Abstract
More adults are dying between the ages of 15 and 60 in developing countries than previously thought, according to new research that used a novel analytical technique developed to improve estimates. The study, Measuring adult mortality using sibling survival: a new analytical method and new results for 44 countries, 1974-2006, shows how this new method can address problems that have prevented health surveys from being used as an accurate source of adult mortality data. Additionally, the new techniques provide a tool for directly measuring the impact of HIV instead of relying solely on theoretical models. The work was done in collaboration with scientists at the University of Queensland.
Research findings
Study researchers introduced a new method called the Corrected Sibling Survival (CSS) method. Using a sample of 44 countries, researchers used the CSS method to show that more adults are dying between the ages of 15 and 60 in developing countries than previously suggested by other analyses of sibling history data. This is especially true in countries with a high prevalence of HIV. Kenya, Zambia, Swaziland, and Tanzania all saw their death rates double between 1986 and 2006, and in Zimbabwe, a country badly affected by the HIV epidemic, there has been a three– to four-fold increase in adult mortality since the late 1980s. The new method also showed a sharp spike in mortality in Rwanda during the 1994 genocide, followed by a strong decline. The country’s death rate is now comparable to neighboring countries.
The study findings show the risk of adult death between ages 15 and 60 to be about 20% to 35% for females and 25% to 45% for males in sub-Saharan African populations largely unaffected by HIV. In countries of Southern Africa, where the HIV epidemic has been most pronounced, as many as 8 out of 10 men alive at age 15 will be dead by age 60, as will 6 out of 10 women.
Adult mortality levels in populations of Asia and Latin America are generally lower than in Africa, particularly for women. The exceptions are Haiti and Cambodia, where mortality risks are comparable to many countries in Africa. In all other countries with data, the probability of dying between ages 15 and 60 was typically around 10% for women and 20% for men, not much higher than the levels prevailing in several more developed countries.
The study findings also suggest that the CSS method, which applies a correction for both selection and recall bias, yields more accurate estimates of adult mortality in developing countries from sibling survival data than previous methods.
Analytical approach
Researchers used logistic regression to develop the CSS method. They then applied this method to generate estimates of and trends in adult mortality, using the summary measure 45q15—the probability of a 15-year-old dying before his or her 60th birthday—for 44 countries with sibling survival data from Demographic and Health Surveys.
Research objective
IHME is developing a variety of methods that improve the accuracy and timeliness of birth and death data to assist governments and international health agencies in low-resource settings to plan health care policies and monitor the effectiveness of public health interventions. Most low-income countries lack death registration systems, and researchers have to either create estimates based on child mortality rates or rely on surveys of siblings or others who have survived in families.
Surveys have yielded estimates in the past that were implausibly low, primarily for two reasons. Siblings often recall incorrectly the number of people who have died in their families and their ages at death, a problem known as recall bias. Another problem with surveys is that they often miss families that have been so devastated by mortality that there are few surviving members available to answer questions. This is known as survival bias. In this study, researchers developed a corrected sibling survival method that compensates for both recall bias and survival bias, allowing a more precise estimate of death rates in a given country by age, sex, and time period.
Recommendations for future work
Based on their findings, the researchers suggest that all nationally representative survey programs with adequate sample size ought to implement this new method for tracking adult mortality in order to more reliably understand the levels and patterns of adult mortality and how they are changing. Additionally, sibling survival histories should be routinely collected, with all respondents asked about sibling histories, in all future household survey programs.
Methods
In April 2010, researchers at IHME published in PLoS Medicine the Corrected Sibling Survival (CSS) methods, which address both the survival and recall biases that have plagued the use of survey data to estimate adult mortality. Using these new methods, researchers are able to more accurately estimate adult mortality levels and trends.
Using logistic regression, the methods directly estimate the probability of dying in a given country, by age, sex, and time period from sibling history data. The logistic regression framework borrows strength across surveys and time periods for the estimation of the age patterns of mortality and facilitates the implementation of solutions for underrepresentation of high-mortality families and recall bias.
IHME researchers then applied these new methods to 44 countries with Demographic and Health Survey (DHS) sibling survival data to generate estimates of and trends in adult mortality in those countries, using the summary measure 45q15, the probability of a 15-year-old dying before his or her 60th birthday.
Here, we provide our final results dataset for the 44 countries as well as the Stata code necessary to apply our methods to DHS data and reproduce the results presented in this paper.
