohort studies. Environ Health Perspect 1994, 102(Suppl 8):53-6.
• [12]Lee J, Tan CS, Chia KS: A practical guide for multivariate analysis of dichotomous outcomes. Ann Acad Med Singapore 2009, 38:714-719.
• [13]Schwartz LM, Woloshin S, Welch HG: Misunderstandings about the effects of race and sex on physicians' referrals for cardiac catheterization. N Engl J Med 1999, 341:279-83.
• [14]Localio AR, Margolis DJ, Berlin JA: Relative risks and confidence intervals were easily computed indirectly from multivariable logistic regression. J Clin Epidemiol 2007, 60:874-882.
• [15]Thompson ML, Myers JE, Kriebel D: Prevalence odds ratio or prevalence ratio in the analysis of cross sectional data: what is to be done? Occup Environ Med 1998, 55:272-277.
• [16]Coutinho LM, Scazufca M, Menezes PR: Methods for estimating prevalence ratios in cross-sectional studies. Rev Saude Publica 2008, 42:992-998.