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Determination of maternal risk factors of preterm delivery: adjusted for sparse data bias; results from a population-based case-control study in Iran

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ObjectiveTo determine the maternal risk factors associated with preterm delivery in Iran. MethodsA population-based case-control study was conducted including 48 women having preterm delivery (case group) and100 women having term delivery (control group) between March 2007 and March 2012 in the maternity hospitals ofthe Selseleh County, Lorestan province, Iran. Information regarding maternal risk factors was collected by structuredinterview and reviewing the medical records. The maternal risk factors associated with preterm delivery wereidentified using univariate and multivariable logistic regression analysis after adjusting the sparse data bias. The areaunder the receiver operating characteristic (ROC) curves was estimated to evaluate the discrimination power of thestatistical models. ResultsMultivariable analysis demonstrated that multiparty (odds ratio [OR], 14.23; 95% confidence interval [CI], 1.60–127.05),history of gestational diabetes (OR, 0.10; 95% CI, 0.01–0.99), thyroid dysfunction (OR, 97.32; 95% CI, 5.78–1,637.80),urinary tract infection (OR, 16.60; 95% CI, 3.20–85.92), and taking care during pregnancy (OR, 0.12; 95% CI, 0.03–0.50)had significant impact on preterm delivery after adjusting the potential confounders. The area under the ROC curvefor the aforementioned maternal risk factors was 0.86 (95% CI, 0.80–0.92). ConclusionOur study provides evidence for the associations between multiparty, history of gestational diabetes, thyroiddysfunction, urinary tract infection, as well as taking care during pregnancy, and preterm delivery.

Abstract

ObjectiveTo determine the maternal risk factors associated with preterm delivery in Iran. MethodsA population-based case-control study was conducted including 48 women having preterm delivery (case group) and100 women having term delivery (control group) between March 2007 and March 2012 in the maternity hospitals ofthe Selseleh County, Lorestan province, Iran. Information regarding maternal risk factors was collected by structuredinterview and reviewing the medical records. The maternal risk factors associated with preterm delivery wereidentified using univariate and multivariable logistic regression analysis after adjusting the sparse data bias. The areaunder the receiver operating characteristic (ROC) curves was estimated to evaluate the discrimination power of thestatistical models. ResultsMultivariable analysis demonstrated that multiparty (odds ratio [OR], 14.23; 95% confidence interval [CI], 1.60–127.05),history of gestational diabetes (OR, 0.10; 95% CI, 0.01–0.99), thyroid dysfunction (OR, 97.32; 95% CI, 5.78–1,637.80),urinary tract infection (OR, 16.60; 95% CI, 3.20–85.92), and taking care during pregnancy (OR, 0.12; 95% CI, 0.03–0.50)had significant impact on preterm delivery after adjusting the potential confounders. The area under the ROC curvefor the aforementioned maternal risk factors was 0.86 (95% CI, 0.80–0.92). ConclusionOur study provides evidence for the associations between multiparty, history of gestational diabetes, thyroiddysfunction, urinary tract infection, as well as taking care during pregnancy, and preterm delivery.

참고문헌 (39)

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