Comparisons of infant mortality using a percentile-based method of standardization for birthweight or gestational age

Irva Hertz-Picciotto, Rebeca Din-Dzietham

Research output: Contribution to journalArticle

33 Scopus citations


Comparisons of infant, perinatal, or neonatal mortality across populations with different birthweight or gestational age distributions are problematic. Summary measures with adjustment for birthweight or gestational age frequently are invalid or lack interpretability. We propose a percentile- based method of standardization for comparing infant, perinatal, or neonatal mortality across populations that have different distributions of birthweight and/or gestational age. The underlying concept is a simple one: comparable health for two population groups will be expressed as equal rates of disease or mortality at equal quantiles in the two distributions of birthweight or gestational age. We describe this method mathematically and present an example comparing mortality rates for African-American vs European-American infants in North Carolina. When gestational age is transformed to its rank, the well-known crossover in mortality rates, in which preterm African- American infants die at lower rates but term infants at higher rates, disappears: African-Americans show higher mortality rates at any percentile of gestational age. With homogeneous mortality rate ratios, a summary star st c becomes meaningful. We also demonstrate adjustment for percentile- transformed gestational age or birthweight in multiple logistic regression models. Percentile standardization is easily implemented, has advantages over other methods of internal standardization such as that of Wilcox and Russell, and communicates an intuitive public health-based concept of equality of mortality across populations.

Original languageEnglish (US)
Pages (from-to)61-67
Number of pages7
Issue number1
StatePublished - Jan 1998
Externally publishedYes



  • African-Americans
  • Birthweight
  • Epidemiologic methods
  • Infant mortality
  • Nonparametrics
  • Standardization

ASJC Scopus subject areas

  • Epidemiology

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