New Survey Measures of Mortality at Older Ages in Low and Middle-Income Countries

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.