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Knowledge about factors that influence fertility among Australians of reproductive age: a population-based survey
ORIGINAL ARTICLES: INFERTILITY
Knowledge about factors that influence fertility among Australians of reproductive age: a population-based survey Karin Hammarberg, Ph.D.,a,b Tracey Setter, M.P.H.,a Robert J. Norman, M.D.,c Carol A. Holden, Ph.D.,d Janet Michelmore, Dip.Ed.,e and Louise Johnson, Dip.Ed.a a Victorian Assisted Reproductive Treatment Authority, Melbourne, Victoria; b Jean Hailes Research Unit, School of Public Health and Preventive Medicine, Monash University, Clayton, Victoria; c Robinson Institute, School of Paediatrics and Reproductive Health, University of Adelaide, North Adelaide, South Australia; d Andrology Australia, Monash Institute of Medical Research, Monash University, Clayton, South Australia; and e Jean Hailes Foundation for Women's Health, Clayton, Victoria, Australia
Objective: To explore knowledge about the effects on fertility of age, obesity, smoking, and timing of intercourse among Australians of reproductive age. Design: Telephone survey of a representative sample of Australians. Setting: Not applicable. Patient(s): Australians aged 18 to 45 years who wish to have a child or another child now or in the future. Intervention(s): None. Main Outcome Measure(s): Knowledge about the effect on fertility of age, obesity, smoking, and timing of intercourse. Result(s): A total of 462 interviews were conducted. The majority of respondents underestimated, by about 10 years, the age at which male and female fertility starts to decline. Only one in four correctly identified that female fertility starts to decline before age 35, and one in three identified that male fertility starts to decline before age 45. Most (59%) were aware that female obesity and smoking affect fertility, but fewer recognized that male obesity (30%) and smoking (36%) also influence fertility. Almost 40% of respondents had inadequate knowledge of when in the menstrual cycle a woman is most likely to conceive. Conclusion(s): Considerable knowledge gaps about modifiable factors that affect fertility were identified. These are targeted in a national education campaign to promote awareness of factors Use your smartphone that influence fertility. (Fertil SterilÒ 2013;99:502–7. Ó2013 by American Society for Reproducto scan this QR code tive Medicine.) and connect to the Key Words: Age, education, fertility, obesity, smoking Discuss: You can discuss this article with its authors and with other ASRM members at http:// fertstertforum.com/hammarbergk-fertility-age-obesity-smoking-education/
M
ost people want and expect to have children at some stage of their life (1–5). For some,
reasons beyond their personal control prevent them from achieving this. For others, potentially preventable factors
Received August 27, 2012; revised October 2, 2012; accepted October 16, 2012; published online November 14, 2012. K.H. has nothing to disclose. T.S. has nothing to disclose. R.J.N. has received payment for lectures from Merck Serono. C.A.H. has received reimbursement from VARTA for participating in Your Fertility and payment from Pfizer for development of educational presentations. J.M. has nothing to disclose. L.J. has received funding for travel and administrative support from her employer, the Victorian Department of Health, payment from universities for development of educational presentations, and is a member of the Occupational Therapy Board of Australia. Supported by the Australian Government Department of Health and Ageing, Population Health Programs Branch, Family Planning Grants Program. Reprint requests: Karin Hammarberg, Ph.D., Jean Hailes Research Unit, School of Public Health and Preventive Medicine, Monash University, Level 1 43–51 Kanooka Grove, Clayton 3168, Victoria, Australia (E-mail: [email protected]). Fertility and Sterility® Vol. 99, No. 2, February 2013 0015-0282/$36.00 Copyright ©2013 American Society for Reproductive Medicine, Published by Elsevier Inc. http://dx.doi.org/10.1016/j.fertnstert.2012.10.031 502
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reduce their chances of realizing this life goal. We set out to survey Australians of reproductive age about their understanding of the impact of age, weight, smoking, and timing of sex on fertility. There is reliable evidence of the negative effects on fertility and obstetric outcomes of increasing maternal and paternal age (6–15). For a diverse range of reasons, including access to effective contraception and improved education and employment opportunities for women, the age of childbearing in Australia and other high-income countries has increased in the last few decades VOL. 99 NO. 2 / FEBRUARY 2013
Fertility and Sterility® (14, 16, 17). This in turn has led to increasing rates of age-related infertility, more people seeking assisted reproductive technology (ART) treatment to conceive, and some people having fewer children than they had planned (8, 14, 17). Statistically, women's fecundity starts to decline around age 30 and by age 35 the decline accelerates (18). The age of the male partner influences semen quality and fertility (9, 19, 20). It is apparent that many underestimate the influence of increasing female and male age on the chance of conceiving and having a healthy baby (4, 14, 17, 21–25). This combined with the belief that ART can overcome age-related infertility may result in a missed opportunity to have biological children (23–26). There is also consistent evidence of the adverse effects of being overweight and smoking on fertility, obstetric outcomes, and the health of the baby at birth and in the future (27–37). In high-income and middle-income countries, the rates of overweight (body mass index [BMI] R25) and obesity (BMI R30) are increasing (38–40). Rates of smoking vary between countries, but in Australia in 2008 one in five people of reproductive age were smokers (41). Most people are aware of the negative effects of obesity and smoking on general health, but research suggests that the adverse effects of these lifestyle factors on fertility, obstetric outcomes, and neonatal and long-term health of children are poorly understood (23, 42, 43). Little is known about the level of understanding among people of reproductive age about when in the menstrual cycle a woman is most likely to conceive. It has been suggested that educating couples about the fertile window in the menstrual cycle is a simple and inexpensive way to increase the chance of conception for those who wish to have children (44–46). To allow people to make well-informed decisions about family formation, prevent the personal suffering associated with infertility and adverse obstetric and perinatal outcomes, and reduce the health-care costs of treating infertility, pregnancy, and neonatal complications, awareness about modifiable factors that affect fertility is essential. We explored the extent of knowledge among the general population of Australian women and men of reproductive age about the effects of age, obesity, smoking, and timing of intercourse on the chance of conceiving.
MATERIALS AND METHODS The study was approved by the Research and Ethics Committee of the State Government of Victoria's Department of Human Services.
Setting The Victorian Assisted Reproductive Treatment Authority (VARTA) in the state of Victoria, Australia, is a statutory authority responsible for administering aspects of the Assisted Reproductive Treatment Act of 2008 (Victoria) (47). One of its roles is to provide public education and resources for the community and health professionals on matters relating to fertility and ART. In 2011, the project Your Fertility was initiated by VARTA and its partners in the Fertility Coalition: the Jean Hailes Foundation for Women's Health VOL. 99 NO. 2 / FEBRUARY 2013
(www.jeanhailes.org.au), Andrology Australia (www.andro logyaustralia.org), and the Robinson Institute at the University of Adelaide (www.adelaide.edu.au/robinson-institute). The aim of Your Fertility is to promote awareness of factors that influence fertility so that individuals and couples can make informed and timely decisions regarding childbearing and to prevent infertility and involuntary childlessness. To guide the development of educational material and other project activities, the need to ascertain existing knowledge gaps was identified.
Participants Men and women aged 18 to 45 years, living in Australia, wishing to have a child or an additional child now or in the future, and with sufficient English language proficiency to participate in a telephone survey (script available online as Supplemental Material) were eligible to participate.
Method The Social Research Centre (SRC, www.srcentre.com.au) conducts quantitative and qualitative research across all areas of social and health research for academic institutions, government, and nonprofit and corporate organizations. The SRC was contracted to conduct a telephone survey about fertility awareness with a representative sample of the Australian population who fulfilled the inclusion criteria. Telephone access among adult Australians is almost universal. Traditional telephone surveying, using randomly generated landline numbers, has in recent years become less accurate at reaching the general population due to an increasing incidence of households with no landline (cell phone only), particularly among those younger than 40 years. To ensure a representative sample, a split sample technique was employed that covered randomly generated landline numbers and randomly generated cell phone numbers. This split sample ensures full coverage of the Australian population. The best practice error margin for social research is 5% (at 95% confidence level). This means that the target sample size needs to be large enough so that if, for example, 50% of the sample answer ‘‘yes’’ to a question, we can be confident (to a level of 95%) that the actual figure in a census would average between 45% and 55%. The optimum sample size to achieve this 5% error margin on any population over 1 million is n ¼ 385. To meet industry standard error margins, a sample of at least 385 was needed for this study. To enable interviews to be achieved with hard-to-reach individuals, an unlimited call cycle was used (numbers where there was no response were tried more than seven times), and the call times included evenings and weekends.
Materials Based on existing literature and the aim of the Your Fertility education campaign, a questionnaire gauging knowledge about the influence of age, obesity, smoking, and timing of sex was devised. It also included questions about sociodemographics and fertility, reproductive-health school education, and preferred sources of reproductive health-related information. The professional interviewers assigned to this project 503
ORIGINAL ARTICLE: INFERTILITY attended a 2-hour briefing session that covered the project's background, objectives, and procedures as well as all aspects of administering the survey questionnaire. A pilot comprising 30 interviews was conducted, and the only change arising from the pilot testing was a minor wording change for grammatical clarity. The interview took 10 to 12 minutes to complete. The perceived adequacy of knowledge learnt at school about prevention of pregnancy, safe sex, and sexually transmitted infections (STIs), the biology of reproduction, protection of fertility, and the influence of age, weight, and smoking was rated by respondents as ‘‘good knowledge,’’ ‘‘some knowledge,’’ ‘‘poor knowledge,’’ and ‘‘was not taught.’’ The response alternatives for perceived influence on fertility of male and female obesity and smoking were: ‘‘a lot,’’ ‘‘a little,’’ ‘‘not at all,’’ or ‘‘don't know’’; at what age men's and women's fertility starts to decline: 20–24, 25–29, 30–34, 35–39, 40–44, 45–49, R50, ‘‘age doesn't matter,’’ or ‘‘don't know’’; knowledge about the most fertile time in the menstrual cycle: ‘‘in the middle week between periods,’’ ‘‘in the week just after her period,’’ ‘‘in the week just before her next period,’’ ‘‘almost any day except during her period,’’ ‘‘during her period,’’ or ‘‘don't know’’; whether the respondent had sought information on reproductive health matters: ‘‘yes’’ or ‘‘no’’; and preferred sources of information about reproductive matters: ‘‘Internet,’’ ‘‘health professional,’’ ‘‘books,’’ ‘‘family,’’ ‘‘school/university,’’ ‘‘friends,’’ ‘‘TV,’’ or ‘‘other.’’
Data Management and Analysis Data were entered in SPSS for Windows, release 18.00 (SPSS, Inc.) and weighted by age, gender, level of education, country of birth, location (state), and type of telephone (landline or cell phone) to ensure that it was proportionally representative of the Australian population. The calculation of the poststratification weighting factors was undertaken using a ‘‘rim weighting’’ approach, sometimes referred to as iterative proportional fitting. This technique was used to adjust for the disproportionate nature of the sample and differential survey response rates across age, gender, educational attainment, country of birth, location, and telephony status. The sample was weighted to independent population benchmarks. The weights created by ‘‘rim weighting’’ were created using a statistical regression approach which seeks to achieve the ‘‘best fit’’ possible with the population proportions specified by the weighting variables while disturbing the overall data as little as possible. Participants were grouped into three age groups; 18–24 years, 25–34 years, and 35–45 years. Frequencies and proportions were used to describe the range of categorical responses and comparisons of proportions were made by chi-square test. P< .05 was considered statistically significant.
RESULTS A total of 18,910 telephone calls were attempted. The proportion that could not be reached (answering machine, engaged, no answer, incoming call restrictions, disconnected number, or not a residential number); where the respondent was not eligible; or where the respondent had insufficient English lan504
guage to complete the interview was 68.9%, 15.6%, and 2.1%, respectively. Of the 2,535 eligible respondents, 2,073 refused to participate, and 462 (18.2%) completed the interview. The three most common reasons for refusal were that the person was not interested, hung up before a reason could be ascertained, or was too busy. The majority of interviews were achieved using cell phone numbers (76%, n ¼ 352), with 24% (n ¼ 110) achieved using landline numbers. Of the respondents, 253 (55%) were women, and 209 (45%) were men. The number of participants in the age groups 18–24 years, 25–34 years, and 35 to 45 years was 196 (42%), 181 (39%), and 85 (18%), respectively. The sociodemographic characteristics of the participants are shown in Table 1. When asked to rate knowledge with reference to what they had learned at school on fertility-related topics, the majority of respondents reported ‘‘good knowledge’’ about prevention of pregnancy (64%), safe sex and STIs (62%), and the biology of reproduction (59%). However, much smaller proportions reported acquiring ‘‘good knowledge’’ regarding protection of fertility (38%), and the influence of age (30%), weight (18%), and smoking (38%) on fertility. Respondents aged 18–24 years were statistically significantly more likely than those aged 35–45 years to state that they had acquired ‘‘good knowledge’’ through school about the impact on fertility of age (47% vs. 18%, P< .001), weight (29% vs. 7%, P< .001), and smoking (55% vs. 21%, P< .001). Participants' beliefs about the age when female and male fertility starts to decline are shown in Tables 2 and 3, respectively. Only about one quarter (26%) of participants realized that a woman's fertility starts to decline before the age of 35. Taken together, 42% stated that female fertility starts to decline after the age of 40, ‘‘Age doesn't matter,’’ or ‘‘Don't know.’’ Men were more likely than women to provide one of these answers (51% vs. 33%, P< .001). A statistically significantly higher proportion of those who had not completed secondary school than those with more education responded that a woman's age does not impact on fertility (19% vs. 2%, P< .001). One third (33%) of participants accurately identified that male fertility starts to decline before age 45, but 58% responded that men's
TABLE 1 Sociodemographic characteristics of survey participants (n [ 462). Age, y, mean (SD) Place of residence % Metropolitan Regional/rural/remote Level of education % 10 years or less of schooling Completed secondary school (year 12) Post-school diploma or trade certificate University degree Did not respond Relationship status % Married/de facto (including 2% same-sex) In a relationship but not living together (including 1% same-sex) Not currently in a relationship Have one or more children, %
27.30 (6.79) 73 27 13 37 28 18 4 49 11 39 30
Hammarberg. Fertility awareness among Australians. Fertil Steril 2013.
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Fertility and Sterility®
TABLE 2 Age when female fertility starts to decline: participant responses (%). Age <35 35–39 40–44 R45 ‘‘Age doesn't matter’’ or ‘‘Don't know’’ a
a
All
Women
Men
26 32 18 13 11
31 36 17 9 7
20 29 20 18 13
DISCUSSION
Correct answer.
Hammarberg. Fertility awareness among Australians. Fertil Steril 2013.
fertility does not start to decline until after the age of 50, ‘‘Age doesn't matter,’’ or ‘‘Don't know.’’ Overall, 59% of respondents agreed that female obesity and smoking influence a woman's fertility ‘‘a lot,’’ but fewer believed that male obesity (30%) or smoking (36%) influence men's fertility ‘‘a lot.’’ Higher proportions of men than women believed that male obesity and smoking have ‘‘no influence at all’’ on fertility (25% vs. 13%, P¼ .001 and 15% vs. 7%, P¼ .02, respectively). Those with less than 12 years of education were less likely than those with higher levels of education to state that female smoking influences fertility ‘‘a lot’’ (41% vs. 61%, P< .001) and were more likely to believe that the male partner's smoking has ‘‘no influence at all’’ on fertility (24% vs. 9%, P< .001). When asked when in the menstrual cycle a woman is most likely to conceive, a third (32%) correctly identified the middle week between periods. Twenty-nine percent said the week just after her period, 18% in the week just before the next period, 7% almost any day except during her period, 2% during her period, and 12% said that they did not know. Over one third (39%) indicated that they had previously sought information on reproductive health matters. The most common method for seeking information was by using a general Internet search (58%), followed by speaking directly to a health professional (36%) and through books (21%). When asked to choose a single preferred method of all those used, the most popular was the Internet (48%), followed by health professionals (28%) and books (9%). There were few demographic variations in preferences; however, those in the 35–45 year age group were more likely than those aged 18–24 years to state that their preferred source of information was speaking to a health professional (45% vs. 17%, P< .001). Those who had not yet sought information on reproductive health matters were asked where they would look for such
TABLE 3 Age when male fertility starts to decline: participants' responses (%). Age
All
Women
Men
<45a 45–49 R50 ‘‘Age doesn't matter’’ or ‘‘Don't know’’
33 9 32 26
31 12 28 29
36 6 35 23
a
Correct answer.
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information should they need it. As with those who had sought information, the Internet (65%) and health professionals (29%) were the two most preferred sources whereas books did not rate as highly among those who had not actively sought information before (5%). The only notable demographic variation in responses was that females were more likely than males to approach a health professional to find information (47% vs. 17%, P< .001).
This study of a representative sample of Australians of reproductive age identified considerable knowledge gaps about potentially modifiable factors that influence fertility. The results add to existing evidence about lack of fertility awareness among university students (2, 4, 48), subfertile and pregnant women (24), childless women (23), and reproductive-aged women (22). Public education targeting these knowledge gaps could potentially reduce the risk of involuntary childlessness and people having fewer children than they plan to have. The findings of this survey will guide the Your Fertility public education activities. One of the strengths of this study is the inclusion of men. Contrary to popular belief, men expect and desire parenthood as much as women do (3, 49, 50). To optimize their chance of becoming fathers, men need to be aware of the factors that influence their own and their partner's fertility. Most studies gauging fertility awareness focus on women (22–25, 51). Because childbearing requires participation of both the female and male partner, involving men in conversations about fertility is imperative. Reproductive-health school education traditionally focuses on prevention of pregnancy and STIs. The finding that younger people were more likely than those in the oldest age group to recall learning about the adverse influence of age, obesity, and smoking on fertility at school suggests that the importance of protecting fertility has become part of some schools' curriculum in recent years. Although this is encouraging, even in the youngest age group only about half had learned that age and smoking negatively affect fertility, and less than one third that obesity influences fertility. Comprehensive sex education should include information about lifestyle factors that reduce fertility and ways to protect fertility. A woman's age is the single most important determinant of her chance of conceiving, but her partner's age also contributes (11). The majority of participants underestimated, by about 10 years, the age at which male and female fertility starts to decline. Not having a partner who is willing to have children prevents some women from having children during the most fertile years of their reproductive life (1, 26). For others, lack of awareness about the negative effect of age on fertility may result in delayed childbearing (25). The impact of female age on fertility was misjudged by 42% of participants, who thought that female fertility starts to decline after the age of 40 or that age does not affect fertility or who did not know about the relationship between female age and fertility. Men were less aware than women about the impact of a woman's age on her fertility. More than half provided responses that indicate lack of 505
ORIGINAL ARTICLE: INFERTILITY understanding about the limits of female reproductive life, which suggests that men should be targeted in education and information campaigns such as Your Fertility. General public knowledge about the impact of increasing male age on fertility has to our knowledge not previously been investigated. Although male age is a less significant factor in couple fertility than female age, it contributes to the chance of conception occurring (11). Almost one third of participants in this study stated that male fertility starts to decline after age 50, and more than a quarter said that age does not influence male fertility or that they did not know whether male fertility is affected by age. Taken together, this suggests that almost 60% of people underestimate the role of male age on fertility. More than 40% of participants were unaware that smoking and obesity significantly reduce women's fertility, and around two thirds were unaware that these factors also affect men's fertility. Smoking and obesity are lifestyle factors that are potentially amenable to change. In addition to informing about the risks to general health of obesity and smoking, health education and health promotion messages should include information about the adverse effects of smoking and obesity on women's and men's fertility. Only about one third of participants correctly identified the middle week between periods as the fertile time in the menstrual cycle. However, it could be argued that the response alternatives were ambiguous and that some of those who responded the week after the period were in fact aware of the fertile window. Nevertheless, around 40% of participants were clearly ill-informed about when in the menstrual cycle conception is most likely to occur. Therefore, one of the key messages of the Your Fertility education campaign is that knowledge about the fertile window can improve couples' chance of conceiving. Increasingly, people seek health information from the Internet (52). This was confirmed in this study where the majority stated that their preferred source of reproductive health information is the Internet. Therefore, the main platform for dissemination of fertility related information for the Your Fertility campaign will be the Web site www.yourfertility. org.au. Health promotion messages based on current evidence about the negative effects of age, obesity, and smoking on the chance of having a healthy baby, and the importance of knowing when in the menstrual cycle a woman is most likely to conceive are made available to the general public through this Web site and social networks. The Your Fertility Web site ranks second in a Google search of the word ‘‘fertility,’’ suggesting that its relevance to the search word and trustworthiness are considered high. The not-for-profit status and reputation of the Fertility Coalition partners and the scientifically based information contribute to this high ranking. A potential limitation of the study was the relatively low participation rate. As requests for information through unsolicited phone calls are becoming more common, they are increasingly being declined. According to the Pew Research Center, the response rate of a typical telephone survey has declined from 36% in 1997 to 9% in 2012 (53). The 18% response rate achieved in this survey suggests that the topic may have been perceived as more relevant and important 506
than some other survey topics. Despite diminishing response rates, telephone surveys that include landlines and cell phones and are weighted to match the demographic composition of the population continue to provide accurate information about the surveyed populations (53). In conclusion, a large proportion of people of reproductive age in Australia have a considerable knowledge gap relating to the potentially modifiable factors that affect fertility. A broad-based approach is needed to improve knowledge in this area and should include: information about fertility protection in sex education and other reproductive health curricula; health care providers gauging people's childbearing intentions and desires, providing information that can help them realize their goals (54, 55); and promotion of factual and accessible information through public education initiatives such as Your Fertility.
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Knowledge about factors that influence fertility among Australians of reproductive age: a population-based survey Karin Hammarberg, Ph.D.,a,b Tracey Setter, M.P.H.,a Robert J. Norman, M.D.,c Carol A. Holden, Ph.D.,d Janet Michelmore, Dip.Ed.,e and Louise Johnson, Dip.Ed.a a Victorian Assisted Reproductive Treatment Authority, Melbourne, Victoria; b Jean Hailes Research Unit, School of Public Health and Preventive Medicine, Monash University, Clayton, Victoria; c Robinson Institute, School of Paediatrics and Reproductive Health, University of Adelaide, North Adelaide, South Australia; d Andrology Australia, Monash Institute of Medical Research, Monash University, Clayton, South Australia; and e Jean Hailes Foundation for Women's Health, Clayton, Victoria, Australia
Objective: To explore knowledge about the effects on fertility of age, obesity, smoking, and timing of intercourse among Australians of reproductive age. Design: Telephone survey of a representative sample of Australians. Setting: Not applicable. Patient(s): Australians aged 18 to 45 years who wish to have a child or another child now or in the future. Intervention(s): None. Main Outcome Measure(s): Knowledge about the effect on fertility of age, obesity, smoking, and timing of intercourse. Result(s): A total of 462 interviews were conducted. The majority of respondents underestimated, by about 10 years, the age at which male and female fertility starts to decline. Only one in four correctly identified that female fertility starts to decline before age 35, and one in three identified that male fertility starts to decline before age 45. Most (59%) were aware that female obesity and smoking affect fertility, but fewer recognized that male obesity (30%) and smoking (36%) also influence fertility. Almost 40% of respondents had inadequate knowledge of when in the menstrual cycle a woman is most likely to conceive. Conclusion(s): Considerable knowledge gaps about modifiable factors that affect fertility were identified. These are targeted in a national education campaign to promote awareness of factors Use your smartphone that influence fertility. (Fertil SterilÒ 2013;99:502–7. Ó2013 by American Society for Reproducto scan this QR code tive Medicine.) and connect to the Key Words: Age, education, fertility, obesity, smoking Discuss: You can discuss this article with its authors and with other ASRM members at http:// fertstertforum.com/hammarbergk-fertility-age-obesity-smoking-education/
M
ost people want and expect to have children at some stage of their life (1–5). For some,
reasons beyond their personal control prevent them from achieving this. For others, potentially preventable factors
Received August 27, 2012; revised October 2, 2012; accepted October 16, 2012; published online November 14, 2012. K.H. has nothing to disclose. T.S. has nothing to disclose. R.J.N. has received payment for lectures from Merck Serono. C.A.H. has received reimbursement from VARTA for participating in Your Fertility and payment from Pfizer for development of educational presentations. J.M. has nothing to disclose. L.J. has received funding for travel and administrative support from her employer, the Victorian Department of Health, payment from universities for development of educational presentations, and is a member of the Occupational Therapy Board of Australia. Supported by the Australian Government Department of Health and Ageing, Population Health Programs Branch, Family Planning Grants Program. Reprint requests: Karin Hammarberg, Ph.D., Jean Hailes Research Unit, School of Public Health and Preventive Medicine, Monash University, Level 1 43–51 Kanooka Grove, Clayton 3168, Victoria, Australia (E-mail: [email protected]). Fertility and Sterility® Vol. 99, No. 2, February 2013 0015-0282/$36.00 Copyright ©2013 American Society for Reproductive Medicine, Published by Elsevier Inc. http://dx.doi.org/10.1016/j.fertnstert.2012.10.031 502
discussion forum for this article now.*
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reduce their chances of realizing this life goal. We set out to survey Australians of reproductive age about their understanding of the impact of age, weight, smoking, and timing of sex on fertility. There is reliable evidence of the negative effects on fertility and obstetric outcomes of increasing maternal and paternal age (6–15). For a diverse range of reasons, including access to effective contraception and improved education and employment opportunities for women, the age of childbearing in Australia and other high-income countries has increased in the last few decades VOL. 99 NO. 2 / FEBRUARY 2013
Fertility and Sterility® (14, 16, 17). This in turn has led to increasing rates of age-related infertility, more people seeking assisted reproductive technology (ART) treatment to conceive, and some people having fewer children than they had planned (8, 14, 17). Statistically, women's fecundity starts to decline around age 30 and by age 35 the decline accelerates (18). The age of the male partner influences semen quality and fertility (9, 19, 20). It is apparent that many underestimate the influence of increasing female and male age on the chance of conceiving and having a healthy baby (4, 14, 17, 21–25). This combined with the belief that ART can overcome age-related infertility may result in a missed opportunity to have biological children (23–26). There is also consistent evidence of the adverse effects of being overweight and smoking on fertility, obstetric outcomes, and the health of the baby at birth and in the future (27–37). In high-income and middle-income countries, the rates of overweight (body mass index [BMI] R25) and obesity (BMI R30) are increasing (38–40). Rates of smoking vary between countries, but in Australia in 2008 one in five people of reproductive age were smokers (41). Most people are aware of the negative effects of obesity and smoking on general health, but research suggests that the adverse effects of these lifestyle factors on fertility, obstetric outcomes, and neonatal and long-term health of children are poorly understood (23, 42, 43). Little is known about the level of understanding among people of reproductive age about when in the menstrual cycle a woman is most likely to conceive. It has been suggested that educating couples about the fertile window in the menstrual cycle is a simple and inexpensive way to increase the chance of conception for those who wish to have children (44–46). To allow people to make well-informed decisions about family formation, prevent the personal suffering associated with infertility and adverse obstetric and perinatal outcomes, and reduce the health-care costs of treating infertility, pregnancy, and neonatal complications, awareness about modifiable factors that affect fertility is essential. We explored the extent of knowledge among the general population of Australian women and men of reproductive age about the effects of age, obesity, smoking, and timing of intercourse on the chance of conceiving.
MATERIALS AND METHODS The study was approved by the Research and Ethics Committee of the State Government of Victoria's Department of Human Services.
Setting The Victorian Assisted Reproductive Treatment Authority (VARTA) in the state of Victoria, Australia, is a statutory authority responsible for administering aspects of the Assisted Reproductive Treatment Act of 2008 (Victoria) (47). One of its roles is to provide public education and resources for the community and health professionals on matters relating to fertility and ART. In 2011, the project Your Fertility was initiated by VARTA and its partners in the Fertility Coalition: the Jean Hailes Foundation for Women's Health VOL. 99 NO. 2 / FEBRUARY 2013
(www.jeanhailes.org.au), Andrology Australia (www.andro logyaustralia.org), and the Robinson Institute at the University of Adelaide (www.adelaide.edu.au/robinson-institute). The aim of Your Fertility is to promote awareness of factors that influence fertility so that individuals and couples can make informed and timely decisions regarding childbearing and to prevent infertility and involuntary childlessness. To guide the development of educational material and other project activities, the need to ascertain existing knowledge gaps was identified.
Participants Men and women aged 18 to 45 years, living in Australia, wishing to have a child or an additional child now or in the future, and with sufficient English language proficiency to participate in a telephone survey (script available online as Supplemental Material) were eligible to participate.
Method The Social Research Centre (SRC, www.srcentre.com.au) conducts quantitative and qualitative research across all areas of social and health research for academic institutions, government, and nonprofit and corporate organizations. The SRC was contracted to conduct a telephone survey about fertility awareness with a representative sample of the Australian population who fulfilled the inclusion criteria. Telephone access among adult Australians is almost universal. Traditional telephone surveying, using randomly generated landline numbers, has in recent years become less accurate at reaching the general population due to an increasing incidence of households with no landline (cell phone only), particularly among those younger than 40 years. To ensure a representative sample, a split sample technique was employed that covered randomly generated landline numbers and randomly generated cell phone numbers. This split sample ensures full coverage of the Australian population. The best practice error margin for social research is 5% (at 95% confidence level). This means that the target sample size needs to be large enough so that if, for example, 50% of the sample answer ‘‘yes’’ to a question, we can be confident (to a level of 95%) that the actual figure in a census would average between 45% and 55%. The optimum sample size to achieve this 5% error margin on any population over 1 million is n ¼ 385. To meet industry standard error margins, a sample of at least 385 was needed for this study. To enable interviews to be achieved with hard-to-reach individuals, an unlimited call cycle was used (numbers where there was no response were tried more than seven times), and the call times included evenings and weekends.
Materials Based on existing literature and the aim of the Your Fertility education campaign, a questionnaire gauging knowledge about the influence of age, obesity, smoking, and timing of sex was devised. It also included questions about sociodemographics and fertility, reproductive-health school education, and preferred sources of reproductive health-related information. The professional interviewers assigned to this project 503
ORIGINAL ARTICLE: INFERTILITY attended a 2-hour briefing session that covered the project's background, objectives, and procedures as well as all aspects of administering the survey questionnaire. A pilot comprising 30 interviews was conducted, and the only change arising from the pilot testing was a minor wording change for grammatical clarity. The interview took 10 to 12 minutes to complete. The perceived adequacy of knowledge learnt at school about prevention of pregnancy, safe sex, and sexually transmitted infections (STIs), the biology of reproduction, protection of fertility, and the influence of age, weight, and smoking was rated by respondents as ‘‘good knowledge,’’ ‘‘some knowledge,’’ ‘‘poor knowledge,’’ and ‘‘was not taught.’’ The response alternatives for perceived influence on fertility of male and female obesity and smoking were: ‘‘a lot,’’ ‘‘a little,’’ ‘‘not at all,’’ or ‘‘don't know’’; at what age men's and women's fertility starts to decline: 20–24, 25–29, 30–34, 35–39, 40–44, 45–49, R50, ‘‘age doesn't matter,’’ or ‘‘don't know’’; knowledge about the most fertile time in the menstrual cycle: ‘‘in the middle week between periods,’’ ‘‘in the week just after her period,’’ ‘‘in the week just before her next period,’’ ‘‘almost any day except during her period,’’ ‘‘during her period,’’ or ‘‘don't know’’; whether the respondent had sought information on reproductive health matters: ‘‘yes’’ or ‘‘no’’; and preferred sources of information about reproductive matters: ‘‘Internet,’’ ‘‘health professional,’’ ‘‘books,’’ ‘‘family,’’ ‘‘school/university,’’ ‘‘friends,’’ ‘‘TV,’’ or ‘‘other.’’
Data Management and Analysis Data were entered in SPSS for Windows, release 18.00 (SPSS, Inc.) and weighted by age, gender, level of education, country of birth, location (state), and type of telephone (landline or cell phone) to ensure that it was proportionally representative of the Australian population. The calculation of the poststratification weighting factors was undertaken using a ‘‘rim weighting’’ approach, sometimes referred to as iterative proportional fitting. This technique was used to adjust for the disproportionate nature of the sample and differential survey response rates across age, gender, educational attainment, country of birth, location, and telephony status. The sample was weighted to independent population benchmarks. The weights created by ‘‘rim weighting’’ were created using a statistical regression approach which seeks to achieve the ‘‘best fit’’ possible with the population proportions specified by the weighting variables while disturbing the overall data as little as possible. Participants were grouped into three age groups; 18–24 years, 25–34 years, and 35–45 years. Frequencies and proportions were used to describe the range of categorical responses and comparisons of proportions were made by chi-square test. P< .05 was considered statistically significant.
RESULTS A total of 18,910 telephone calls were attempted. The proportion that could not be reached (answering machine, engaged, no answer, incoming call restrictions, disconnected number, or not a residential number); where the respondent was not eligible; or where the respondent had insufficient English lan504
guage to complete the interview was 68.9%, 15.6%, and 2.1%, respectively. Of the 2,535 eligible respondents, 2,073 refused to participate, and 462 (18.2%) completed the interview. The three most common reasons for refusal were that the person was not interested, hung up before a reason could be ascertained, or was too busy. The majority of interviews were achieved using cell phone numbers (76%, n ¼ 352), with 24% (n ¼ 110) achieved using landline numbers. Of the respondents, 253 (55%) were women, and 209 (45%) were men. The number of participants in the age groups 18–24 years, 25–34 years, and 35 to 45 years was 196 (42%), 181 (39%), and 85 (18%), respectively. The sociodemographic characteristics of the participants are shown in Table 1. When asked to rate knowledge with reference to what they had learned at school on fertility-related topics, the majority of respondents reported ‘‘good knowledge’’ about prevention of pregnancy (64%), safe sex and STIs (62%), and the biology of reproduction (59%). However, much smaller proportions reported acquiring ‘‘good knowledge’’ regarding protection of fertility (38%), and the influence of age (30%), weight (18%), and smoking (38%) on fertility. Respondents aged 18–24 years were statistically significantly more likely than those aged 35–45 years to state that they had acquired ‘‘good knowledge’’ through school about the impact on fertility of age (47% vs. 18%, P< .001), weight (29% vs. 7%, P< .001), and smoking (55% vs. 21%, P< .001). Participants' beliefs about the age when female and male fertility starts to decline are shown in Tables 2 and 3, respectively. Only about one quarter (26%) of participants realized that a woman's fertility starts to decline before the age of 35. Taken together, 42% stated that female fertility starts to decline after the age of 40, ‘‘Age doesn't matter,’’ or ‘‘Don't know.’’ Men were more likely than women to provide one of these answers (51% vs. 33%, P< .001). A statistically significantly higher proportion of those who had not completed secondary school than those with more education responded that a woman's age does not impact on fertility (19% vs. 2%, P< .001). One third (33%) of participants accurately identified that male fertility starts to decline before age 45, but 58% responded that men's
TABLE 1 Sociodemographic characteristics of survey participants (n [ 462). Age, y, mean (SD) Place of residence % Metropolitan Regional/rural/remote Level of education % 10 years or less of schooling Completed secondary school (year 12) Post-school diploma or trade certificate University degree Did not respond Relationship status % Married/de facto (including 2% same-sex) In a relationship but not living together (including 1% same-sex) Not currently in a relationship Have one or more children, %
27.30 (6.79) 73 27 13 37 28 18 4 49 11 39 30
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Fertility and Sterility®
TABLE 2 Age when female fertility starts to decline: participant responses (%). Age <35 35–39 40–44 R45 ‘‘Age doesn't matter’’ or ‘‘Don't know’’ a
a
All
Women
Men
26 32 18 13 11
31 36 17 9 7
20 29 20 18 13
DISCUSSION
Correct answer.
Hammarberg. Fertility awareness among Australians. Fertil Steril 2013.
fertility does not start to decline until after the age of 50, ‘‘Age doesn't matter,’’ or ‘‘Don't know.’’ Overall, 59% of respondents agreed that female obesity and smoking influence a woman's fertility ‘‘a lot,’’ but fewer believed that male obesity (30%) or smoking (36%) influence men's fertility ‘‘a lot.’’ Higher proportions of men than women believed that male obesity and smoking have ‘‘no influence at all’’ on fertility (25% vs. 13%, P¼ .001 and 15% vs. 7%, P¼ .02, respectively). Those with less than 12 years of education were less likely than those with higher levels of education to state that female smoking influences fertility ‘‘a lot’’ (41% vs. 61%, P< .001) and were more likely to believe that the male partner's smoking has ‘‘no influence at all’’ on fertility (24% vs. 9%, P< .001). When asked when in the menstrual cycle a woman is most likely to conceive, a third (32%) correctly identified the middle week between periods. Twenty-nine percent said the week just after her period, 18% in the week just before the next period, 7% almost any day except during her period, 2% during her period, and 12% said that they did not know. Over one third (39%) indicated that they had previously sought information on reproductive health matters. The most common method for seeking information was by using a general Internet search (58%), followed by speaking directly to a health professional (36%) and through books (21%). When asked to choose a single preferred method of all those used, the most popular was the Internet (48%), followed by health professionals (28%) and books (9%). There were few demographic variations in preferences; however, those in the 35–45 year age group were more likely than those aged 18–24 years to state that their preferred source of information was speaking to a health professional (45% vs. 17%, P< .001). Those who had not yet sought information on reproductive health matters were asked where they would look for such
TABLE 3 Age when male fertility starts to decline: participants' responses (%). Age
All
Women
Men
<45a 45–49 R50 ‘‘Age doesn't matter’’ or ‘‘Don't know’’
33 9 32 26
31 12 28 29
36 6 35 23
a
Correct answer.
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information should they need it. As with those who had sought information, the Internet (65%) and health professionals (29%) were the two most preferred sources whereas books did not rate as highly among those who had not actively sought information before (5%). The only notable demographic variation in responses was that females were more likely than males to approach a health professional to find information (47% vs. 17%, P< .001).
This study of a representative sample of Australians of reproductive age identified considerable knowledge gaps about potentially modifiable factors that influence fertility. The results add to existing evidence about lack of fertility awareness among university students (2, 4, 48), subfertile and pregnant women (24), childless women (23), and reproductive-aged women (22). Public education targeting these knowledge gaps could potentially reduce the risk of involuntary childlessness and people having fewer children than they plan to have. The findings of this survey will guide the Your Fertility public education activities. One of the strengths of this study is the inclusion of men. Contrary to popular belief, men expect and desire parenthood as much as women do (3, 49, 50). To optimize their chance of becoming fathers, men need to be aware of the factors that influence their own and their partner's fertility. Most studies gauging fertility awareness focus on women (22–25, 51). Because childbearing requires participation of both the female and male partner, involving men in conversations about fertility is imperative. Reproductive-health school education traditionally focuses on prevention of pregnancy and STIs. The finding that younger people were more likely than those in the oldest age group to recall learning about the adverse influence of age, obesity, and smoking on fertility at school suggests that the importance of protecting fertility has become part of some schools' curriculum in recent years. Although this is encouraging, even in the youngest age group only about half had learned that age and smoking negatively affect fertility, and less than one third that obesity influences fertility. Comprehensive sex education should include information about lifestyle factors that reduce fertility and ways to protect fertility. A woman's age is the single most important determinant of her chance of conceiving, but her partner's age also contributes (11). The majority of participants underestimated, by about 10 years, the age at which male and female fertility starts to decline. Not having a partner who is willing to have children prevents some women from having children during the most fertile years of their reproductive life (1, 26). For others, lack of awareness about the negative effect of age on fertility may result in delayed childbearing (25). The impact of female age on fertility was misjudged by 42% of participants, who thought that female fertility starts to decline after the age of 40 or that age does not affect fertility or who did not know about the relationship between female age and fertility. Men were less aware than women about the impact of a woman's age on her fertility. More than half provided responses that indicate lack of 505
ORIGINAL ARTICLE: INFERTILITY understanding about the limits of female reproductive life, which suggests that men should be targeted in education and information campaigns such as Your Fertility. General public knowledge about the impact of increasing male age on fertility has to our knowledge not previously been investigated. Although male age is a less significant factor in couple fertility than female age, it contributes to the chance of conception occurring (11). Almost one third of participants in this study stated that male fertility starts to decline after age 50, and more than a quarter said that age does not influence male fertility or that they did not know whether male fertility is affected by age. Taken together, this suggests that almost 60% of people underestimate the role of male age on fertility. More than 40% of participants were unaware that smoking and obesity significantly reduce women's fertility, and around two thirds were unaware that these factors also affect men's fertility. Smoking and obesity are lifestyle factors that are potentially amenable to change. In addition to informing about the risks to general health of obesity and smoking, health education and health promotion messages should include information about the adverse effects of smoking and obesity on women's and men's fertility. Only about one third of participants correctly identified the middle week between periods as the fertile time in the menstrual cycle. However, it could be argued that the response alternatives were ambiguous and that some of those who responded the week after the period were in fact aware of the fertile window. Nevertheless, around 40% of participants were clearly ill-informed about when in the menstrual cycle conception is most likely to occur. Therefore, one of the key messages of the Your Fertility education campaign is that knowledge about the fertile window can improve couples' chance of conceiving. Increasingly, people seek health information from the Internet (52). This was confirmed in this study where the majority stated that their preferred source of reproductive health information is the Internet. Therefore, the main platform for dissemination of fertility related information for the Your Fertility campaign will be the Web site www.yourfertility. org.au. Health promotion messages based on current evidence about the negative effects of age, obesity, and smoking on the chance of having a healthy baby, and the importance of knowing when in the menstrual cycle a woman is most likely to conceive are made available to the general public through this Web site and social networks. The Your Fertility Web site ranks second in a Google search of the word ‘‘fertility,’’ suggesting that its relevance to the search word and trustworthiness are considered high. The not-for-profit status and reputation of the Fertility Coalition partners and the scientifically based information contribute to this high ranking. A potential limitation of the study was the relatively low participation rate. As requests for information through unsolicited phone calls are becoming more common, they are increasingly being declined. According to the Pew Research Center, the response rate of a typical telephone survey has declined from 36% in 1997 to 9% in 2012 (53). The 18% response rate achieved in this survey suggests that the topic may have been perceived as more relevant and important 506
than some other survey topics. Despite diminishing response rates, telephone surveys that include landlines and cell phones and are weighted to match the demographic composition of the population continue to provide accurate information about the surveyed populations (53). In conclusion, a large proportion of people of reproductive age in Australia have a considerable knowledge gap relating to the potentially modifiable factors that affect fertility. A broad-based approach is needed to improve knowledge in this area and should include: information about fertility protection in sex education and other reproductive health curricula; health care providers gauging people's childbearing intentions and desires, providing information that can help them realize their goals (54, 55); and promotion of factual and accessible information through public education initiatives such as Your Fertility.
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