Literature DB >> 35184726

Fertility awareness and subclinical infertility among women trying to get pregnant at home.

Kaori Iino1,2, Rie Fukuhara3, Megumi Yokota3, Yoshihito Yokoyama3.   

Abstract

BACKGROUND: Recent studies on fertility awareness among the reproductive population have reported the lack of accurate knowledge about fertility and assisted reproductive technologies. However, there has been little information regarding women trying to get pregnant at home. The aim of this study was to explore the prevalence of subclinical infertility among women trying to get pregnant at home, and to evaluate awareness regarding infertility and reasons for not visiting infertility clinics among women who use pregnancy-assist mobile applications to help them conceive.
METHODS: A total of 2084 Japanese women responded to this online survey. We selected 1541 women according to the study criteria. Based on the results of 61 questions, we evaluated knowledge regarding fertility, prevalence of subclinical infertility, and reasons for not visiting the clinic among the participants.
RESULTS: Despite the desire to conceive, the participants had an apparent tendency to overestimate the age limit for childbearing. A total of 338 (21.9%) women answered that in general women aged > 45 years could get pregnant. Approximately 40% of the women had possible subclinical infertility and were unaware of the fact. Additionally, about 70% of the women considered themselves to have infertility problems. Women who were aware of the possibility of infertility hesitated to visit the clinic due to unfamiliarity with a gynecologist or clinic, and apprehensions about the gynecologic examination.
CONCLUSIONS: In our study, some women required treatment for infertility. Nonetheless, they hesitated to visit an infertility clinic. Sexual health education, together with proper accessibility to gynecology clinics, are necessary to reduce involuntary childlessness.
© 2022. The Author(s).

Entities:  

Keywords:  Education; Fertility knowledge; Involuntary childlessness; Japanese; Subclinical infertility

Mesh:

Year:  2022        PMID: 35184726      PMCID: PMC8859874          DOI: 10.1186/s12905-022-01626-z

Source DB:  PubMed          Journal:  BMC Womens Health        ISSN: 1472-6874            Impact factor:   2.809


Background

The average age of first pregnancy has increased in most countries since the 1980s [1]. This delay in childbearing has been attributed to changes in women’s social and economic environments, namely, higher education, social progress, and the rise of effective contraception [2-4]. Although the decision of a delayed marriage or pregnancy influences the lifestyle of women, it leads to several health problems. Older mothers have a higher risk of both obstetric and fetal complications, including gestational diabetes, placenta previa, placental abruption, hypertensive disorders of pregnancy, and fetal congenital anomalies [5-8]. Moreover, recent studies on fertility awareness in the reproductive population have reported the lack of accurate knowledge about fertility and assisted reproductive technologies (ART) among women who are trying to conceive [4, 9–22]. The proportion of women having accurate knowledge about fertility is particularly low in Japan, compared to other industrial countries [23]. The importance of health literacy and fertility education has been emphasized in the Japanese society, similar to other countries [21]. Furthermore, the number of websites or applications disseminating information on fertility have rapidly increased in the last decade [20, 24]. In addition, there are a lot of application services that inform the users about the approximate ovulation day from the menstrual cycle, and the number of users of this kind of application is increasing. Although the merit of getting information about reproductive health from websites or smartphone applications could be limited among women who use these daily, the use of self-timing therapy with these application services would be more convenient than going to the clinic. Thus, women have been able to access fertility information more easily than before. However, the number of infertile patients has been increasing in Japan [25]. The aforementioned facts suggest the presence of other problems, not only the lack of fertility knowledge but also circumstances surrounding women or underlying psychological problems. To clarify the underlying problems, we investigated women who were trying to conceive naturally. The majority of previous studies on fertility-related knowledge have been conducted among university students [9, 11–14, 17, 22, 26, 27]. These studies concluded that many of university students overestimated women’s age-related decline in ovarian function. Although this tendency of insufficient knowledge of fertility is very important, they could not reveal all the problems. That is because most of university students would not realistically consider fertility and infertility at the time of the survey. Therefore, an investigation among the general population is required. There have been some studies regarding fertility knowledge among the general population [10, 15, 18, 20, 24, 28, 29]. However, there has been little information on the following aspects among women trying to conceive naturally: (1) prevalence and awareness of subclinical infertility, and (2) reasons for visiting the clinic to identify the possibility of infertility. We performed online research in Japan regarding the knowledge on fertility, the prevalence and risk factors of potential infertility, and reasons for not visiting infertility clinics among women who used pregnancy-assist mobile applications at home.

Material and methods

Participants and procedures

We conducted the study on a smartphone application (Lunaluna) that comprised user information, including women’s health, fertility, and ovulation prediction (MTI, Tokyo, Japan) in September 2018 [30]. We chose Lunaluna as the tool for our investigation for the following two reasons. First, Lunaluna is one of the most popular applications presenting women’s health information among Japanese reproductive-aged women. Second, the developers of Lunaluna had experienced other academic research on the application. The time frame that collected the names of participants who wanted to have children was shown for 13 days. At the beginning of the session, the purpose and methods of this study were presented to all participants. Additionally, we informed the participants that this survey was targeted at women trying to get pregnant at that moment. After obtaining informed consent, the participants had to answer several questions on the application site regarding fertility and methods undertaken for childbearing. Each participant took about 50 min to fill in the questionnaire. All participants’ data were anonymized during the analysis. In addition, the data were saved in a computer, which was protected with strict security. A total of 2084 women responded to this survey. We selected 1541 women according to the inclusion criterion, that is women who wanted to have children at that time, and two exclusion criteria, that is (1) women receiving infertility treatment and (2) women receiving hormone therapy (Fig. 1). Several questions were asked in order to select the target woman. The first question was as follows: “Do you want to have children now?” We obtained a negative response from 114 women who responded to the remaining questions. Of the 1970 women who wanted to have children, 272 were under treatment for infertility, 146 did not respond to the question on infertility treatment, and 11 were undergoing hormone therapy. We eventually analyzed 1541 participants who completed the questionnaire.
Fig. 1

Flow diagram showing participant selection

Flow diagram showing participant selection

Measures

Based on previous research, the questionnaire was designed for this study by three gynaecologists, including one reproductive medicine specialists [9, 21, 24]. The questionnaire comprised of 62 questions in seven sections. Every question was shown to the participants in Japanese, and the format of answers to each question was presented in parentheses. Questions for selecting women according to the criteria (3 items) The first question was, ‘Do you want to have children now?’ (Yes/No). Only participants who answered ‘Yes’ proceed with the following questions: ‘Are you receiving infertility treatment?’(Yes/No) and ‘Are you receiving hormone therapy?’(Yes/No). Participant’s demographic information (31 items) Participants were asked to state their age, body weight, height, smoking status (Never or Former/Current), medical history (open response), social status (Full-time/Part-time/Housewife or Unemployed/Student), marital status (Yes/No), and personal experience of reproduction (Yes/No, if yes, input the number of children). Menstrual information (10 items) Participants were asked to state their age of menarche and pattern of menstrual cycle (Regular/Variable-length; persistent ≥ 7-day difference in the length of consecutive cycles/Interval of amenorrhea of ≥ 60 days). The answer to the menstrual cycle was defined according to the criteria of the Stage of Reproductive Aging Workshop [31]. Next, participants were asked whether they had the following symptoms: dysmenorrhea (Yes/No, and if yes, did they use painkillers or not), irregular vaginal bleeding (Yes/No), and hypermenorrhea (Yes/No). Knowledge about age-related decline in fertility (1 item) The question was, ‘In general, until what age do you think women can get pregnant?’. Attitude and behavior towards trying to get pregnant (4 items) Participants were asked the following questions: ‘Since how long are you having intercourse without contraception?’, ‘How frequent do you have intercourse?’(open response), ‘Do you feel any difficulties while having intercourse?’ (Yes/No), and ‘What are you doing to become pregnant? (Self-timing therapy with application service/Self-timing therapy without application service/Nothing in particular)’. We chose the following question: ‘What are you doing to become pregnant?’ to clarify the number of women who used the application service of self-timing therapy because it would be an important participants’ characteristic for this study. Awareness and attitude regarding infertility (4 items) At first, participants were asked the question, ‘Have you ever had an infertility examination?’(Yes/No). Only participants who answered ‘Yes’ proceed with the following questions: ‘What is the likelihood of your infertility?’ (Highly unlikely, Unlikely, Possibly, Likely, and Highly likely) [32], ‘Do you think you should be examined for infertility?’(Yes/No), and ‘Why haven’t you visited a clinic for infertility examination?’(multiple choices allowed: There is no time/I am afraid of the gynecologic examination/I feel afraid of discovering the truth/Partner is not cooperative/I don’t know a familiar gynecologic doctor or clinic/If I am infertile, I don’t want another person to know it/Nothing in particular/ Other, open response). With regard to the last question; ‘Why haven’t you visited a clinic for infertility examination?’, we presented several likely answers for the participants to choose from, including the option “other” as it allowed respondents to answer the question freely. Partner’s demographic information (9 items) Participants were requested to state their partner’s age, body weight, height, and medical history (open response).

Statistical analysis

We performed logistic regression analysis to assess the risk factors for subclinical infertility among women trying to get pregnant at home. We defined subclinical infertility among women who failed to conceive successfully after ≥ 12 months of regular, unprotected intercourse (or ≥ 6 months if the women over age 35 years), according to the Practice Committee of the American Society for Reproductive Medicine, 2013 [33]. We calculated the odds ratios (OR) and 95% confidence interval (CI) in the multivariate analysis after simultaneously controlling for potential confounders, such as age, body mass index (BMI), history of smoking, delivery status, incidence of abortion or miscarriage, menstrual cycle, including BMI and smoking history of partner. The multivariate analysis was performed among 1377 women because of 164 missing data. Statistical analyses were performed using the SPSS software package, version 22.0 (SPSS Inc., Chicago, IL, USA). A P value < 0.05 was considered statistically significant.

Results

Characteristics of participants and partners.

Table 1 summarizes the characteristics of the participants and their partners. The largest age and BMI group of participants were 30–34 years (37.1%) and 18.5–24.9 kg/m2 (67.6%), respectively. Regarding their partner, the largest age and BMI group were 30–39 years (52.0%) and 18.5–24.9 kg/m2 (64.9%), respectively. 234 (15.2%) participants and 636 their partners (41.3%) were current smokers.
Table 1

Characteristics of participants and partners (N = 1541)

Participants’ informationN (%)
Age (years)16–29500 (32.4)
30–34571 (37.1)
35–39314(20.4)
40–44128 (8.3)
45–5028 (1.8)
Body mass index (kg/m2) < 18.5225 (14.6)
18.5–24.91040 (67.6)
25–29.9198 (12.9)
 ≥ 3076 (4.9)
SmokingNever smoked or former smoker1307 (84.8)
Current smoker234 (15.2)
Social statusFull-time job888 (57.6)
Part-time job320 (20.8)
Housewife/Unemployed323 (21.0)
Student10 (0.6)
Marital statusSingle294 (19.1)
Married1247 (80.9)
ReproductionHave children582 (37.8)
Experience of abortion or miscarriage305 (19.8)
History of present illnessInternal Medicine85 (5.5)
Gynecologic disease41 (2.7)
Endometriosis12 (0.8)
Myoma8 (0.5)
Ovarian cyst5 (0.3)
Dysplasia of uterine cervix9 (0.6)
Other7 (0.5)
Mental illness37 (2.4)
Other63 (4.1)
Nothing1315 (85.3)
Menstrual cycle aRegular1185 (76.9)
Variable length persistent ≥ 7-day difference in length of consecutive cycles157 (10.2)
Interval of amenorrhea of ≥ 60 days72 (4.7)
Dysmenorrhea bYes652 (42.3)
Partners’ information
Age (years) ≤ 29357 (23.2)
30–39801 (52.0)
40–49319 (20.7)
50–6433 (2.1)
Body mass index (kg/m2) < 18.562 (4.0)
18.5–24.91000 (64.9)
25–29.9363 (23.6)
 ≥ 3080 (5.2)
SmokingNever smoked or former smoker879 (57.0)
Current smoker636 (41.3)

aEach category was defined according to the criteria of the Stage of Reproductive Aging Workshop

bDysmenorrhea was defined women who need pain killer during menstrual period almost every time

Characteristics of participants and partners (N = 1541) aEach category was defined according to the criteria of the Stage of Reproductive Aging Workshop bDysmenorrhea was defined women who need pain killer during menstrual period almost every time Nearly 80% of the women had a job (full-time: 57.6%; part-time: 20.8%). Of 1541, 1,247 (80.9%) women were married and 582 (37.8%) women had children. A total of 41 women (2.7%) had gynecologic disease: Endometriosis 12 (0.8%), Myoma 8 (0.5%), Ovarian cyst 5 (0.3%), and Dysplasia of uterine cervix 9 (0.6%). There were no women who had medical history which leads infertility necessarily, for example bilateral oophorectomy or hysterectomy. Regarding to menstrual cycle, regular, variable-length; persistent ≥ 7-day difference in the length of consecutive cycles, and interval of amenorrhea of ≥ 60 days were 76.9%, 10.2%, 4.7%, respectively. 652 (42.3%) out of all participants suffered with dysmenorrhea.

Knowledge about the age-related decline of fertility, Attitude and behavior for trying to get pregnant, and Awareness of and attitude towards infertility

Table 2 presents the participants’ knowledge about the age-related decline of fertility, attitude and behavior for trying to get pregnant, and awareness and attitude regarding infertility.
Table 2

Questions and answers about Knowledge about the age-related decline of fertility, Attitude and behavior for trying to get pregnant, and Awareness of and attitude towards infertility

QuestionAnswerN (%)a
In general, what age do you think women can get pregnant until? < 35 year55 (3.6)
35–39 year412 (26.8)
40–44 year735 (47.7)
 ≥ 45 year338 (21.9)
What are you doing to become pregnant?Self-timing therapy with application service1146 (74.4)
Self-timing therapy without application service50 (3.2)
Nothing in particular345 (22.4)
Since how long are you having intercourse without contraception? < 1 year746 (48.4)
1 to < 2 year267 (17.3)
2 to < 3 year159 (10.3)
3 to < 4 year94 (6.1)
 ≥ 4 year222 (14.4)
No response53 (3.4)
What is the likelihood of your infertility?Highly unlikely121 (7.9)
Unlikely342 (22.2)
Possibly651 (42.2)
Likely306 (19.9)
Highly likely118 (7.7)
No response3 (0.2)
Do you think you should be examined for infertility?Yes718 (46.6)
No644 (41.8)
Why haven’t you visited a clinic for infertility examination?bThere is no time307 (22.5)
I am afraid of the gynecologic examination173 (12.7)
I feel afraid of discovering the truth305 (22.4)
Partner is not cooperative107 (7.9)
I don’t know a familiar gynecologic doctor/clinic304 (22.3)
If I am infertile, I don’t want another person to know it89 (6.5)
Nothing in particular415 (30.5)
Other368 (27.0)

aDistribution of responses calculated excluding missing data

bThis question was asked to women without an experience of a prior infertility examination (n = 1362)

Questions and answers about Knowledge about the age-related decline of fertility, Attitude and behavior for trying to get pregnant, and Awareness of and attitude towards infertility aDistribution of responses calculated excluding missing data bThis question was asked to women without an experience of a prior infertility examination (n = 1362) Approximately 338 (21.9%) women believed that women aged > 45 years could have children. Additionally, 47.7% of the participants selected the 40–44 years category as the upper age limit to have children. These results highlight the apparent tendency of most participants to overestimate the possible age of childbearing. About three-quarters (74.4%) of the women used the ovulation prediction service included in the application. The number of women whose sterile period was < 1 year, 1 year, 2 years, 3 years, and ≥ 4 years was 746 (48.4%), 267 (17.3%), 159 (10.3%), 94 (6.1%), and 222 (14.4%), respectively. Regarding infertility awareness, about 70% of women thought the following about the possibility of infertility: (1) highly unlikely (7.9%), (2) unlikely (22.2%), (3) possibly (42.2%), (4) likely (19.9%), and (5) highly likely (7.7%). Among these five groups divided by the likelihood of their infertility, the prevalence of subclinical infertility was calculated as shown in Fig. 2. Among those who gave a negative response to the question on potential infertility (“Never”, “Almost never”), > 40% of women had a sterile period of > 1 year.
Fig. 2

Awareness of infertility and sterile period. Legend: Each category of the awareness of infertility corresponds to the results of the question “Do you think you are infertile?” in Table 2. Each bar represents the proportion of potentially sterile women whose sterile periods were more than one year

Awareness of infertility and sterile period. Legend: Each category of the awareness of infertility corresponds to the results of the question “Do you think you are infertile?” in Table 2. Each bar represents the proportion of potentially sterile women whose sterile periods were more than one year Over half of the 1,362 women, who had never been examined for infertility, were aware of the necessity for an infertility examination. The primary reasons for not visiting the clinic were as follows: (i) “no time” (22.5%), (ii) “hesitation to know the truth” (22.4%), and (iii) “an absence of a familiar gynecologist or clinic (22.3%).” Other reasons behind this hesitancy included the following: (1) “the fear of gynecologic examination” (12.7%), (2) “an uncooperative partner” (7.9%), and (3) “the hesitation to let another person know about their infertility (6.5%).” Among the potential answers, the most common subjective reason given for the “other” option was “I do not think myself infertility because of experience of giving birth (N = 80, 5.9%)”, and the second was “financial reason (N = 27, 2.0%)”.

Relationships between infertility and risk factors

Table 3 summarizes the unadjusted and multivariable-adjusted ORs of infertility for demographic characteristics and fertility experiences. Among the 1,541 women, 742 (48.2%) were infertile with sterile periods of > 1 year. According to the multivariable analysis, multiparity (OR; 1.450, 95% CI; 1.144–1.837, P = 0.002), slightly changed menstrual cycles (variable-length ≥ 7-day difference [OR; 1.536, 95% CI; 1.076–2.193]), and having male partners with smoking habits (OR; 1.383, 95% CI; 1.088–1.759, P = 0.008) were significant risk factors for infertility. With respect to age, three groups, including women aged 35–39 years (OR; 1.885, 95% CI; 1.307–2.719, P = 0.001) and 40–44 years (OR; 2.554, 95% CI; 1.490–4.375, P = 0.001) and women whose partners were aged 40–49 years (OR; 1.519, 95% CI; 1.030–2.240, P = 0.035), had a significantly higher risk of infertility, compared to the youngest group. On the other hand, women’s BMI, smoking history, incidence of abortion or miscarriage, and BMI of male partners were not significant risk factors for infertility.
Table 3

The odds ratio of infertility by demographic characteristics and fertility experiences

Unadjusted odds ratioMultivariable-adjusted odds ratioa
OR95% CIpOR95% CIp
Age(years)
16–291.0
30–341.2220.960–1.5550.1041.0940.817–1.4660.547
35–392.3711.773–3.1720.0001.8851.307–2.7190.001
40–443.3602.199–5.1340.0002.5541.490–4.3750.001
45–503.9441.647–9.4480.0022.8971.068–7.8590.037
Body mass index (kg/m2)
 < 18.51.0
18.5–24.91.0570.792–1.4100.7080.8950.650–1.2330.498
25–29.91.2360.842–1.8120.2790.8150.527–1.2600.357
 ≥ 302.0581.193–3.5500.0091.3640.738–2.5190.322
Smoking
Never or former smoker1.0
Current smoker1.4641.102–1.9430.0081.1560.832–1.6070.387
Delivery status
Nullipara1.0
Have children1.7821.445–2.1970.0001.4501.144–1.8370.002
Experience of abortion or miscarriage
No1.0
Yes1.7671.363–2.2900.0001.1830.882–1.5850.262
Menstrual cycle
Regular1.0
Variable length ≥ 7-day difference1.3890.991–1.9470.0561.5361.076–2.1930.018
Interval of amenorrhea of ≥ 60 days1.3740.849–2.2260.1961.4300.848–2.4090.179
Age of partner (years)
18–291.0
30–391.6671.295–2.1460.0001.3260.973–1.8060.074
40–492.6711.955–3.6490.0001.5191.030–2.2400.035
50–642.5291.207–5.3010.0141.2010.525–2.7470.665
Body mass index of partner (kg/m2)
 < 18.51.0
18.5–24.90.7520.447–1.2640.2820.7270.408–1.2950.279
25–29.90.8760.508–1.5120.6350.7590.414–1.3920.373
 ≥ 301.4180.715–2.8120.3181.1870.560–2.5200.655
Smoking of partner
Never or former smoker1.0
Current smoker1.4971.219–1.8400.0001.3831.088–1.7590.008

OR, odds ratio; CI, confidence interval

aAdjusted for age, body mass index, smoking, delivery status, experience of abortion or miscarriage, menstrual cycle, age of partner, body mass index of partner, and smoking of partner. Multivariate analysis was performed among 1377 women because of 164 missing data

The odds ratio of infertility by demographic characteristics and fertility experiences OR, odds ratio; CI, confidence interval aAdjusted for age, body mass index, smoking, delivery status, experience of abortion or miscarriage, menstrual cycle, age of partner, body mass index of partner, and smoking of partner. Multivariate analysis was performed among 1377 women because of 164 missing data

Discussion

Several previous studies have highlighted the poor knowledge regarding fertility among women of reproductive age [4, 9, 11–15, 17–20, 22, 24, 26–29]. However, in this research field, awareness and attitude regarding infertility among the general population has not been discussed adequately. In this study, we revealed that there were a considerable number of women who continued to try conceiving at home, despite the possibility of subclinical infertility and being aware of it. We also showed that some women hesitated to go to an infertility clinic as they were not familiar with gynecologic examinations. The number of women who need infertility treatment has been recently increasing in several countries [34, 35]. Among all infertility treatments, ART puts significant economic, mental, and physical burden on the women [36-38]. Furthermore, it has a considerable impact on their daily lives. The increasing number of women with infertility may be attributed to their lifestyle changes, such as delayed parenthood due to higher education, social progress, and late marriage [2-4]. Moreover, several epidemiological investigations from various countries have reported about the poor knowledge regarding infertility among numerous women of reproductive age [4, 9, 11–15, 17–20, 22, 24, 26–29]. This subsequently increases the number of women unexpectedly requiring infertility treatment. Poor fertility awareness is a particularly important concern in some developed countries where declining birth rate is a serious social issue [34, 39, 40]. In this study, the apparent tendency to overestimate the age limitation for childbearing was consistent with those in previously published results [4, 9–22]. Obtaining correct medical information through the internet is accessible for most people in recent times [20, 24]. However, the dissemination of knowledge on fertility and infertility is inadequate among women who need them. Certain background factors, such as the tendency to harbor sensitivity regarding infertility problems and late childbearing by celebrities, also create a significant impact. Hence, imparting sex education might effectively resolve the problem of insufficient knowledge on fertility. Passet-Wittin, J. identified five categories of determinants of medical help-seeking for infertility: socio-demographic variables, socio-economic factors, reproductive history, attitudes, and psychological factors [41]. Although surveys on psychological factors were limited, anxiety about medical treatment was reported as an important reason for not pursuing medical treatment of infertility [41]. Our results revealed another problem that had not been discussed well in the literature, that is, the hesitancy of visiting an infertility clinic, which was attributed to a lack of familiarity with a gynecologist or clinic and fear of gynecologic examination. Simply put, despite infertility being a characteristic problem in Japan, women faced difficulty in visiting gynecology clinics. The previous surveys on psychological factors were conducted in Europe and US where people have different images of infertility from that in Japan [41-43]. In comparison with people in Europe and the US, Japanese people tend to feel that the topic of infertility is a taboo. Therefore, hesitancy of visiting an infertility clinic may be a unique aspect in Japan. One reason for the aforementioned problem is that women rarely visit gynecology clinics before getting pregnant in Japan. The administration of human papilloma virus vaccines or recognition of women’s health care would enhance their familiarity with a gynecology clinic. The multivariate analysis in our study indicated “multipara” as a significant risk factor for infertility. Such women may lack sufficient awareness on secondary infertility due to a previous pregnancy. Despite being overlooked for secondary infertility, such women should be aware of infertility in case of a long period of sterility. Our study has several limitations. First, the participants were selected from among those who used a particular application, thus, raising the possibility of a selection bias. The aforementioned application presented information about pregnancy and was aimed at helping the users conceive. Thus, the participants might have had a stronger desire to bear a child, compared to ordinary women. In addition, there were 10 university students in this study. In general, it is rare for university students to try to get pregnant. However, the number was so small (0.6% of all) that including university students would have little influence on our results. Second, we conducted the study among Japanese women who often harbor negative and sensitive ideas about infertility. This tendency of more women hesitating to go to the clinic for infertility examination or women not wanting to know the truth that they are infertile may have influenced our results. Third, our investigation lacked information about the selected participants’ place of residence. There are several infertility clinics in a city, compared to the few in the countryside. This uneven distribution of infertility clinics might have also influenced the choice to seek infertility treatment. Thus, the differences in this study could not be clarified. Fourth, as there had been no research about medical help-seeking for infertility in Japan, we designed some of the questions about “awareness and attitude regarding infertility” for this study. However, the information might be biased.

Conclusions

According to our investigation, there may be a significant number of women with subclinical infertility among those trying to get pregnant at home. Furthermore, these women generally hesitate to visit the clinic for several reasons, namely, being unfamiliar with seeing a gynecologic doctor and feeling afraid of discovering the truth. Additionally, our results also indicate that prior experience of childbirth might be a possible risk factor for secondary infertility. The dissemination of correct knowledge regarding fertility and infertility is insufficient. The presence of a gynecologist who could provide medical advice at an appropriate time might effectively resolve the problem that some subclinical infertility patients encounter, namely; hesitant to go to a clinic because of an unfamiliar gynecologic doctor or clinic. Our study had a small sample size with limited participants. This calls for the need for large-scale studies in various countries.
  38 in total

1.  Fertility awareness and parenting attitudes among American male and female undergraduate university students.

Authors:  Brennan D Peterson; Matthew Pirritano; Laura Tucker; Claudia Lampic
Journal:  Hum Reprod       Date:  2012-03-08       Impact factor: 6.918

2.  Fertility awareness, intentions concerning childbearing, and attitudes towards parenthood among female and male academics.

Authors:  C Lampic; A Skoog Svanberg; P Karlström; T Tydén
Journal:  Hum Reprod       Date:  2005-11-17       Impact factor: 6.918

Review 3.  Delayed childbearing: effects on fertility and the outcome of pregnancy.

Authors:  Juan Balasch; Eduard Gratacós
Journal:  Fetal Diagn Ther       Date:  2011-01-12       Impact factor: 2.587

Review 4.  Factors associated with medical help-seeking for infertility in developed countries: A narrative review of recent literature.

Authors:  Jasmin Passet-Wittig; Arthur L Greil
Journal:  Soc Sci Med       Date:  2021-02-17       Impact factor: 4.634

5.  International estimates of infertility prevalence and treatment-seeking: potential need and demand for infertility medical care.

Authors:  Jacky Boivin; Laura Bunting; John A Collins; Karl G Nygren
Journal:  Hum Reprod       Date:  2007-03-21       Impact factor: 6.918

6.  What do women know about the risks of delayed childbearing?

Authors:  Suzanne Tough; Karen Benzies; Christine Newburn-Cook; Karen Tofflemire; Nonie Fraser-Lee; Alexandra Faber; Reg Sauve
Journal:  Can J Public Health       Date:  2006 Jul-Aug

7.  Childless women's knowledge of fertility and assisted human reproduction: identifying the gaps.

Authors:  Judith C Daniluk; Emily Koert; Anthony Cheung
Journal:  Fertil Steril       Date:  2011-12-21       Impact factor: 7.329

8.  Factors influencing childbearing decisions and knowledge of perinatal risks among Canadian men and women.

Authors:  Suzanne Tough; Karen Tofflemire; Karen Benzies; Nonie Fraser-Lee; Christine Newburn-Cook
Journal:  Matern Child Health J       Date:  2007-01-20

Review 9.  Efficacy of psychosocial interventions for psychological and pregnancy outcomes in infertile women and men: a systematic review and meta-analysis.

Authors:  Yoon Frederiksen; Ingeborg Farver-Vestergaard; Ninna Grønhøj Skovgård; Hans Jakob Ingerslev; Robert Zachariae
Journal:  BMJ Open       Date:  2015-01-28       Impact factor: 2.692

Review 10.  What do people know about fertility? A systematic review on fertility awareness and its associated factors.

Authors:  Juliana Pedro; Tânia Brandão; Lone Schmidt; Maria E Costa; Mariana V Martins
Journal:  Ups J Med Sci       Date:  2018-06-29       Impact factor: 2.384

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