Estimating the infant mortality rate from DHS birth histories in the presence of age heaping

• Published in: PloS one 2021-11, Vol.16 (11), p.e0259304-e0259304
• Main Authors: Romero Prieto, Julio, Verhulst, Andrea, Guillot, Michel
• Format: Article
• Language: English
• Subjects: Acquired immune deficiency syndrome; Africa South of the Sahara - epidemiology; Age; Age groups; AIDS; Asia, Southeastern - epidemiology; Bias; Biology and Life Sciences; Birth; Birth Rate; Child mortality; Children & youth; Estimates; Evaluation; Families & family life; Female; HIV; Human immunodeficiency virus; Humans; Infant; Infant Mortality; Infants; Information sources; Life Tables; Male; Medicine and Health Sciences; Modelling; Mortality patterns; Patient outcomes; People and Places; Polls & surveys; Population; Registration; Response bias; Surveys and Questionnaires; Tables (data)
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0259304

The infant mortality rate (IMR) is a critical indicator of population health, but its measurement is subject to response bias in countries without complete vital registration systems who rely instead on birth histories collected via sample surveys. One of the most salient bias is the fact that child deaths in these birth histories tend to be reported with a large amount of heaping at age 12 months. Because of this issue, analysts and international agencies do not directly use IMR estimates based on surveys such as Demographic and Health Surveys (DHS); they rely instead on mortality models such as model life tables. The use of model life tables in this context, however, is arbitrary, and the extent to which this approach appropriately addresses bias in DHS-based IMR estimates remains unclear. This hinders our ability to monitor IMR levels and trends in low-and middle-income countries. The objective of this study is to evaluate age heaping bias in DHS-based IMR estimates and propose an improved method for adjusting this bias. Our method relies on a recently-developed log-quadratic model that can predict age-specific mortality by detailed age between 0 and 5. The model's coefficients were derived from a newly constituted database, the Under-5 Mortality Database (U5MD), that represents the mortality experience of countries with high-quality vital registration data. We applied this model to 204 DHS surveys, and compared unadjusted IMR values to IMR values adjusted with the log-quadratic model as well as with the classic model life table approach. Results show that contrary to existing knowledge, age heaping at age 12 months rarely generates a large amount of bias in IMR estimates. In most cases, the unadjusted IMR values were not deviating by more than +/- 5% from the adjusted values. The model life table approach, by contrast, introduced an unwarranted, downward bias in adjusted IMR values. We also found that two regions, Sub-Saharan Africa and South Asia, present age patterns of under-5 mortality that strongly depart from the experience represented in the U5MD. For these countries, neither the existing model life tables nor the log-quadratic model can produce empirically-supported IMR adjustments. Age heaping at age 12 months produces a smaller amount of bias in DHS-based IMR estimates than previously thought. If a large amount of age heaping is present in a survey, the log-quadratic model allows users to evaluate, and whenever necessary, adjust IMR estimates