Key words: low birth weight, maternal smoking, newborn, pregnancy, risk factorsIntroduction. 15 to 25% of women smoke during pregnancy. Scientific evidence suggests that exposure to smoking causes decreased birth weight. The aim of this study was to assess the correlation between smoking during pregnancy, maternal sociodemographic characteristics, and low birth weight.Methods. Data were derived from 1572 questionnaires administered to each woman that gave birth at the Gynecology Teaching Hospital "S. Anna" in Turin (Italy) during the period from 2008 to 2010. Multiple logistic analysis was used to evaluate the association between socio-demographic characteristics and birth weight; the stepwise approach with a "backward elimination" procedure was followed, and the goodness of fit of the model was estimated using the Hosmer-Lemeshow test.Results. The univariate analysis revealed that smoking cigarettes (17%), having a lower educational level (13%), and female sex of the infant (13%) seem to be risk factors, as they increase the risk of having a low birth weight child. Logistic regression analysis showed that gestational age and maternal smoking are the statistically associated variables. Conclusions.The results confirmed that birth weight increases proportionally with the length of the gestational age and that maternal smoking and the child's sex (female) increase the risk of having a lower birth weight. Logistic regression demonstrated that the association between maternal smoking and low birth weight shows an increased risk for the whole population (OR=2.85), for male (OR=3.45) and for female newborns (OR=2.44). (RO = 2,85), tako za novorojenčke moškega (RO = 3,45) kot tudi ženskega spola (RO = 2,44). IZVLEČEK
Introduction: The Appropriateness Evaluation Protocol (AEP) is a widely used assessment tool that identifies and measures the inappropriateness variables of hospital healthcare related to unjustified admission and/or length of stay, however it does not apply specifically to gynaecology or obstetrics wards. Objectives of the study: The main objectives of the present study were to develop a new tool for the evaluation of the appropriateness of admission and hospital stay in obstetric settings; as well as to analyze the main determinants of inappropriate admission and days of hospital stay within all the units of the Pediatric Hospital “Regina Margherita” and the Obstetrics and Gynaecology Teaching Hospital “S.Anna” in Turin. Methods: A multidisciplinary team of reviewers, composed of gynaecologists, paediatricians and obstetricians, was established and the appropriateness evaluation criteria, the operational handbook and the plan were all defined. Data were collected during the period between September and December 2005 and then put in an ad hoc database. Data analysis and evaluation were performed by univariate analysis (chisquare test) and multivariate analysis using a multiple logistic regression model. The level of significance was set at p<0.05. Results: Out of 734 clinical records, 598 were considered for the study. The prevalence of inappropriateness of admission was 3.34%. The total number of examined days was 2888, 801 of which (27.74%) were considered to be inappropriate. The variables “place of residence” (÷²=6.272; p=0.0435) and “type of admission” (÷²=14.223; p<0.001) were significantly associated with the inappropriateness of the admission. Between the 2nd and the 8th day of hospital stay the percentage of inappropriate days exponentially increased (up to 56%). With regards to the quality of the clinical records almost all of them were characterized by the presence of anamnesis, objective exams, discharge letters, clinical diary entries and the signature of the responsible healthcare professional. Objective examination was often incomplete or partially complete or absent. Conclusions: The proposed Obstetric AEP was demonstrated to be useful for the evaluation of the appropriateness of obstetric admissions and hospital stays, as well as the determinants for when these were inappropriate. This specific tool, in the future, could be used to monitor hospital usage and the allocation of resources related to this health care area
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