Fertility Motivations and Its Related Factors in Women of Reproductive Age Attended Health Centers in Sabzevar, Iran

Document Type: Original Research Article

Authors

1 Lecturer of Midwifery, neyshabur University of Medical Sciences, Neyshabur, Iran

2 Midwifery student, Faculty of Nursing and Midwifery, Sabzevar University of Medical Sciences, Sabzevar, Iran

3 Master of Social Welfare, Sabzevar University of Medical Sciences, Sabzevar, Iran

Abstract

Background & aim: The severe reduced fertility rate and growing increase of older population in Iran have led to economic and social consequences in the country. Therefore, the purpose of this study was to investigate the fertility motivations and some of its related factors in women of reproductive age referring to urban health centers.
Methods: This cross-sectional study was performed on 450 women. The population consisted of fertile women within the age range of 18- 35 years referring to urban health centers of Sabzevar, Iran in 2016, who were selected by cluster sampling. Data collection tools included demographic and Miller’s Childbearing Questionnaire. Data analysis was performed in SPSS (version 22) using descriptive statistics, Pearson correlation test, Spearman correlation test, the Kruskal Wallis, and regression test.
Results: The means of positive and negative fertility motivation were 22.64±0.33 and 17.1±3.85, respectively. There was a significant negative correlation between positive fertility motivation with educational level (P=0.01), as well as negative fertility motivation with income level (P=0.001). Moreover, positive fertility motivation correlate positively with age (P=0.01), number of pregnancies, childbirth and children (P=0.001). There was a significant relationship among child gender, accommodation, and spouse occupation (P=0.01).
Conclusion: The results of this study showed that factors including age, educational level, number of pregnancies and children, income level, spouse occupation and accommodation can affect fertility motivation. It is suggested that population policies can increase fertility rate by enhancing fertility motivations.

Keywords

Main Subjects


Introduction


Recent demographic changes have led to the unprecedented reduction in the rate of fertility in all regions of world. Iran has experienced a steep drop in fertility. There has been a reduction of more than 50% in the rate of fertility not only unique among Muslim countries, such as Iran, but also all over the world (1). The Censuses and statistics of Iran indicated that the total fertility rate reached 1.2 in 2011 from 6.3 children per woman in 1986 (2). According to the World Bank, the population growth of Iran will become less than 1% in 2025, and the Iranian population will decrease to 0.99% in 2025 (3). Recent UN reports are also warning; and according to the low population growth scenario of the UN in 2010, if Iran continues to pursue a demographic substitution and does not plan to balance it, it will experience a population of 31 million in the next 80 years with 47% of the elderly people over the age of 60 (4). A rapid decline in fertility rate, as well as altering the balance of age pyramid, can cause irreparable economic and social damages to Iran (5). Therefore, the decline of tendency towards childbearing is now an important social issue which should be solved in Iran (3).

From a demographic perspective, fertility is the most important determinant of population fluctuations (gender and age structures of population); therefore, the investigation of fertility is more important than other demographic phenomena (death and migration). Fertility can be affected by a variety of cultural, social, and economic factors which certainly affect various societies in different ways (6). Demographic issues are so extensive that cannot be summarized in one specific theory or formula. As a result, population movements have various and contradictory outcomes at different times and places (5). Zhang (2017) emphasized on the tendency to have a son, income status, education level, and number of deliveries as the main factors influencing women’s tendency to fertility in China (7). In a study by Rad et al. (2015) in Tabriz, religious beliefs were reported as the most important factor in the tendency of married women towards fertility (8). Motlagh (2016) also considered age of women, economic problems, and the men’s opposition as the main reasons for the unwillingness to have a child (9).

The women position has also changed due to the changes in the functions of families. Urbanization and higher education of women provide them opportunities to find jobs out of house and help them become independent before and after marriage. Nowadays, women have greater freedom in making decisions about childbearing and child-rearing. Promotion of socio-economic status of women has made them aware of various ways to achieve the birth control by obtaining the necessary knowledge about this issue (10).

According to recent studies, fertility is under the influence of individuals’ choices, as well as social norms, values, and culture (11). Fertility motivation is a complicated issue with cultural, behavioral, and belief roots. It is affected
by changes in the context of demographic transition, as well as economic and social development. Fertility motivations has two dimensions of positive and negative. Positive fertility motivation includes personal reasons of anyone for having children and the fertility enjoyment, birth and childhood, the traditional viewpoint, satisfaction with child rearing, the sense of need and survival, and instrumental values of a child. Negative fertility motivation entails reasons for not having a child, such as fear of being a parent, parental stress, and child care challenges (12, 13).

According to a study conducted by Miller in the US, positive fertility motivation can lead to a higher tendency towards childbearing, the greater number of children, and lower intervals between births (12). Khadivzadeh (2014) also found that there was a positive direct relationship between positive fertility motivation in couples with a tendency to childbearing and ideal number of children (14).

Given the rapid decline in fertility rates of Iran, the prospect of population policy should focus on direct and indirect factors of increasing fertility to overcome the future challenges of the country by determining factors which affect fertility and adopting suitable demographic policies accordingly. Demographic researchers and policymakers face the challenge of fertility development and determinants of fertility behavior for future (6). The present study aimed to investigate childbearing motivations in women referring to the health centers in Sabzevar, Iran, in 2016 and investigate the relationship between fertility motivations and some personal, economic and social factors.

 

Materials and Methods

This cross-sectional study was conducted on 450 women aged 18-35 referring to health centers in Sabzevar in 2016. The sample size was determined through simple regression model. In this study, the correlation coefficient was equal to 0.1 based on similar studies (13, 14), and the sample size was equal to 450 using PASS 11 software. The 95% confidence level, the expected regression coefficient of 1 in sample, the standard deviation of 1 for the independent variable, and the correlation coefficient of 0.1 were the applied parameters in calculating the sample size. After employing two-step cluster method, two centers were randomly selected from the main 7 health centers in Sabzevar. The participants in the study were selected by convenience sampling from each center based on the number of daily visitors. The inclusion criteria of study were Iranian nationality and residency in Sabzevar, being married, and non-pregnant at the time
of the study. The exclusion criteria were
the history of hysterectomy, tubectomy, or vasectomy in a spouse.

The study was performed after obtaining research approval from the Ethics Committee of Sabzevar University of Medical Sciences (IR.MEDSAB.REC.1395.35), Sabzevar, Iran, making the necessary coordination with authorities of selected health centers. Data was collected from the women referring to the selected health centers of Sabzevar for receiving services by considering the inclusion criteria. In line with ethical consideration, the eligible women were informed about the purpose of the study. Furthermore, written informed consent was obtained from all participants. After describing the method of responding to questionnaires, research units were asked to study the questionnaire and select an answer that was closer to their current state. If participants were illiterate or semi-literate, questionnaires were completed through interviews by the researchers.

Data collection tool of this study included an interview form consisting of two sections, namely demographic characteristics and fertility characteristics, as well as Miller’s fertility motivation questionnaire. Miller’s fertility motivation questionnaire includes two dimen-sions, namely positive and negative motivations. Positive motivation has 30 items with the subscales of fertility enjoyment, birth and childhood, traditional viewpoint, satisfaction with child rearing, sense of need and survival, and instrumental values of a child. On the other hand, negative motivation entails 19 items related to the fear of being a parent, parental stress, and child care challenges. This questionnaire is rated on a four-point Likert scale, ranging from completely disagree to strongly agree, scored from 1 to 4, respectively (12). In a study conducted by Khadivzadeh (2014), the reliability of this questionnaire was confirmed by test-retest method (r=0.98) and Cronbach’s alpha (α=0.94) (14). In the present study, the reliability of this tool was also confirmed by test-retest method (r=0.89). The content and face validity of the translated version of the questionnaire was approved by 10 faculty members of Sabzevar University of Medical Sciences. After considering necessary suggestions and modification, the final version of the questionnaire was utilized in this study.

Data was analyzed through statistical SPSS software (version 22) using descriptive statistics, Kolmogorov-Smirnov, Pearson correlation, Spearman, and the Kruskal-Wallis tests. Since the results of correlation were purely descriptive and cannot be used for interpretation, the regression model was used to determine the related factors to fertility motivations. P

 

Results

Table 1 shows some characteristics of research units. As can be seen, the mean age of 26.2 years was for women and 30.2 years for men. Moreover, the mean score for the length of
marriage was 5.9 years. A total of 194 subjects (43%) were living in rented houses. The mean values for the number of children, number of pregnancies, and number of deliveries were 1.4, 1.74, and 1.4, respectively. The mean number of abortion was 0.32. Furthermore, 111 subjects (24.6%) had no children and 118 subjects (34.7%) had both male and female children. Moreover, 221 subjects (64.4%) only mentioned the history of vaginal delivery.

Table 2 presents positive and negative fertility motivations of participating women in this study. The mean score of positive fertility motivation and negative motivation in research units were 22.64 and 17.1, respectively. The results of spearman correlation test indicated that there was a significant negative correlation between education level and the overall score of positive fertility motivations (P=0.01). In this regard, the higher the education level of women, the lower the level of their positive fertility motivations. On the other hand, negative motivation has a significant direct relationship

 

Table 1. Socio-demographic characteristics of women of reproductive age referring to health centers of Sabzevar

Variable

Number

Percentage

Education

Illiterate and elementary school

60

13.3

Elementary school diploma

75

16.7

High school diploma

131

29.1

Associate degree and Bachelor

162

36

Master and PhD

22

4.9

Spouse education

Illiterate and elementary school

67

15

Elementary school diploma

91

20.2

High school diploma

113

25.1

Associate and bachelor degree

131

29.1

Master and PhD

48

10.6

Job

Housewife

308

86.4

School or university student

56

12.4

Employee

67

15

Self employed

19

4.2

Spouse job

Unemployed

5

1.1

School or university student

12

2.7

Employee

114

25.3

Self employed

256

56.9

Worker

63

14

Income

Less than reasonable rate

96

21.3

At a reasonable rate

326

72.4

More than reasonable rate

28

6.2

Child gender

Female

117

34.4

Male

104

30.6

Both genders

118

34.7

 

Table 2. Mean and standard deviation of fertility motivation scores in women of reproductive age referring to health centers of Sabzevar

Fertility motivation

Mean (sd)

Positive motivation

Fertility, birth and childhood enjoyment

21.41 (3.32)

Traditional viewpoint

20.42 (3.50)

Satisfaction with child rearing

21.80 (2.85)

Sense of need and survival

18.07 (3.21)

Instrumental values of a child

31.53 (7.19)

Negative motivation

Fear of being a parent

20.90 (5.07)

Parental stress

21.86 (5.65)

Child care challenges

8.51 (4.09)

 

 

with age, number of deliveries, number of pregnancies and number of children (P<0.05). Accordingly, with the increase in the age
and number of pregnancies and childbirth, individual motivation is decreased.

There was also a significant negative relationship between the number of abortions and the overall score of negative motivations (P=0.02); therefore, an increase in the number of abortions could decrease negative fertility motivations. Moreover, income level correlated negatively with the overall score of negative fertility motivations (P=0.001); accordingly, an increased level of income led to higher negative fertility motivations of research units (Table 3).

The result of the Kruskal-Wallis test indicated that husbands’ jobs were related to negative fertility motivations. As a result, the highest fertility motivation was seen when the husband was unemployed (P=0.01). There was also a relationship between the child’s gender and negative fertility motivations, meaning that the highest negative fertility motivation was seen in a group with both male and female children (P=0.01). Moreover, types of residence associated with negative fertility motivations, so the least negative fertility motivation was reported in participants residing in their own

 

Table 3. Correlation of individual- societal factors with total scores of positive and negative motivations in women of reproductive age referring to health centers of Sabzevar

Variable

Positive motivations

Negative motivations

Age

P=0.75

r=0.01

P=0.01

* r=0.10

Spouse age

P=0.76

r=0.01

P=0.02

* r=0.10

Duration of marriage

P=0.31

r=-0.04

P=0.47

r=0.03

Number of children

P=0.85

r=0.09

P=0.001

* r=0.14

Number of abortions

P=0.95

r=-0.003

P=0.02

* r=-0.09

Number of deliveries

P=0.63

r=0.02

P=0.001

* r=0.16

Education level

P=0.01

* r=-0.11

P=0.50

r=0.03

Spouse’s education level

P=0.28

r=-0.05

P=0.80

r=0.008

Income level

P=0.75

r=0.01

P=0.001

* r=-0.13

*P<0.05

 

 

personal houses (P=0.01).

According to the study on the correlation between components of fertility motivation and both personal and socioeconomic factors, the results of Pearson and Spearman tests indicated that satisfaction with child rearing in the positive fertility motivation dimension has a significant negative relationships with mothers’ age (r=-0.12, P=0.009), spouse age (r=-0.11, P=0.01), duration of marriage (r=-0.15, P=0.008) and number of children (r=-0.10, P=0.003). Furthermore, sense of need and survival in the positive motivation dimension correlated negatively with educational levels of woman (r=-0.11, P=0.01); therefore, an increase in the educational level could decrease the childbearing motivation.

The findings were also indicative of a significant relationships between instrumental values of a child with husbands’ educational level (r=-0.14, P=0.001) and job (P= 0.003). Based on the obtained results, the highest fertility motivation for the instrumental values of a child was seen in lower educational level and unemployment of husbands. Parental stress in negative fertility motivations had a significant direct relationship with number of children (r=0.13, P=0.007); however, it had significant negative relationship with the level of income (r=-0.10, P=0.01).

There was a direct significant relationship between childcare challenges in the negative fertility motivation dimension and number of children (r=0.12, P=0.008), while there was a negative relationship with income level (r=-0.11, P=0.01). Childcare challenges crenelated significantly with job (P=0.013); therefore, the highest negative motivations for childcare challenges were seen in employed women.

The regression analysis method was used
to determine related factors to fertility motivations. In order to control effective variables, all variables and relevant variables (in correlation test) were considered as the independent variables. The two main variables of positive and negative fertility motivations were considered as dependent variables, which were separately included in the linear regression model. Finally, results indicated that studied variables predicted 12% of the variance of positive motivations (R2=0.12). Moreover, educational level and length of marriage were the strongest predictors (P <0.05). The studied variables also predicted 20% of variance of negative motivations (R2=0.20). As shown in table 4, among the investigated variables, income level, age, and number of children were the strongest predictors (P <0.05).


 

 

Table 4. Processed linear regression model for investigating the associated factors with fertility motivations

Fertility motivation

Variable

B**

b*

p-value

R2

Positive motivation

Education level

-1.38

-1.08

0.01

0.12

Term of marriage

-0.46

-0.20

0.02

Negative motivation

Income level

-0.54

0.16

0.001

0.20

Number of children

0.14

0.14

0.005

Age

0.76

0.11

0.01

* Standardized regression coefficient

** Non-standardized regression coefficient

 

 

Discussion


The present study was conducted to investigate fertility motivations and some relevant factors in women of reproductive age referring to health centers of Sabzevar in 2016. The results of the linear regression analysis indicated that among different variables, women’s educational level played a decisive role in explaining changes in positive fertility motivations. Therefore, an increase in women’s educational level reduced the positive fertility motivation, which was consistent with results of studies conducted by Motlagh (2016), Arjmand (2016), Nozaki (2017), and several other studies (9, 11, 14- 17).

Abbasi Shovazi found that education was the only variable that might directly affect the fertility. Admission to the university and increased higher levels of education could affect the fertility indirectly by changing individual attitudes and beliefs, which can led to the delay in childbearing age (17). Furthermore, a higher education could lead to greater participation of women in economic, social, and cultural measures of society and replace a lot of opportunities of child bearing and rearing with other desired daily activities (18). This result was inconsistent with studies by Hosseini (2012) who aimed to assess the fertility of Kurdish women in Mahabad (19). The reason for this discrepancy might be different demographic, cultural and socio-economic characteristics of Kurdish women.

According to results of the linear regression analysis, an increase in age enhances negative fertility motivations of women. The age variable plays an important role in affecting the dependent variable, which is in line with studies by Motlagh, Shovazi, Sennott and Azmoude (9, 17, 20, 21). Given that ages of spouses during pregnancy and childbearing have a major impact on the health of children and mothers, the reluctance of older ages for preventing probable risks can be justified. However, this result is in contrast with the results obtained from a study by Eslamlou (2013), which addressed the attitudes of couples at premarital stage to fertility in 420 couples referring to counseling centers in Urmia. According to this study, the age variable did not make any difference in couples’ fertility attitude in terms of number and gender
of future generation neonates (6). The inconsistency between the results of the above-mentioned research and the current study lies in the fact that these two studies were conducted at different course of time. The former was carried out at the premarital stage, whereas, the latter one was performed after marriage and during pregnancy.

Based on results of the linear regression analysis, the number of children was a predictive factor affecting negative fertility motivations; therefore, an increase in the number of children enhanced negative fertility motivations in women, which was consistent with studies conducted by Hosseini and Begi, as well as Azmoude (11, 21). Shiri conducted a research on demographic-economic factors affecting the reproductive population of 15-49 year-old women working in education district of Tehran and reported that the more the number of children, the more the interest in female fertility, which is in sharp contrast with the results obtained from the current study (18). The reason for this is mainly due to the difference in age range and the recruitment of all research units that could be attributed to the delay of childbearing in women.

There was also a significant negative correlation between the number of abortions and total score of negative fertility motivations, therefore an increase in the number of abortions decrease the negative fertility motivation of individuals. This was consistent with results of the study conducted by Mozaffari study (2014), which addressed
a significant direct relationship between number of abortions and the inclination to fertility (22).

Based on results of the current study, there was a relationship between child gender and negative fertility motivations; therefore, the highest negative fertility motivation was seen in a group with children of both genders. As Motlagh reported (2016), more than two-thirds of women declared the male-female gender seeking as the main reason for desire to have the later children (9). A study performed by Azmoude (2017) also indicated that the inclination to fertility in women with children of both genders was significantly lower than women with children of the same gender (21). According to a study in Nepal, the women’s interest in having children of both genders was an important factor influencing their fertility desire (22).

Accordingly, the couples’ gender preference has been an inseparable public traditional belief in most developed and developing countries. Therefore, obtaining the desired child gender is an important factor in childbearing of different demographic groups (23). Regarding accommodation, the obtained results of this study indicated that there was a relationship between the type of residence and negative fertility motivations; therefore, the lowest negative fertility motivation was seen in residence of personal houses, which was in line with the findings of studies conducted by Motlagh (2016) and Ababulgu (2016). The studies reported that owning a personal house had a significant direct relationship with women’s fertility desires (9, 24).

According to results of a linear regression analysis, an increase in income levels decreased the negative fertility motivations in women; and the income level variable played a decisive role in explaining changes of negative fertility motivations. This result was consistent with studies by Arjmand, Rad, and Acharya (8, 15, 25), but inconsistent with the study carried out by Shiri (2009). As he reported, there was
no significant relationship between fertility motivations of women with income levels. The inconsistency of this research with the present study was probably due to the difference in research population, the financial independence, and diversity of research units in terms of education and income levels (18). Razavizadeh (2015) also conducted a qualitative study in Mashhad indicating that economic concerns of child rearing was a major reason for low number of children according to participants (26).

Accordingly, people with higher socio-economic levels had higher levels of life expectations and standards leading to smaller families by allocating more resources to each child (8). Although children are considered profitable for the future, they impost higher costs on families in their childhood. Consequently, most people decide to have fewer children in spite of their great desire (14). In the present study, there was a significant relationship between fertility negative motivations and female jobs, which was in the same vein with the results of studies performed by Hosseini (2014), Hejazi (2013), and Ghasemi (2014) who reported the lower possibility of childbearing among employed women than unemployed women (10, 11, 27).

Employed women will be always worried about facing the pregnancy since they are stressful about their jobs and being away from the society. In fact, participation in the society is the reason for women’s tendency to have fewer children (13). Employed women spend much time outdoors and in the workplace and are mainly affected by values of modern society, formal relations, and stressful workplaces. In such a situation, costs of childbearing and pregnancy are higher for women (28). The female employment rate is lower in Iran than other industrial countries; therefore, the employment is not a threatening factor for childbearing (29).

This study was conducted in health centers of Sabzevar with patients from different socio-economic levels; however, it was limited to female participants and not their husbands. Accordingly, it is suggested to conduct a study on fertility motivations and its relevant factors in both male and female couples in different regions of Iran and among different ethnic groups with different cultures.

 

Conclusion

The results of this study indicated that age, educational level, number of children, number of pregnancies and delivery, number of abortions, income level, spouse’s occupation, place of residence, having children of both genders, length of marriage, and women’s employment were factors affecting fertility motivations. According to the results, it is suggested to adopt encouraging demographic policies on factors affecting the women fertility in order to increase the rate of fertility in society. Long-term programs seem particularly necessary for increasing employment and entrepreneurship, solving housing problems, removing barriers to marriage at an appropriate age, and providing support for employed women with children.

 

Acknowledgements

The present study was conducted by the financial support of Research Deputy at Sabzevar University of Medical Sciences (Code 94211). Authors would like to thank the Research Council and all personnel of selected health centers in Sabzevar for their cooperation in this research.

 

Conflicts of interest

      The authors declare no conflicts of interest.

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