PROJECT SUMMARY
Following large declines in childhood mortality and progress in lowering mortality from causes of death that
affect young adults, mortality is rapidly shifting to ages above 50 years old in low- and lower middle-income
countries (LLMICs). Global health objectives now emphasize preventing deaths in those older age groups.
US federal agencies, international organizations and governments of LLMICs are thus expected to increase
their investments in interventions addressing non-communicable diseases and other behavioral factors that
affect mortality risks above age 50 in LLMICs. Designing, targeting, and evaluating these interventions
requires accurate estimates of death rates at older ages. However, the standard sources of mortality data
(i.e., civil registration and vital statistics systems) are deficient in most LLMICs. We propose to test a survey
method for the measurement of mortality above age 50 in LLMICs, the “parental survival history”. This
method extends the approach used to generate survey data on mortality in younger age groups, by asking
respondents to report the vital status of their biological parents, as well as their age (if alive) or age at death
and time since death (if deceased). Its collection only requires minimal time (<2 minutes per survey
respondent). It can thus readily be integrated into the questionnaires of large surveys conducted in LLMICs,
such as the Demographic and Health Surveys. We examine the possibility of selection biases in parental
survival histories, using long-term data on family ties and mortality from several health and demographic
surveillance systems in Africa and Asia. Then, we measure the prevalence of reporting errors in parental
survival histories, including misclassification of vital status, as well as age and date errors. Finally, we use
micro-simulations to identify a) the settings in which parental survival histories might yield accurate
estimates of mortality at older ages, and b) the sample sizes required for these estimates to be sufficiently
precise. If accurate and collected on a large scale, data from parental survival histories will help better track
progress towards new global health goals in LLMICs that pertain primarily to ages 50 and older.