A Cross Sectional Study of Iranian Women and Sex Preference for Children

Background: Children sex preferences may have significant effects in fertility behavior which is an influential component of population dynamics and could control the population size, structure, and composition. One of the core concerns of researches and policy makers is to study these determinants.Objectives: The main objective of this study is to investigate Iranian women’s sex preference and its highly influential factors through applying Classification & Regression Trees algorithm as a practical classification method.Materials: A cross-sectional study during 2014 was conducted to collect demographical data of 1250 Iranian women in age 15-49. To classify sex preferences for children, age, educational level, place of residence, and difference number of siblings for women, were nominated as predictors.Results: 71 percentages of women’s sex preference have been classified correctly (the accuracy of the model=0.71). In extracted decision tree, women's age, educational level and difference number of siblings were significant. One of the vital results indicated that educated Iranian women in different age cohorts are in favor of having girls.Conclusions: Classification & Regression Trees is an effective and easy to interpret non-parametric method which builds classification tree for predicting dependent variables

Parent-employment conflict analysis by ordinal regression: a case study of employed parents in Tehran

Background: Addressing the evolving dynamics of family structures, the parent-employment conflict (PEC) emerges as a significant conundrum of the current century. This article seeks to delve into the intricate factors influencing PEC among employed parents in Tehran, Iran. Methods: This study employed a stratified random sampling method across various regions within Tehran province, in 2017. A structured questionnaire, encompassing demographic details, the history of fertility, and attitudes towards childbearing, alongside the delineation of conflicts between professional responsibilities and parental duties used to collect 449 employed parents. Since PEC was an ordinal variable with three categories of low (6-12), middle (12-18), and high (18-30), an ordinal regression method was applied to some selected covariates. Results: The findings suggest that women comparing to men, those with “secondary and high school” and “diploma” comparing to “master degree and PhD” educational levels, governmental employees comparing to free-lance employees, and those employees working 45 hours and more comparing to employees working less than 40 hours in a week had higher PEC. Conclusion: In general, unless socialization norms and policymakers’ views adopt social realities, PEC will not reduce. Policymakers should pay more attention to institutionalize of social supports and implement family supportive policies

Determinants of Iranian youths’ marriage age: A parametric survival analysis approach

  Background: Early and delayed marriage has their own effects on mothers and their children's health and social dimensions. Nowadays, Iran experiences delayed marriage due to several factors; thus, the present study was concocted to investigate the factors affecting youths’ marriage age, and to compare these factors between males and females.  Methods: To study demographic, socio-economical, and some atitudinal behavior factors affecting the age of marriage, in the current cross-sectional study, 12741 Iranian pre-married youths including 6381 males and 6360 females from all provinces were selected using multi-stage stratified method and the data was collected using a structured questionnaire in 2014. The questionnaire included demographic, socio-economical, and some atitudinal behavior questions about childbearing. Kaplan-Meier, Log-Rank test, and parametric survival analysis were applied in IBM SPSS Statistics for Windows, Version 22.0., and SAS 9.3 software.     Results: Gamma and Log Logistic parametric models were the best fitted models for females’ and males’ marriage age, respectively. Females and males who lived in provinces with TFR<2 were married α=0.03 (95%CI=0.02_-0.05) and α=0.05 (95%CI=0.04_0.06) times later than those who lived in provinces with TFR 2, respectively. Rural females and males married α=-0.06 (95%CI=-0.08_-0.03) and -0.02 (95%CI=-0.06_-0.03) times sooner than urban ones, respectively. As educational level, the number of siblings, and income increased, the youths’ marriage age increased (P<0.05). Employed youths also married later compared with unemployed ones.  Conclusion: Young females and males had the same factors influencing their marriage age

Application of classification tree approach to analysis youth marriage age gap

Background: During the last decades, the average gap between attitudinal and behavioral youths’ marriage age has increased due to the changes in Iranian society and family patterns. This paper is devoted to studying this increment.   Methods: Classification and Regression Trees (CART) are applied for modeling the marriage age gap (MAG) of 12741 youths selected by a multi-stage cluster sampling method from 31 provinces in Iran.     Results: Classification accuracies of fitted CART for females’ and males’ MAG were equal to .62 and .60, respectively. The most influential variables on females' and males' MAG were educational level and the number of siblings, respectively. Females with "university education," "diploma and less education with 5 and more siblings", and “employed diploma and less education with 3 or 4 siblings" married later than their desired time. Males with "3 and more siblings", "employed with 2 and fewer siblings and 3 and more ideal number of children", "employed university educated with 2 and fewer siblings and 1 or 2 ideal number of children", and " employed with 2 and fewer siblings and 1 or 2 ideal number of children with a diploma and less education and negative opinion towards childbearing" also married later than their desired time.    Conclusion: If the inevitable experience of modernity doesn’t combine with the convenient policy and the economic and socio-cultural conditions of the community don’t change, the negative consequences of such developments would be more than its positive achievements on different social issues especially and more importantly youth’s marriage age

Socio-economic factors of value of children affecting ideal number of children by gender

  Background: Socio-economic factors, following psychological factors, affect the value of children in parents’ view and this value itself could influence Ideal Number of Children (INC), which is one of the most important dimensions of fertility behavior. The aim of the present study was to investigate parents’ INC according to the factors influencing the value of children from the viewpoint of men and women, separately.  Methods: In a cross-sectional study, multi-stage stratified sampling method was conducted to collect data from 590 males and 610 females in Tehran province, Iran, using a questionnaire including demographic and attitudinal questions. To describe data, SPSS-17, and to examine the factors influencing INC, path analysis was used in AMOS 22 and Goodness of fitted model was approved using the relative chi-square ( , Goodness of Fit Index (GFI), Adjusted GFI (AGFI), and Root Mean Square Error of Approximation (RMSEA) indices.   Results: Indices of Goodness of fit confirmed the fitted models ( =2.289, GFI=0.994, AGFI=0.973, and RMSEA=0.047 for males’ model and =0.511, GFI=0.989, AGFI=0.994, and RMSEA=0.020 for females’ model). Negative psychological (males’ coefficient=-0.20 and females’ coefficient=-0.17, P<0.001) and positive economic (males’ coefficient=0.11 and females’ coefficient=0.09, P<0.05) factors of children values were both significant on INC based on gender. Moreover, negative social factor (males’ coefficient=-0.26, P<0.05) of value of children was significant on INC only for males. These significant factors had higher impacts on men's INC, as compared with that of women  Conclusion: According to the results of the present study, significant factors influencing INC of males and females were negative psychological and positive economic factors of the value of children and the negative social factor of value of children was the only significant factor influencing INC for males

Comparing the number of children ever born (CEB) of rural and urban migrant women to Tehran by regression tree model

Background & Objective: Migration, in any forms and by any motivations or outcomes, as a demographic phenomenon, has various cultural and socio-economic effects on local, regional, national and international levels. On the other hand, fertility plays an important role in health and population studies and researchers have examined its changes and trends in various aspects. The aim of this research was modeling the mean number of children ever born (CEB) for women who have left their cities or villages and migrated to Tehran city using regression tree model. Methods: Data was obtained from 2% of raw data from the census of 2011 and analyzed by regression tree model. Tree models are nonparametric statistical techniques which do not need complicated and unreachable assumptions of traditional parametric ones and have a considerable accuracy of modeling. These models are associated with simple interpretation of results. Therefore, they have been used by researches in many fields such as social sciences. Results: Age, educational level, job status, cause of migration, internet use for urban migrant women and age for rural migrant women were assumed as influential covariates in predicting the mean number of CEB. Conclusion: Regression tree findings revealed that urban migrants who were in higher age groups, lower educational levels, unemployed and have not used internet have had more mean number of CEBs

Analysis of Birth Spacing Using Frailty Models

Background and objectives: Birth spacing is an important variable for identification of fertility acceleration, total fertility rate, and maternal and fetal health. Therefore, special attention has been paid to this issue by researchers in the fields of medical sciences, health, and population. In addition, proper analysis of this concept is of foremost importance. Application of classical analytical techniques with no attention to their assumptions (e.g., independence of events) is associated with inefficient results. As such, this study aimed to present frailty models as effective models for this analysis. Methods: Frailty models consider the dependence between unobserved intervals and dispersions by exerting a random impact on the model. Different types of these models include shared, conditional, correlated and time-dependent frailty, each of which along with their applications were presented in the current research using two examples. Results: In practice, the shared frailty model is highly applied due to its simplicity. Nevertheless, since most of the unknown factors affecting the birth spacing are not common between different births, the shared frailty models must be used with caution. Conclusion: Use of classical statistical methods, such as the Cox proportional hazards model, the important assumption of which is the dependence of events occurred, is not appropriate for the accurate analysis of birth spacing. On the other hand, frailty models consider the correlation between the intervals and are an effective method for analysis of birth spacing, use of which is recommended to researchers in fields of medicine and population

Classification the Number of Children Ever Born using CART Model

Background and Objective: Discriminant analysis and logistic regression are classical methods for classifying data in several studies. However, these models do not lead in valid results due to not meeting all necessary assumptions. The purpose of this study was to classify the number of Children Ever Born (CEB) using decision tree model in order to present an efficient method to classify demographic data. Methods: In the present study, CART tree model with Gini splitting rule was fitted to classify the number of CEB in fertility behavior of at least once married 15-49 year-old women, in Semnan-2012. 405 women aged 15-49 years old comprised the survey sample. Results: Women in first and second birth cohorts who had married at an early age had 3 CEB while women who had married at an older age had 2 CEB. Women in third birth cohort who had married at an early age and were employed, had 2 CEB while unemployed women in this cohort whose type of marriages were familial and non-familial had 0 and 1 CEB respectively. Women in the third birth cohort who were married in older age had 1 CEB. Conclusion: Among important advantages of CART model are the simplicity in interpretation, using distribution-free measures, considering missing data and outliers for construction trees which has increased the usage of this method. Therefore, this method is a suitable way for classifying demographic data in comparison to other classical modeling methods in the conditions that necessary assumptions are not met

Predicting children\'s affective temperament indices according to parental affective temperament: An intergenerational study

Intergenerational transmission is referred to transmission of behaviors, characteristics, and/or tendencies from one generation to the other. In this process, parents of one generation tend to repeat some of their psychological characteristics in their offsprings. The aim of the current study was to predict children’s affective temperament indices based on parental affective temperament characteristics. A total of 207 university students (146 females, 56 males, 5 anonymous) and their parents (207 Fathers, 207 mothers) in Tehran have been collected using convenience sampling method. Participants were asked to complete Positive and Negative Emotionality Scale (PNES). Method of the present descriptive study was correlational. Analysis of the data involved both descriptive and inferential statistics including means, standard deviations, correlation, and mixed model. The results showed a significant correlation between parental and children's affective temperament indices (p<0.001). The results of mixed model revealed that parental affective temperament characteristics had the ability to predict children's affective temperament indices implying intergenerational transmission of positive and negative emotionality from parents to children (p<0.001). Based on the results of the present study, it can be concluded that affective temperament characteristics can be transmitted from one generation to the other. Recognition of the intergenerational mechanisms not only predicts affective temperament characteristics of the next generation but also can prevent damaging features to be transmitted. It can be done by improving healthy characteristics performing educational-interventional programs

Factors Affecting Unplanned Pregnancy in Semnan Province, Iran

Background & aim: Despite the success of family planning programs in Iran in the recent decades, considerable proportions of pregnancies are still unintended and can be a cause of poor mental and physical health of the mother and child. The aim of this study was to investigate some important factors affecting uplanned pregnancies among married women in Semnan province, one of the developed provinces of Iran with below replacement fertility level. Methods: The data for this study were drawn from a cross-sectional survey conducted in Semnan province in 2014. A total of 363 married women within the age range of 15-49 years who were pregnant or had the history of at least one delivery were considered. The study sample was selected using multi-stage stratified sampling method. The data were collected using a self-structured questionnaire with 90 items and Cronbach's alpha coefficient of 0.88. Data analysis was performed in SPSS (version 20) using Crammer’s V coefficients and Chi-square tests. Logistic regression analysis was also applied to model the risk of unintended pregnancies based on selected covariates. Results: According to the results, around 18.2% of the pregnancies were unplanned, 7.7% and 10.5% of which were mistimed and unwanted, respectively. Based on the logistic regression analysis, birth cohort, number of children ever born, and contraceptive methods had significant effects on the risk of unintended pregnancies. Furthermore, about 48% of the women experiencing unintended pregnancy were using a traditional contraceptive method before or at the time of the conception.   Conclusion: As the findings indicated, the women who used contraceptive method, as well as those with higher number of children and younger birth cohorts had higher risk of unplanned pregnancies. It should be noted that the majority of unplanned pregnancies among the women in younger birth cohort were mistimed pregnancies. So it is recommended to continue offering family planning and health services to these women in order to prevent unplanned pregnancy, unsafe abortion, and many chronic diseases