Validity of Self-Report Data in Hypertension Research: Findings from the Study on Global Ageing and Adult Health (SAGE)

Eric Tenkorang, Memorial University
Yujiro Sano, University of Western Ontario
Pearl Sedziafa, Memorial University
Vincent Kuuire, University of Western Ontario

Several studies indicate little congruence between self-report and biometric data, yet 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) for five countries (Ghana, China, India, South Africa and Russia). Data were obtained from Wave 1 of the SAGE collected in 2007/2008. A multinomial logit model is used to examine the effect of demographic and socio-economic variables on the likelihood of respondents self-reporting that they are not hypertensive when their biometric data shows otherwise. We also model the likelihood of respondents self-reporting that they are hypertensive when in fact their biometric data shows otherwise. Socio-economic and demographic variables are significantly associated with inconsistent reporting of hypertension. Tracking inconsistent reports is crucial to minimizing measurement errors and generating unbiased and precise parameter estimates.