Selection of statistical methods for estimating the association between exposure factors and rare outcomes based on cohort studies.
10.3760/cma.j.cn112338-20230106-00011
- VernacularTitle:基于队列研究估计暴露因素与罕见结局关联的统计方法选择
- Author:
Xiao Hang LIU
1
;
Chen WANG
1
;
Ruo Hua YAN
1
;
Xiao Xia PENG
1
;
Cheng Hong YIN
2
Author Information
1. Center for Clinical Epidemiology and Evidence-Based Medicine, Beijing Children's Hospital, Capital Medical University, National Center for Children Health, Beijing 100045, China.
2. Department of Central Laboratory, Beijing Obstetrics and Gynecology Hospital, Capital Medical University/Beijing Maternal and Child Health Care Hospital, Beijing 100026, China.
- Publication Type:Journal Article
- From:
Chinese Journal of Epidemiology
2023;44(7):1126-1132
- CountryChina
- Language:Chinese
-
Abstract:
Odds ratio (OR) and relative risk (RR) are the most commonly used statistical indicators for the estimation of the association between exposure and outcome. In the cohort study with rare outcomes, the estimated OR approximately equals RR, but RR seems more interpretable. The study aims to explore the difference between OR and RR estimated by different multivariate analyses to provide reference for the selection of more appropriate multivariate regression methods and reporting indicators for estimating the association between exposure and rare outcome in cohort studies. This case study used the data from China birth cohort study. Modes of conception and congenital disabilities were regarded as exposure and outcome, respectively. Maternal age, family history of congenital disabilities with clear evidence were included as covariates. Logistic regression, log-binomial regression, and Poisson regression were used to estimate the OR and RR, respectively. Then, OR, RR, and their 95%CI estimated by three regression models were compared. The OR estimated by logistic regression was approximately equal to the RR estimated by log-binomial regression or Poisson regression. However, the RR estimated by log-binomial regression or Poisson regression was closer to 1.00, with a narrower 95%CI. Log-binomial regression or Poisson regression might have non convergence or over dispersion problems. It is recommended to report the RR obtained by log-binomial regression or Poisson regression in the cohort study with rare outcomes if applicable.
