The Association Between Infertility and Highly Educated Working Women and its Residence-Wise Prevalence: Insights from India

Abstract

Background

At the present time, after giving birth to one or two, couples usually use some method of family planning. But if women are unable to conceive a child, known as infertility, is a medical problem and carries serious demographic, social, as well as health consequences. In the present study, an attempt has been made to study the relationship between infertility and highly educated working women after controlling for certain socioeconomic and demographic variables and efforts have been made to see this difference between urban and rural residing women.

Methods

The information about infertile women is collected from 40,401 currently married women aged 20–35 in India using National Family Health Survey data conducted in 2015-16. Bivariate analysis along with unadjusted and adjusted logistic regression is used to access the relationship of our objective.

Results

Findings of the bivariate analysis revealed that among 40,401 currently married women 3782 (9.4%) women are infertile in India. Out of 3782 infertile women, 1242 (10.7%) reside in urban and 2540 (8.8%) in rural areas. Findings of logistic regression analysis show that women are 20% more likely to be infertile if they are highly educated as well as have a job. When we saw this interaction effect by place of residence, we found that women living in urban areas had a 1.32 (95% CI 1.126–1.876) times increased likelihood of infertility compared with those without this interaction effect whereas rural women had an increased likelihood of infertility by 1.06 (95% CI 1.008–1.536) times. Respondent’s age and overweight were also found to be positively associated factors of infertility in urban as well as rural areas. Although the wealth index is only a potential predictor of infertility in urban areas, its effect on infertility in rural areas is minor.

Conclusions

In India education and wealth index both are increasing day by day. Due to the increasing level of education and other knowledge in society, we observe age at marriage is also increasing particularly in the urban areas, also the intention to have less number of children in the highly educated and higher socio-economic status groups is observed, and this creates another medical burden called infertility which is an emerging issue across the world, especially in India. In fact, Infertility is not only a medical burden but also affects the married life of women. Thus, there is a need to focus on this issue and make people aware of it through various programs.

Background

Infertility is essentially defined as the inability to conceive a baby. Infertility may occur due to male factors, female factors, or a combination of male and female factors or may be unexplained. Infertility is increasing day by day and possible reasons for this may include sexually transmitted infections, coping with stress, lifestyle, job pressure, postponing parenthood, galloping urbanization, Obesity, etc. Infertility is a global health issue affecting millions of people of reproductive age worldwide. Epidemiological and community-based surveys adopted various criteria and time frames to define infertility. Primary infertility is described in English demographic terms as the inability to have children as a result of being unable to conceive or carry a pregnancy to live childbirth. Physicians describe infertility as the inability to conceive following one year of exposure to conception whereas epidemiologists define infertility as the inability to conceive within two years of exposure to conception. However, infertility is redefined by the World Health Organization as the inability to become pregnant after being exposed to conception for one to two years [1]. If you have been pregnant before and had a healthy baby, but now you are unable to get pregnant or carry the baby to term, this is called secondary infertility. Moreover, different studies use different definitions for infertility, making it difficult to compare them directly [2]. A methodical review of national health surveys found that in 2010, about 10.5% of women worldwide suffered from secondary infertility and about 2% from primary infertility [3]. There is a wide variation in the prevalence of secondary infertility, from less than 6% to more than 16% of women worldwide [4]. Most scientists concur that infectious illness, which can result in fallopian tube obstruction, significantly contributes to variation among groups and changes through time. Since the risk of infertility tends to rise with age, differences and changes in the age at childbirth are likely important factors. The World Health Organization (WHO) has classified the various causes of infertility according to the male and female reproductive systems [5]:

Paste Fig. 1 here.

There is relatively little information about specific risk factors and the prevalence of male infertility worldwide [4]. According to the information that is available, 48 million couples and 186 million people worldwide are infertile. Although the ICPD Program of Action emphasizes that services for reproductive health should include infertility prevention and treatment [6], infertility is being given insufficient attention in India's reproductive health program. The number of cases of infertility is increasing rapidly in both developed and developing countries. Infertility in India is estimated at 4–6% by the Census of 1981, with both primary and secondary infertility adding up to 17.9 million [7–8]. In India, the overall prevalence of primary infertility lies between 3.9% and 16.8%, as per WHO estimates [9]. Infertility has a significant negative impact on the lives of infertile spouses. In particular, women are more prone to violence, divorce, social stigma, depression, anxiety, and low self-esteem. In some circumstances, the fear of infertility might prevent both men and women from taking contraception if they feel under societal pressure to demonstrate their fertility at a young age due to a high social value placed on having children [1]. Studies from a few African nations have shown that infertile couples are substantially more likely to experience marital instability, such as separation and divorce [10]. Numerous studies have also shown that childless women are subjected to physical and psychological abuse at the hands of family members [11]. There are psychological effects of infertility among infertile women including anxiety, depression, and suicidal thoughts. However, the reasons for this vary. Infertility has been determined to be the fourth most traumatic life event in a woman's lifetime, after her parent’s death and a partner’s infidelity, which is also significant to mention [12]. In addition to these things, the impact of lifestyle factors on overall health and wellbeing, as well as fertility, has been documented in previous studies [13–14]. Globally, infertility has been shown to be a growing problem that requires immediate attention. In many developing countries, medical facilities are inadequate to address this issue, which makes it all the more important. There have been a few recent studies that attempt to address the issue, but there is still limited information available about the levels, trends, and consequences of infertility, especially in India.

Several earlier articles have studied various aspects of infertility such as the effect of infertility diagnosis on the psychological status of women undergoing fertility treatment in Greece [15], levels and patterns of infertility and childlessness in NFHS-2 (1998–1999) and NFHS-3 (2005–2006) is compared [16], the impact of infertility on a woman’s quality of life in Iran [17], relationship of dietary patterns and morbidities with primary infertility among currently married women aged 20–49 years using NFHS-4 data [18], the prevalence and potential determinants of primary infertility among the currently married women in the reproductive age 15–49 using NFHS-4 data [19], etc. It is true that infertility affects women of all educational levels equally, but those with higher education are more likely to seek medical attention [20–23]. Lack of fertility awareness among young people and women seeking fertility treatment can increase the duration of infertility before seeking medical help and can be prevented with proper education strategies [24]. In the current study, the relationship between infertility and highly educated working women has been studied, after controlling for certain socioeconomic and demographic variables and it has also been attempted to detect which women in rural and urban areas are more likely to experience infertility. This study involved currently married women aged 20–35 and used the fourth round of National Family Health Survey data conducted in India. In order to exclude the effects of adolescent sterility and high age effects, the age groups under 20 and over 35 were excluded from the analysis.

Materials And Methods

Data

The present article is based on data from the 4th round of the National Family Health Survey (NFHS). A large-scale and multi-stage survey, the National Family Health Survey provides information on 640 districts in 36 states and union territories in India. This dataset provides national, state, and district-level information on births, deaths, women’s health, child nutrition, family planning, domestic violence, etc. NFHS-4’s women file has been used in this study. The information about infertile women has been collected from 40,401 currently married women aged 20-35 in India using National Family Health Survey data conducted in 2015-16.

Outcome Variables

The dependent variable for this study is infertile women classified into two parts named yes (coded as 1) and no (coded as 0). This survey did not ask directly about infertility, so the variable infertility is constructed by combining the four variables. The information about infertile women is collected from married women who live with their husbands, whose marital duration is greater than or equal to five years, open birth interval (OBI) greater than or equal to five years, and in this duration not using any contraceptive.

Paste Figure 2 here.  

Study covariates

The background variables selected to show the determining effect of infertile women in the present study are age-group considered in our study is classified into three parts, namely 20–25 years, 25–30 years and 30–35 years, women’s education which is divided into four parts namely no education, primary education, secondary education and higher education, religion is classified into three parts namely Hindu, Muslim and others (Christians, Sikhs, Buddhist/Neo-Buddhist, Jain, Jewish, Parsi/Zoroastrian and others), caste is also divided into three parts namely SC/ST, OBC & others, wealth index is stratified into five parts namely poorest, poorer, middle, richer and richest, Body Mass Index (BMI)  is classified into three parts namely Underweight (<18.5 kg/m²),  Normal weight (18.5-25.0 kg/m²) and Overweight (>25.0 kg/m²), mass-media is divided into two parts namely exposure (reading newspaper/magazine, listening to radio or watching television) and non-exposure and respondent’s currently working is divided into two parts namely Yes and No. So there are eight independent variables that have been considered.

Statistical Analysis

In order to test for associations between a dependent variable and each predictor variable, bivariate analysis, and chi-square tests have been performed on selected background variables. Finally, in order to determine whether these background characteristics are deterministic or not, unadjusted and adjusted logistic regression has been applied. The task of logistic regression analysis is to estimate the log odds of a particular event. The basic form of Logistic function is

This indicated that the log odds of infertility are a linear function of the independent variables. The results of the logistic regression are reported as unadjusted and adjusted odds ratios (ORs) with 95 percent confidence intervals for covariates respectively.

Result

Paste Table1 here.

Table 1 represents the result of the bivariate analysis and chi-square test of infertile women. Among 40,401 currently married 20-35 year age-group women, 3,782 (i.e. 9.4%) women are infertile. Infertile women are further classified according to their place of residence. Among 40,401 currently married 20-35 year age-group women, 11,657 (28.85%) women residing in urban area, in which 1,242 (10.7%) women are infertile and 28,744 (71.15%) women residing in rural area, in which 2,540 (8.8%) women are infertile. In India, among 29.1%, 37.5% and 33.4% currently married women of age-group 20-25, 25-30 and 30-35, 2.9%, 8.4% and 16.0% women are infertile respectively. In urban area, among 24.4%, 38.2% and 37.4% currently married women of age-group 20-25, 25-30 and 30-35, 2.9%, 9.3% and 17.2% women are infertile respectively. In rural area, among 30.9%, 37.3% and 31.8% currently married women of age-group 20-25, 25-30 and 30-35, 2.9%, 8.1% and 15.5% women are infertile respectively. The results of the chi-square test suggest that age is a significant variable in total, rural and urban areas for further study of infertility. Among the total of 40,401 sampled currently married women of higher fertility age 22.1%, 13.4%, 51.6%, and 13.0% women have no education, primary, secondary and higher education respectively, and among each of these educated groups 7.8%, 9.3%, 9.6% and 10.3% women are infertile respectively. In the urban areas, among 11.8% of illetrate women, 6.7% were infertile, 10.3% of primary educated women 8.6% were infertile, 55.0% of secondary educated women 9.3% infertile, and 22.9% highly educated women 9.8% infertile. In the rural areas, among 26.2% no educated women 8.8% infertile, 14.7% primary educated women 10.5% infertile, 50.2% secondary educated women 11.0% infertile, and 8.9% highly educated women 12.7% infertile. Whole India is divided into many religions but here for simplicity, the religion is classified into three major categories (i.e. Hindu, Muslim, and Others). Among the total sample of 40,401 women 77.5%, 11.6%, and 10.9% women belong to Hindu, Muslim, and Other religions respectively. In each of these religious groups 9.3%, 8.8%, and 10.6% of women are infertile. When infertile women are classified according to religion, then according to the classification we can say that the effect of religion on infertility in urban areas is less compared to rural areas. In urban areas, the effect of religion on infertility is insignificant but in rural areas, the effect of religion on infertility is significant. However, when infertile women are classified according to caste, their effect on infertility is significant in the urban area while insignificant in the rural area. As per Census 2011 report, 68.84% of the people in India are living in rural areas and only 31.16% are living in urban areas. Because the majority of India’s population lives in rural areas, the overall effect of caste on infertility is insignificant. Since the wealth status of respondents, much effects on infertility and is found to be significant in both types of places of residence (i.e. rural as well as urban), so the overall effect of wealth status is also significant. BMI (Body Mass Index) is a pertinent indicator of infertility. If women are over weighted then occurs some issue to conceive in comparison to underweight and normal weight. The result of the chi-square test suggests that BMI is also an important differential variable and that its effect on infertility exists in both types of residences. Exposure to mass media is also found to be a significant variable in infertility. Among the total sample of 40,401 currently married women aged 20-35, 19.2% have no mass media exposure and 80.8% have any type of mass media exposure. Among those not exposed to mass media, 8.6% of women experience infertility, while among mass media-exposed women, 9.5% experience infertility. If the exposure to mass media is classified according to a place of residence then the variable is found to be significant in urban areas while it is found to be insignificant in rural areas. Since the percentage of working women in India is not that high but as the education of women is increasing, the percentage of working women is also increasing. Generally, it has been seen that highly educated women are going to get a job. Among the total sample of 40,401 currently married women, 80.4% are not working of which 8.9% of women are infertile and only 19.6% of women are currently working of which 11.4% women are infertile. The result of the chi-square test shows that the current working status of women is found to be significant for determining the infertility condition in urban as well as rural areas.

Paste Table 2 here. 

Table 2 shows the results of unadjusted logistic regression of infertile women in India and by place of residence. Women who are currently aged 25-30 and 30-35 are 3 times and 6 times more likely to experience infertility than women in the 20-25 age group. This covariance has been found to be significant in both rural and urban dwellings. Women who belong to the age group 25-30 and 30-35 are 3 times and approx 7 times more likely to experience infertility in urban, whereas in rural 2 times and 6 times more likely to experience infertility than 20-25 age group women. This result suggests that urban women in the same age group experience more infertility than rural women. The result of unadjusted logistic regression was found to be significant according to education. Women who are primarily educated, secondary educated, and highly educated are 22.3%, 25.6%, and 36.1% more likely to experience infertility than women who have no education. In the urban areas, primary educated women are 29.9%, secondary educated women are 42.1% and highly educated women are a 51.4% higher chance to become infertile than no educated women, whereas, in rural areas, primary educated women are 22.3%, secondary educated women are 29.5% and highly educated women are 51.2% more likely to experience infertility than no educated women. The result of unadjusted logistic regression shows that the effect of religion on infertility as a whole is found to be significant. This covariate is found to be significant in rural areas but not in urban areas. In the rural areas, Muslims are 15% less likely and other religions are 21.6% more likely to experience infertility than Hindus. When caste is considered to be covariant, its effect is found to be opposite to that of religion, meaning that the effect of caste is found to be significant in urban areas, but not in rural areas. Moreover, in the urban areas, other caste women are 20.6% and OBC caste women are 16.2% more likely to experience infertility than SC/ST women.

The results of Table 2 suggest that the wealth status of women is significant in rural as well as urban. With the increase in wealth status of women, the likelihood of experiencing infertility increases. Women who have wealth status poorer, middle, richer, and richest are 13.9%, 19.3%, 34.9%, and 24.3% more likely to experience infertility than the poorest women. Moreover, the effect of an increase in wealth status is greater in urban areas than in rural areas. Women who are underweight are 20% less likely and obese women are 71% more likely to experience infertility compared to normal-weight women. Women who have mass media exposure are 11.5% more likely to experience infertility than women who are not exposed to mass media. According to the result of un-adjusted logistic regression, mass-media exposure was found to be significant only in the urban area, whereas it was insignificant in the rural area. Taking into account the current working status of women, Table 2 shows that women who are currently working are 32.4% more likely to experience infertility than women who are not working, and furthermore, this covariate has been found to be significant in both urban and rural. When we see the interaction effect of higher education and the current working status of women then we found that women who are highly educated as well as currently working are 22.5% more likely to experience infertility than women of other statuses and this interaction effect was found to be significant in both habitat types.

Paste Table 3 here.

Paste Table 4 here.

Table 3 shows the results of adjusted logistic regression of infertile women in India and by place of residence when the current working status of women is not considered in the model while  Table 4 shows the result of adjusted logistic regression of infertile women in India and by place of residence when the current working status of women and the interaction effect of highly educated and currently working status of women are considered in the model after controlling for certain socioeconomic and demographic variables of the model I. Considering age, Table 4 shows that women whose current age belongs to the age group 25-30 and 30-35 are 3 times (95% CI 2.582-3.298) and approx 6 times (95% CI 5.115-6.493) more likely to experience infertility than 20-25 age group women. This covariate is found to be significant in both types of regions that are rural as well as urban. In urban, women who belong to the age group 25-30 and 30-35 are 3 times (95% CI 2.636-4.288) and approx 7 times (95% CI 5.168-8.307), whereas in rural approx 3 times (95% CI 2.396-3.183) and 5 times (95% CI 4.765-6.287) more likely to experience infertility than 20-25 age group women. The result of adjusted logistic regression shows that women with primary, secondary, and higher education are 9.7% (95% CI 1.015-1.295), 21.4% (95% CI 1.059-1.343), and 33.2% (95% CI 1.083-1.538) more likely to become infertile as compared to no educated women. So this shows that as education increases, infertility also increases. In the urban area, the effect of education on infertility is more as compared in the rural areas. In the urban area, 12% (95% CI 1.033-1.314), 19.1% (95% CI 1.062-1.473), and 24.1% (95% CI 1.097-1.498) primary, secondary, and highly educated women are more likely to become infertile compared to no educated women whereas, in rural areas, 2% (95% CI 0.812-1.043) which is insignificant, 10.4% (95% CI 1.014-1.243) and 15.2% (95% CI 1.088-1.418) primary, secondary and highly educated women are more likely to become infertile as compared to no educated women.

The findings of Table 4 suggest that in India, the Muslim religion significantly affects infertility, but other religions do not. In urban areas, it is not found to be significant among Muslims, but in other religions, it is found to be significant at a level of 10% as compared to Hindus. In Rural, religion is found to be significant. Muslims are 15.6%  (95% CI 0.721-0.987) less likely to become infertile at a 5% level of significance and other religions are 6.2% (95% CI 1.007-1.312) more likely to become infertile at 10% level of significance as compared to Hindu. Caste is found to be significant overall. Others and OBC caste are 13.2% (95% CI 1.023-1.253) and 10% (95% CI 1.002-1.207) more likely to experience infertility as compared to SC/ST. Caste is considered important in urban areas but not in rural areas which is just opposite to religion. The wealth index is found to be a significant indicator of infertility. Poorer, Middle, Richer and Richest are 18.6% (95% CI 1.050-1.341), 20.4% (95% CI 1.056-1.373), 27.2% (95% CI 1.108-1.461) and 17.8% (95% CI 1.013-1.369) more likely to become infertile than poorest women. Wealth Index is found to be a significant indicator in both rural as well as urban, but the effect of wealth status in urban areas is very high than in rural areas. BMI also plays a significant role in determining infertility. Underweight and overweight women are 12.6% (95% CI 0.793–0.965) less and 46.2% (95% CI 1.344–1.590) more likely to be infertile, respectively, compared to normal-weight women. BMI is found to be a significant indicator in both urban as well as rural areas. In the urban areas, 18.1% (95% CI 0.660-0.923) of underweight women are less likely and 25.8% (95% CI 1.103-1.435) of overweight women are more likely to become infertile while in rural areas, 9.7% (95% CI 0.709-0.982) underweight women are less likely and 60.7% (95% CI 1.442-1.792) overweight women are more likely to become infertile. Mass media exposure is found to be significant at the 10% level of significance overall. Women with mass media exposure are 9.4% (95% CI 1.009–1.131) more likely to experience infertility than women who are not exposed to mass media. In the urban areas, 35.1% (95% CI 1.152–1.841) of currently married women who have mass media exposure are more likely to be infertile than women who are not exposed to mass-media, whereas in rural areas, exposure to mass media on infertility is not found to be significant. 

In Model-II, variables for employed women and the interaction of highly educated and employed women have been introduced. All predictors considered in Model-I are still found in the almost similar pattern in Model-II, with additional explanatory variables, employed women and highly educated working women, being positively associated with the likelihood of infertility. This indicates that women who are highly educated as well as employed have a highly significant relationship with infertility status. Women who are working in any field are 11.8% (95% CI 1.029–1.213) more likely to experience infertility than non-working women. The findings advocate that women working in urban areas are more likely to experience infertility. In urban areas, 18.9% (95% CI 1.020–1.386) of women with current working status are more infertile than women who are not currently working. Women working in rural areas are also facing the condition of infertility, but the percentage is less as compared to urban resident women. In rural areas, women with working status are 9.3% (95% CI 1.009-1.206) more infertile than non-working women, while in urban areas the percentage of women experiencing infertility is twice that of rural residing women. Highly educated as well as currently working women are 20.2% (95% CI 1.035–1.538) more likely to be infertile than other women. This interaction effect is more likely to be observed in urban than rural. In urban areas, highly educated working women are 31.8% (95% CI 1.126-1.676) more likely to experience infertility than other women, while only 6.6% (95% CI 1.008-1.536) of highly educated working women in rural areas are more likely to experience infertility than other women. In assessing the strength of the models, the values of -2Log likelihood were determined. This diagnostic tool indicates that Model-II is better than Model-I, and thus Model-II, which comprises variables for working women and highly educated working women, is superior at explaining the incidence of infertility in India and on the basis of the place of residence in it.

Discussion

This study encounters the association between infertility and highly educated working women after controlling for certain socio-economic and demographic variables and has also seen this relational difference in urban as well as rural residing women in 20-35 currently married women using NFHS-4 data. The age groups below 20 years and above 35 years of age were excluded so as to exclude the effects of adolescent sterility and aging. As we know that direct question on infertility has not been asked in the NFHS-4 survey, hence this variable has been constructed by applying some specific conditions. As we know that infertility condition is not a female-centric problem, it occurs in men also, but in this study, only infertility of women has been considered.

The prevalence of infertility was studied using NFHS-4 data and this infertility status was classified according to the residence and divided into three parts: total, urban and rural. In the model I considered seven variables and evaluated the outcome by applying logistic regression. In Model II, one more variable was added and the interaction effect was also considered, and then it was observed what adjustments were made by the model. This study showed that respondents’ age has a significant influence on infertility in both urban as well as rural and the evidence of this result is provided by earlier studies [16, 25-27]. However, infertility may increase with the respondent’s age, so there is a positive relationship between these two variables, possible reason may be as age increases capacity to bear a child decreases. In a previous study, it was found that infertility treatment with In vitro fertilization (IVF) and Intracytoplasmic sperm injection (ICSI) becomes less effective with age, making treatment time-sensitive [28]. Since age is a recognized risk factor for infertility, there is still a need to spread this knowledge. Respondent’s education also has a significant impact on infertility in both types of residences and as education increases, so does the incidence of infertility increase, the possible reason for this could be that as education increases, women’s age at marriage also increases, therefore increasing the complexity of giving birth due to late marriage. Some earlier studies supporting this finding are available in the literature [16, 29]. No significant effect of religion on infertility was found in total and urban areas. But in rural areas, religion has a significant impact on infertility, possible reason for this could be that differences on the basis of religion still exist in the age at marriage and education in rural areas. Caste was found to be a significant variable for infertility. The effect of caste was found to be highly significant for infertility in urban areas, whereas caste was not found to have a significant effect on infertility in rural areas, likely because caste-wise differences in age at marriage and education still exist in urban areas. Others (General) and OBC caste have a higher propensity to go to higher education and get a job, hence the age at marriage is higher. The standard of living is another significant factor influencing infertility, and its prevalence increases with an increase in the standard of living. Although the treatment of infertility is easily accessible and affordable for the wealthiest women as compared to the poor [19, 30], the condition of infertility is also seen mostly in them because of the decent standard of living, women go to higher education, and want to become financially independent by doing the job, which also delays marriage. The standard of living is a highly significant indicator of infertility in the urban area, while the impact of this indicator is not very high in rural areas. Among women of reproductive age, obesity is a common health problem. The World Health Organization (WHO) categorizes overweight as having a body mass index (BMI) above 25 kg/m², while obesity is having a BMI above 30 kg/m² [31]. In some previous studies [32-34], the long-term health risks associated with obesity-related conditions are well documented. Several studies have shown an association between obesity and decreased reproduction rates, and it has been shown that obesity in early adulthood affects reproductive processes. Obesity has a positive association with infertility in both types of residence. As obesity increases, infertility also increases [26]. Mass media exposure has a significant impact on infertility and has a positive association with infertility which says that as mass media exposure increases infertility also increases, possible reason could be in any mass media exposure items such as on TV, radio, newspapers, women see about family planning, education, employment, and the things mentioned in them are taken in the form of late birth, late marriage, which leads to the condition of infertility, especially in India. However, mass media did not have a significant effect on infertility in rural areas, while it was found to be significant in urban areas. The current working status of women is found to be a highly significant indicator of infertility in India and by place of residence, a possible reason could be that women who are in working conditions delay marriage and possibly even delay conception and therefore face problems when they want to get pregnant and are more likely to become infertile. This evidence is supported by some earlier studies [35-36]. The interaction effect of highly educated and working status of women also has a significant influence on infertility and this interaction effect is highly significant in urban areas, a possible reason could be because we know that the percentage of going to higher education is increasing and women who get higher education will definitely take up jobs. In rural areas, since fewer women prefer higher education, this indicator is not so effective for infertility. The option of postponing pregnancy and motherhood has become more popular as women are given more educational and employment options [37]. Many of these women believe that postponing pregnancy has no negative effects and that if they ever have problems conceiving, medical science will be able to intervene with success [38].

Strength and Limitations

There are certain limitations to the present study. Firstly, the NFHS data do not offer the scope to examine all physiological or clinical causes of infertility, as well as the dataset, do not have any question about infertility treatment. Furthermore, this study only addresses the infertility issues associated with women, ignoring infertility problems caused by male factors and both. One of the main strengths of this study is that all the criteria for infertility have been taken together in this study, which gives a true picture of infertile women in India. Additionally, using a national representative dataset provides a comprehensive picture of the situation of this subgroup of women in India.

Conclusions And Recommendations

This article investigated factors affecting the issue of infertility. It is evident that factors such as a woman's age, education, wealth index, exposure to mass media, body mass index, and current employment status had a substantial impact on infertility. This finding may be the result of delayed births and late age at marriage. Intention to marry late and have fewer children is seen in groups of highly educated working women of better socioeconomic status, this leads to a growing medical burden of infertility, an issue that is highly problematic in India. Substantial variation has also been found according to the residence. Highly educated working women living in urban areas were found to be more likely to experience infertility than rural residents. Women who experience disappointment and the social stigma associated with infertility in developing nations like India cannot be ignored. Therefore, it is essential to focus on infertility and raise awareness of it through various programs. Programs should concentrate on reducing the prevalence of endemic infertility-related disorders, postpartum and post-abortion complications, and sexually transmitted diseases (STDs). Since not all types of infertility treatments are financially feasible for the country’s poor and lower-middle-class citizens, several family planning clinics should be constructed to provide crucial infertility examinations, counseling, and medication at a lower cost.

Abbreviations

WHO: World Health Organization, STIs: Sexually Transmitted Infections, ICPD: International Conference on Population and Development, NFHS: National Family Health Survey, OBI: Open Birth Interval, SC/ST: Schedule Caste/Schedule Tribes, OBC: Other Backward Classes, BMI: Body Mass Index, ORs: Odds Ratios, IVF: In Vitro Fertilization, ICSI: Intracytoplasmic Sperm Injection, STDs: Sexually Transmitted Diseases.

Declarations

Acknowledgements

The authors would like to acknowledge the Ministry of Health and Family Welfare (MoHFW) for allowing the use of NFHS-4 data.

Authors’ contributions

Both authors contributed equally to the development of the idea, writing and editing of the final version of the manuscript. The authors read and approved the final manuscript.

Funding

The research has not been financially supported by any organization or funding agency.

Availability of data and materials

Data are available on request from https://dhsprogram.com/Data/.

Ethics approval and consent to participate

Not Applicable.

Consent for publication

Not Applicable.

Competing interests

The authors declare that they have no competing interests.

Author details

^{1, 2*}Department of Statistics, Banaras Hindu University, Varanasi, Uttar Pradesh, 221005, India.

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Tables

Table1. Bivariate analysis of Infertile Women according to Background Characteristics