Prepregnancy body mass index, vaginal inflammation, and the racial disparity in preterm birth

Am J Epidemiol. 2006 Mar 1;163(5):459-66. doi: 10.1093/aje/kwj053. Epub 2006 Jan 4.

Abstract

The authors sought to quantify the overall and race/ethnic-specific relations between prepregnancy body mass index and both preterm birth and vaginal inflammation. Data from a cohort of 11,392 women who enrolled in the multicenter Vaginal Infections and Prematurity Study (1984-1989) at 23-26 weeks' gestation were used. Compared with a prepregnancy body mass index of 22, a body mass index of 16 increased the risk of preterm birth by 90% (odds ratio = 1.9, 95% confidence interval (CI): 1.5, 2.6), and a body mass index of 18 increased the risk by 40% (odds ratio = 1.4, 95% CI: 1.2, 1.7). Ethnicity substantially modified the magnitude of the body mass index effect and the shape of the preterm birth risk curve, with underweight having a greater impact on preterm birth among Blacks and Hispanics than among Whites. Low body mass index increased the risk of a high level of neutrophils (> 5 per oil immersion field) and a high vaginal pH measurement (> or = 5.0) among Black women; for a body mass index of 16 versus 22, the odds ratio = 1.7 (95% CI: 1.1, 2.6). Compared with Black women with a body mass index of 22, Blacks with a body mass index of 16 had a 1.7-fold increased risk for a high level of neutrophils and a high vaginal pH measurement, while those with a body mass index of 18 had a 1.3-fold increased risk.

Publication types

  • Comparative Study
  • Multicenter Study
  • Research Support, N.I.H., Extramural

MeSH terms

  • Adolescent
  • Adult
  • Black or African American*
  • Body Mass Index*
  • Female
  • Gestational Age
  • Hispanic or Latino*
  • Humans
  • Incidence
  • Infant, Newborn
  • Odds Ratio
  • Pregnancy
  • Premature Birth / ethnology*
  • Premature Birth / etiology
  • Retrospective Studies
  • Risk Factors
  • United States / epidemiology
  • Vaginitis / complications*
  • Vaginitis / ethnology
  • White People*