Vol 2 No 4 (2016)

Original Article(s)

  • XML | PDF | downloads: 193 | views: 270 | pages: 158-163

    Back ground & Aim: Recently, early growth patterns have been associated with metabolic and cardiovascular diseases in adulthood. Early child development depends on women’s health. Lack of maternal health during pregnancy can lead to death, disease, and disability in the newborn baby. This research was conducted to study the effect of maternal weight gain during pregnancy on the children’s growth until 6 months of age.
    Methods & Materials: This retrospective cohort study was conducted on a sample of  257 mother/child pairs using the household records of the urbane health center of Amirieh in Shahriar County. Health care records of pregnant women were collected, and their children’s weight was measured at birth and 6 months of age. Multiple linear regressions were used to estimate the adjusted association between maternal and infant weight gain from birth to 6 months of life.
    Results: According to multiple analysis, there was no statistically significant and clinically important association between the infant weight gain and gestational weight gain [b = 3.8; 95% confidence interval (CI): −20.8, 28.5; P = 0.076]. Gestational weight gain, however, showed a significant association with birth weight (b = 16.34; 95% CI: 3.4, 29.3; P = 0.014).
    Conclusion: In this study, there was no association between gestational weight gain and infant weight gain from birth to 6 months. It seems that further studies with larger sample sizes and variables can help us to understand the maternal factors affecting early infant growth. 

  • XML | PDF | downloads: 163 | views: 241 | pages: 164-172

    Background & Aim: In multivariate receiver operating characteristic (MROC) curve analysis, comparing two tests is usually done by means of area under the curve (AUC’s) and sensitivities. However, the existing procedures have not addressed the issue of comparing two MROC curves when they cross each other.
    Methods & Materials: A modified version of AUC (mAUC) under MROC setup is proposed to address the above-mentioned problem. It is also shown that mAUC performs better than AUC. The performance of mAUC in the aspect of crossover curves is supported by a real dataset and simulation studies at different sample sizes.
    Results: Two real datasets, namely, Intra Uterine Growth Restricted Fetal Doppler Study (IUGRFDS) and Indian liver patient (ILP) datasets are used and apart from these simulation studies are also carried out to observe the effect of sample size. These mAUC’s are then compared with each other to show that difference exists between two curves while comparing AUC’s cannot identify the true difference existing between them. With respect to IUGRFDS dataset, MROC curves of the diagnostic procedures middle cerebral artery and cerebroplacental ratio cross each other and are found to be similar when their AUC’s and mAUC’s are compared. In ILP dataset, the extent of correct classification achieved in the case of males is shown to be better than that of females when mAUC’s at 0.5 and 0.8 are compared.
    Conclusion: It is observed that the mAUC’s are competent in identifying the true difference between the crossover MROC curves when the sample size is adequate, and the λ values are 0.5 and 0.8 but not 0.3.

  • XML | PDF | downloads: 234 | views: 476 | pages: 173-179

    Background & Aim: Nowadays, we have some data in different sciences which number of zeros is more than expected, such data are called zero-inflated which can be modeled by regressions for count data. Many researches have been conducted in the field of classical method on count data. Most of Bayesian analysis which is conducted for these data used zero-inflated Poisson regression. Therefore, the main purpose of this research is comparison of Bayesian and classic approaches in regression of zero-inflated negative binomial (NB) on data for determining the size estimation of people who have used alcohol more than once in last year.
    Methods & Materials: This research had been in two provinces of Fars and Kerman in 2011, a sample size of each province was formed proportional to people of that province, and totally the calculated sample size was 700. Zero-inflated NB regression was fitted to the data in two Bayesian and classical methods, and then two methods have been compared. Results of Bayesian method were extracted in OpenBUGS software and through related codes in R and results of classical method were extracted in R software too.
    Results: After fitting classical method, variables of province, gender, age groups, and education had been effective on identifying number of alcoholics, but in Bayesian method, three variables of gender, age groups, and education have become significant. In this research, it was specified that obtained probability intervals from Bayesian method are much Widder than classical method.
    Conclusion: Results of this research indicate that Bayesian method has better function than the classic

  • XML | PDF | downloads: 217 | views: 306 | pages: 180-187

    Background & Aim: Considering the psychosocial model of diseases, the aim of this study was to evaluate the effect of psychiatric intervention with regard to demographic and marriage characteristics on the pregnancy rate using Bayesian network model in infertile women.
    Methods & Materials: In a randomized clinical trial, 638 infertile patients
    referred to an infertility clinic were evaluated. Among them, 140 couples with different levels of depression in at least one of the spouses were included in this substudy. These couples were divided randomly into two groups. After psychiatric intervention the clinical pregnancy rates of the two groups. The data were divided into two groups: demographic characteristics and marriage specifications, and by drawing Bayesian networks using Grow-Shrink (GS) algorithm, the conditional probability of pregnancy was estimated.
    Results: According to the results, Bayesian network model of the GS algorithm was significant  (P = 0.548) and given that the fertility in the intervention group who were concurrently treated with antiretroviral treatment, the conditional probability was 38.5%, and this amount in the control group is 3.5% and group who were concurrently treated with induction of ovulation or did not receive any treatment the conditional probability was 72.2% and this amount in the control group is 23.1% comparing the values shows the importance of psychiatric intervention in increasing pregnancy rate.
    Conclusion: Results obtained from Bayesian network model are in line with results obtained from logistic model in terms of the significance of the variables with the difference that apart from the graphic structure, Bayesian network model also estimates conditional probabilities. This study shows that psychiatric and psychological treatments play an important role in curing infertility that will increase the chances of pregnancy.

  • XML | PDF | downloads: 221 | views: 302 | pages: 188-198

    Background & Aim: Identification of factors influencing reproductive health-related behavior among adolescent students is an important issue to plan effective intervention. Therefore, this study was aimed to determine the effect of sociodemographic factors on constructs modified theory of planned behavior (TPB) in relation to reproductive health in adolescents.
    Methods & Materials: A cross-sectional study was conducted among 578 female students aged 12-16, recruited through a multistage random cluster sampling method, in Tehran, Iran. A self-administered TPB-based constructed questionnaire was designed and used for data gathering. Multivariate regression analyses were conducted to examine association between family size, number of siblings, birth rank, and family closeness, source of information, and reproductive health behavior.
    Results: The mean age of participants was 14.1 years. None of participants were not obtained a perfect score in relation to reproductive health. In addition, they were achieved scores average less than half the rates. Number of siblings, family size, birth rank, mother education, and information source were factors associated with TPB constructs (P < 0.001).
    Conclusion: The results of this study were emphasized sociodemographic factors can have an effective role in students’ Sexual and reproductive health behaviors.