Investigating factors affecting the gap between actual and ideal fertility of women in Tehran

During the past few decades, the decline of fertility in Iran has been a widespread phenomenon, and Tehran had the lowest low fertility in 2019. Understanding the gap between women's actual and ideal fertility is important because it focuses on the reasons why women are unable to achieve their desired number of children. In addition, it has implications for policy and program interventions related to family planning. This article examines the gap between actual and ideal fertility among married women of 15-49 years old in Tehran and the factors that affect it. the sample consists of 398 married women aged 15-49.  The results showed that the average total fertility for women in this study was 1.58 children, which indicates a lower than the replacement fertility rate. The average ideal fertility for the studied women is 1.95 children. According to the fertility gap classification, 38.6% of women have underachieved fertility, 37.8% have achieved fertility and 23.3% have overachieved fertility. The results of bivariate tests showed that the variables of age, age at first marriage, activity status, education and type of occupation of women were significantly related to their actual and ideal fertility gap. There is a significant relationship between total religiosity and the two Belief and experimental dimensions of religiosity with the fertility gap. With the rise of total family values and modern values shifts the gap between women's actual fertility and their ideal fertility. The results of Multiple logistic regression showed that the age variable and modern values significantly predict the probability of individuals being in the underachieved group. With the increase of age decreases the probability of belonging to the overachieved group, and with the increase of traditional values and empirical empirical religiosity increases the possibility of belonging to the overachieved group. The coefficient of determination of the model indicates that the regression model explains 33% of the changes in the fertility gap variable.