Relationship between periodontal disease in pregnant women and the nutritional condition of their newborns

J Periodontol. 2002 Oct;73(10):1177-83. doi: 10.1902/jop.2002.73.10.1177.


Background: The purpose of this study was to determine whether maternal periodontal disease (PD) could be associated with the nutritional condition of newborns.

Methods: After controlling for traditional risk factors for premature childbirth and low birth weight, 69 mothers were selected: 13 were periodontally healthy and 56 had varying stages of PD. They and their newborns formed the study population. PD presence and severity were clinically determined using Russell's periodontal index. The nutritional evaluation of the newborns was determined by Lubchenco's modified growth patterns.

Results: A decrease in the average newborn's weight and gestational age was observed as the mother's level of PD increased. Correlation analysis demonstrated a highly significant clinical relationship between more severe PD and lower birth weight (r = -0.49; P < 0.01); a highly significant relationship was also clinically demonstrated between increasing PD severity and decreasing gestational age of the newborn babies (r = -0.59; P < 0.01). There were significant differences in the weight and gestational age of the newborns of mothers with PD.

Conclusions: These data suggest that PD in pregnant women could be a clinically significant risk factor for preterm deliveries and low birth weight. There was considerable variability in the results, and these preliminary findings need to be confirmed in larger studies.

MeSH terms

  • Adolescent
  • Adult
  • Analysis of Variance
  • Birth Weight
  • Case-Control Studies
  • Female
  • Gestational Age
  • Gram-Negative Bacterial Infections* / complications
  • Humans
  • Infant, Low Birth Weight
  • Infant, Newborn
  • Maternal Age
  • Obstetric Labor, Premature / etiology
  • Periodontal Diseases* / complications
  • Periodontal Index
  • Pregnancy
  • Pregnancy Complications, Infectious*
  • Prenatal Nutritional Physiological Phenomena*
  • Regression Analysis
  • Risk Factors
  • Statistics, Nonparametric