Several studies indicate little congruence between self-report and biometric data, yet very few have examined the reasons for such differences. This paper contributes to the limited but growing body of literature that tracks inconsistent reports of hypertension using data from the Study on Global Ageing and Adult Health (SAGE). Focusing on five countries with different levels of development (Ghana, China, India, South Africa, and Russia), this study offers a comparative perspective that is missing in the literature. Data were obtained from wave 1 of SAGE collected in 2007/2008. A multinomial logit model was used to examine the effects of demographic and socioeconomic variables on the likelihood of respondents self-reporting that they are not hypertensive when their biometric data show otherwise. The authors also model the likelihood of respondents self-reporting that they are hypertensive when in fact their biometric data show they are not. Socioeconomic and demographic variables were shown to be significantly associated with inconsistent reporting of hypertension. For instance, it was observed that wealth was associated with a lower likelihood of self-reporting that one is not hypertensive when their biometric data indicate otherwise. Tracking such inconsistent reports is crucial to minimizing measurement errors and generating unbiased and more precise parameter estimates in hypertension research.