Measuring adult mortality using sibling survival: new analytical methods and results for 38 countries, 1970-2005

Ziad Obermeyer, University of Washington
Julie Knoll Rajaratnam, University of Washington
Chang Park, University of Washington
Emmanuela Gakidou, University of Washington
Margaret C Hogan, Institute for Health Metrics and Evaluation
Alan D. Lopez, University of Queensland
Christopher J.L. Murray, University of Washington

To date, attempts to measure adult mortality from questions in censuses and surveys have generally led to implausibly low levels owing to biases inherent in survey data such as survival and recall bias. We present the Corrected Sibling Survival (CSS) method, which addresses both. It directly estimates the probability of death for a country, age, sex and time period from sibling history data using logistic regression. We apply the method to generate estimates and trends of 45q15 for 38 countries. Our findings suggest that levels of adult mortality in many developing countries are substantially higher than some have suggested. This effort represents a major expansion of our direct knowledge of levels and trends in adult mortality in these countries. The CSS method provides grounds for renewed optimism in collecting sibling survival data. We argue that all nationally representative survey programs ought to implement this critical module for tracking adult mortality.