Objective: To determine the association between periodontal disease and low birth weight among pregnant women.

Methods: Data for this case-control study was collected from June 2019 till February 2020. All women in the Gynecology Department of Lady Willingdon Hospital, Lahore, who had delivered a baby within the last 24 h were invited to participate. Women who delivered babies less than 2.5 kg were considered as 'cases' (having low birth weight - LBW - infants) and those having babies of 2.5 kg or more were categorized as 'controls' (normal birth weight infants). The selected sample was matched for age, general health (indicated by mean upper arm circumference) and Hemoglobin levels. Intraoral examination was conducted and gingival color and appearance; calculus, bleeding on probing, CPITN (Community Periodontal Index of Treatment Needs) and CAL (clinical attachment loss) were recorded. A binary logistic regression analysis was conducted to determine the predictors of LBW infants. The predictors were further confirmed by applying chi-squared test for categorical variables and independent sample T test for quantitative variables.

Results: A total of 60 cases and 120 controls were recruited. The logistic regression model suggested that CPITN score (OR 14.893, 95% CI 4.896, 45.301); CAL (OR 2.148, 95% CI 1.271, 3.631); calculus (OR 25.099, 95% CI 1.916, 328.771); mode of delivery (OR 0.175 95% CI 0.060, 0.514); and gingival recession (OR 0.237, 95% CI 0.078, 0.715) were significant predictors of LBW.

Conclusion: Periodontal disease was found to be a significant predictor of LBW infants.

Download full-text PDF

Source
http://dx.doi.org/10.1007/s10995-023-03620-9DOI Listing

Publication Analysis

Top Keywords

birth weight
16
periodontal disease
12
low birth
12
lbw infants
12
association periodontal
8
disease low
8
weight infants
8
babies 25 kg
8
logistic regression
8
infants
5

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!