Analysis of Environmental Exposures for Nonsyndromic Cleft Lip and/or Palate: A Case-Control Study
Abstract
Background: Orofacial cleft is among the most common developmental malformations in humans. This study aimed to identify the relationship between environmental factors and nonsyndromic cleft lip and/or palate (NSCL/P) in Northwest China.
Methods: This case-control study was conducted in Gansu Province, China over two years (Jan. 1, 2017–Jan. 1, 2019). Overall, 600 NSCL/P cases and 660 normal control cases were finally enrolled in the current study. Data were collected by conducting face-to-face interviews with both parents of each case.
Results: Univariate (χ2) analysis revealed 22 factors as being significantly associated with NSCL/P. Multivariate (stepwise logistic regression) analysis identified that 14 factors had statistically significant association with NSCL/P. Male gender (OR=0.789), paternal age at childbirth of 25-29 yr (OR=0.690), and folic acid supplement (OR=0.197) were found to be protective factors against NSCL/P. On the other hand, blood A-type, multiple births, positive family history of NSCLP (OR=6.660), parental consanguinity (OR=6.107), positive abortion history, high or low maternal childbearing age, and maternal passive smoking (OR=4.349), malnutrition (OR=4.431), infections, and drug use (OR=2.188) during early gestation were significant risk factors for NSCL/P.
Conclusion: Parental age at childbirth of 25–29 yr, and folic acid supplement can reduce the risk of NSCL/P. By contrast, maternal passive smoking, infections, and drug use during early gestation period, and multiple births, parental consanguinity, positive family history, and maternal abortion history can increase the risk of NSCL/P. Identification of risk factors is essential in minimizing the incidence of NSCL/P in a particular population.
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Issue | Vol 51 No 3 (2022) | |
Section | Original Article(s) | |
DOI | https://doi.org/10.18502/ijph.v51i3.8934 | |
Keywords | ||
Nonsyndromic cleft lip Etiology Risk factors Case-control study Logistic regression analysis |
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