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Syndemic methodology has been employed in several studies of HIV-related outcomes affecting Black men who have sex with men (BMSM) and rarely in Black heterosexual men. In contrast to the most common method for assessing syndemics, the use of a syndemic component index, latent class analysis can identify unique combinations of risk factors that may form a syndemic. Analyzing a primarily heterosexual sample of 1,786 Black men from the 2015 Behavioral Risk Factor Surveillance System (BRFSS), we used a 4 latent class model based on depression diagnosis, poverty, and healthcare access to predict ever having been HIV tested. Class 1 was characterized by low proportions of all the risk factors. Class 2 had relatively high healthcare barriers, being the most likely to not have a personal doctor (.8175) and the most likely to have no routine checkup in the past year (.6327) but had relatively low depression diagnosis and poverty. Class 3 had relatively high poverty (.8853), but generally low barriers to healthcare access. Class 4 was characterized by high proportions of all the risk factors. Using log-binomial regression models, there was a significantly lower prevalence of ever having been HIV tested among class 3 (PR = 0.69, 95% CI 0.49, 0.98) and class 4 (PR = 0.49, 95% CI 0.28, 0.84) compared to class 1. When adjusting for education, age, and marital status, the associations were attenuated but still significant for class 3 (aPR = 0.71, 95% CI 0.52, 0.96) and class 4 (aPR = 0.60, 95% CI 0.46, 0.78). Latent class analysis may better serve syndemic research aims in understanding HIV-related outcomes among high-risk populations. Future research using this method to evaluate HIV testing outcomes among BMSM is recommended.