• Rikuta Hamaya, Peilu Wang, Lin Ge, Edward L Giovannucci, and Molin Wang.
• Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA; Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA.
• Am J Prev Med. 2024 Nov 29.

IntroductionWith advancement of medicine, alternative exposures or interventions are emerging with respect to a common outcome, and there are needs to formally test the difference in the associations of multiple exposures.MethodsThe paper proposes a duplication method-based multivariate Wald test in the Cox proportional hazard regression model to test the difference in the associations of multiple exposures with a same outcome. This method applies to continuous or categorical exposures. For illustration, the method was applied to compare the associations between alignment to two different dietary patterns (Alternative Healthy Eating Index-2010 [AHEI-2010] and reversed empirical dietary inflammatory pattern [rEDIP]), either as continuous or quartile exposures, and incident chronic diseases, defined as a composite of cardiovascular disease, cancer, and diabetes, in the Health Professional Follow-up Study (HPFS). Relevant sample codes in R that implement the proposed approach are provided. The present analysis was conducted in 2024.ResultsWith a median follow-up of 22 years, there were a total of 14,427 chronic disease incidences among N=43,185 men included in the HPFS analysis. The hazard ratios (HRs) [95% confidence interval] per increment from the 10th to the 90th percentile for incident chronic disease were 0.83 [0.79, 0.87] for AHEI-2010 and 0.76 [0.73, 0.80] for rEDIP. Although the 95% CIs were overlapped for each exposure, the proposed test was well powered to detect the difference (p=0.005).ConclusionsThe proposed duplication-method-based approach offers a flexible, formal statistical test for heterogeneity in the associations of multiple exposures with the common outcome with minimal assumptions.Copyright © 2024. Published by Elsevier Inc.

5 keywords...

hide…