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ORIGINAL ARTICLES: INFERTILITYM of their life (15). For some, others, potentially preventable factors Australians of reproductive age abotheir understanding of the impactage, weight, smoking, and timingsex on fertility.

There is reliable evidence of the neative effects on fertility and obstetroutcomes of increasing maternal anpaternal age (615). For a diverse ranof reasons, including access to effecticontraception and improved educatioand employment opportunities fwomen, the age of childbearing

Received August 27, 2012; revised October 2, 2012; accepted October 16, 2012; published onlineNovember 14, 2012.

K.H. has nothing to disclose. T.S. has nothing to disclose. R.J.N. has received payment for lectures fromMerck Serono. C.A.H. has received reimbursement from VARTA for participating in Your Fertilityand payment from Pzer for development of educational presentations. J.M. has nothing todisclose. L.J. has received funding for travel and administrative support from her employer,the Victorian Department of Health, payment from universities for development of educationalpresentations, and is a member of the Occupational Therapy Board of Australia.

Supported by the Australian Government Department of Health and Ageing, Population Health Pro-grams Branch, Family Planning Grants Program.

Reprint requests: Karin Hammarberg, Ph.D., Jean Hailes Research Unit, School of Public Health andPreventive Medicine, Monash University, Level 1 4351 Kanooka Grove, Clayton 3168, Victoria,Australia (E-mail: karin.hammarberg@monash.edu).fertstertforum.com/hammarbergk-fertility-age-obesity-smoking-education/* Download a free QR code scanner by sscanner in your smartphones app stor

ost peoplewant and expect tohave children at some stage

reasons beyond their personal controlprevent them from achieving this. For

reduce their chances ofthis life goal. We set outDesign: 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 whichmale and female fertility starts to decline. Only one in four correctly identied that female fertility starts to decline before age 35, andone in three identied that male fertility starts to decline before age 45. Most (59%) were aware that female obesity and smoking affectfertility, but fewer recognized that male obesity (30%) and smoking (36%) also inuence fertility. Almost 40% of respondents had in-adequate knowledge of when in the menstrual cycle a woman is most likely to conceive.Conclusion(s): Considerable knowledge gaps about modiable factors that affect fertility wereidentied. These are targeted in a national education campaign to promote awareness of factorsthat inuence fertility. (Fertil Steril 2013;99:5027.2013 by American Society for Reproduc-tive Medicine.)Key Words: Age, education, fertility, obesity, smoking

Use your smartphoneto scan this QR codeand connect to thediscussion forum forClayton, Victoria, Australia

Objective: To explore knowledge about the effects on fertility of age, obesity, smoking, and timinreproductive age.Reproductive Health, University of Adelaide, North Adelaide, South Australia; d Andrology Australia, Monash Instituteof Medical Research, Monash University, Clayton, South Australia; and e Jean Hailes Foundation for Women's Health,Health and Preventive Medicine, Monash University, Clayton, Victoria; c Robinson Institute, School of Paediatrics anda Victorian Assisted Reproductive Treatment Authority, Melbourne, Victoria; b Jean Hailes Research Unit, School of PublicJanet Michelmore, Dip.Ed.,e and Louise Johnson, Dip.Ed.a

Karin Hammarberg, Ph.D.,a,b Tracey SFertility and Sterility Vol. 99, No. 2, February 2013Copyright 2013 American Society for Reproductivehttp://dx.doi.org/10.1016/j.fertnstert.2012.10.031

502er, M.P.H.,a Robert J. Norman, M.D.,c C0015-0282/$36.00Medicine, Published by Elsevier Inc.hatustralians

l A. Holden, Ph.D.,dAustralia and other high-income coun-tries has increased in the last fewdecades

VOL. 99 NO. 2 / FEBRUARY 2013

female and male age on the chance of conceiving and having

a healthy baby (4, 14, 17, 2125). This combined with thebelief that ART can overcome age-related infertility may resultin a missed opportunity to have biological children (2326).

There is also consistent evidence of the adverse effects ofbeing overweight and smoking on fertility, obstetric out-comes, and the health of the baby at birth and in the future(2737). In high-income and middle-income countries, therates of overweight (body mass index [BMI]R25) and obesity(BMI R30) are increasing (3840). Rates of smoking varybetween countries, but in Australia in 2008 one in vepeople of reproductive age were smokers (41). Most peopleare aware of the negative effects of obesity and smoking ongeneral health, but research suggests that the adverseeffects of these lifestyle factors on fertility, obstetricoutcomes, and neonatal and long-term health of childrenare poorly understood (23, 42, 43).

Little is known about the level of understanding amongpeople of reproductive age about when in the menstrualcycle a woman is most likely to conceive. It has been sug-gested that educating couples about the fertile window inthe menstrual cycle is a simple and inexpensive way to in-crease the chance of conception for those who wish to havechildren (4446).

To allow people to make well-informed decisions aboutfamily formation, prevent the personal suffering associatedwith infertility and adverse obstetric and perinatal outcomes,and reduce the health-care costs of treating infertility, preg-nancy, and neonatal complications, awareness about modi-able factors that affect fertility is essential. We explored theextent of knowledge among the general population of Austra-lian women and men of reproductive age about the effects ofage, obesity, smoking, and timing of intercourse on thechance of conceiving.

MATERIALS AND METHODSThe study was approved by the Research and Ethics Commit-tee of the State Government of Victoria's Department of Hu-man Services.

Setting

The Victorian Assisted Reproductive Treatment Authority(VARTA) in the state of Victoria, Australia, is a statutory au-thority responsible for administering aspects of the AssistedReproductive Treatment Act of 2008 (Victoria) (47). One ofits roles is to provide public education and resources for thecommunity and health professionals on matters relating tofertility and ART. In 2011, the project Your Fertility was(14, 16, 17). This in turnhas led to increasing rates of age-relatedinfertility, more people seeking assisted reproductive technol-ogy (ART) treatment to conceive, and somepeople having fewerchildren than they had planned (8, 14, 17). Statistically,women's fecundity starts to decline around age 30 and by age35 the decline accelerates (18). The age of the male partnerinuences semen quality and fertility (9, 19, 20). It isapparent that many underestimate the inuence of increasinginitiated by VARTA and its partners in the FertilityCoalition: the Jean Hailes Foundation for Women's Health

VOL. 99 NO. 2 / FEBRUARY 2013(www.jeanhailes.org.au), Andrology Australia (www.andrologyaustralia.org), and the Robinson Institute at the Univer-sity of Adelaide (www.adelaide.edu.au/robinson-institute).The aim of Your Fertility is to promote awareness of factorsthat inuence fertility so that individuals and couples canmake informed and timely decisions regarding childbearingand to prevent infertility and involuntary childlessness. Toguide the development of educational material and other pro-ject activities, the need to ascertain existing knowledge gapswas identied.

Participants

Men and women aged 18 to 45 years, living in Australia,wishing to have a child or an additional child now or in thefuture, and with sufcient English language prociency toparticipate in a telephone survey (script available online asSupplemental Material) were eligible to participate.

Method

The Social Research Centre (SRC, www.srcentre.com.au) con-ducts quantitative and qualitative research across all areas ofsocial and health research for academic institutions, govern-ment, and nonprot and corporate organizations. The SRCwas contracted to conduct a telephone survey about fertilityawareness with a representative sample of the Australianpopulation who fullled the inclusion criteria.

Telephone access among adult Australians is almost uni-versal. Traditional telephone surveying, using randomly gen-erated landline numbers, has in recent years become lessaccurate at reaching the general population due to an increas-ing incidence of households with no landline (cell phoneonly), particularly among those younger than 40 years. Toensure a representative sample, a split sample techniquewas employed that covered randomly generated landlinenumbers and randomly generated cell phone numbers. Thissplit sample ensures full coverage of the Australian popula-tion. The best practice error margin for social research is5% (at 95% condence level). This means that the targetsample size needs to be large enough so that if, for example,50% of the sample answer yes to a question, we can be con-dent (to a level of 95%) that the actual gure in a censuswould average between 45% and 55%. The optimum samplesize to achieve this 5% error margin on any populationover 1 million is n 385. To meet industry standard errormargins, a sample of at least 385 was needed for this study.To enable interviews to be achieved with hard-to-reach indi-viduals, an unlimited call cycle was used (numbers wherethere 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 Fertilityeducation campaign, a questionnaire gauging knowledgeabout the inuence of age, obesity, smoking, and timing ofsex was devised. It also included questions about sociodemo-graphics and fertility, reproductive-health school education,

Fertility and Sterilityand preferred sources of reproductive health-related informa-tion. The professional interviewers assigned to this project

503

Data Management and Analysis

guage to complete the interview was 68.9%, 15.6%, and 2.1%,respectively. Of the 2,535 eligible respondents, 2,073 refusedto participate, and 462 (18.2%) completed the interview. Thethree most common reasons for refusal were that the personwas not interested, hung up before a reason could be ascer-tained, or was too busy. The majority of interviews wereachieved using cell phone numbers (76%, n 352), with24% (n 110) achieved using landline numbers. Of the re-spondents, 253 (55%) were women, and 209 (45%) weremen. The number of participants in the age groups 1824years, 2534 years, and 35 to 45 years was 196 (42%), 181(39%), and 85 (18%), respectively. The sociodemographiccharacteristics of the participants are shown in Table 1.

When asked to rate knowledge with reference to whatthey had learned at school on fertility-related topics, the ma-jority of respondents reported good knowledge about pre-Data were entered in SPSS for Windows, release 18.00 (SPSS,Inc.) and weighted by age, gender, level of education, countryof birth, location (state), and type of telephone (landline or cellphone) to ensure that it was proportionally representative ofthe Australian population. The calculation of the poststrati-cation weighting factors was undertaken using a rimweight-ing approach, sometimes referred to as iterative proportionaltting. This technique was used to adjust for the dispropor-tionate nature of the sample and differential survey responserates across age, gender, educational attainment, country ofbirth, location, and telephony status. The sample wasweighted to independent population benchmarks. Theweights created by rim weighting were created using a sta-tistical regression approach which seeks to achieve the bestt possible with the population proportions specied bythe weighting variables while disturbing the overall data aslittle as possible. Participants were grouped into three agegroups; 1824 years, 2534 years, and 3545 years. Frequen-cies and proportions were used to describe the range of cate-gorical responses and comparisons of proportions were madeby chi-square test. P< .05 was considered statisticallysignicant.

RESULTSA total of 18,910 telephone calls were attempted. The propor-tion that could not be reached (answering machine, engaged,no answer, incoming call restrictions, disconnected number,attended a 2-hour brieng session that covered the project'sbackground, objectives, and procedures as well as all aspectsof administering the survey questionnaire. A pilot comprising30 interviews was conducted, and the only change arisingfrom the pilot testing was a minor wording change for gram-matical clarity. The interview took 10 to 12 minutes tocomplete.

The perceived adequacy of knowledge learnt at schoolabout prevention of pregnancy, safe sex, and sexually trans-mitted infections (STIs), the biology of reproduction, protec-tion of fertility, and the inuence of age, weight, andsmoking was rated by respondents as good knowledge,some knowledge, poor knowledge, and was not taught.The response alternatives for perceived inuence on fertilityof male and female obesity and smoking were: a lot, a lit-tle, not at all, or don't know; at what age men's andwomen's fertility starts to decline: 2024, 2529, 3034,3539, 4044, 4549, R50, age doesn't matter, or don'tknow; knowledge about the most fertile time in the men-strual cycle: in the middle week between periods, in theweek just after her period, in the week just before hernext period, almost any day except during her period,during her period, or don't know; whether the respondenthad sought information on reproductive health matters: yesor no; and preferred sources of information about reproduc-tive matters: Internet, health professional, books, fam-ily, school/university, friends, TV, or other.

ORIGINAL ARTICLE: INFERTILITYor not a residential number); where the respondent was noteligible; or where the respondent had insufcient English lan-

504vention of pregnancy (64%), safe sex and STIs (62%), andthe biology of reproduction (59%). However, much smallerproportions reported acquiring good knowledge regardingprotection of fertility (38%), and the inuence of age (30%),weight (18%), and smoking (38%) on fertility. Respondentsaged 1824 years were statistically signicantly more likelythan those aged 3545 years to state that they had acquiredgood knowledge through school about the impact on fertil-ity 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 malefertility starts to decline are shown in Tables 2 and 3,respectively. Only about one quarter (26%) of participantsrealized that a woman's fertility starts to decline before theage of 35. Taken together, 42% stated that female fertilitystarts to decline after the age of 40, Age doesn't matter, orDon't know. Men were more likely than women toprovide one of these answers (51% vs. 33%, P< .001). Astatistically signicantly higher proportion of those whohad not completed secondary school than those with moreeducation responded that a woman's age does not impacton fertility (19% vs. 2%, P< .001). One third (33%) ofparticipants accurately identied that male fertility starts todecline before age 45, but 58% responded that men's

TABLE 1

Sociodemographic characteristics of survey participants (n[ 462).

Age, y, mean (SD) 27.30 (6.79)Place of residence %Metropolitan 73Regional/rural/remote 27

Level of education %10 years or less of schooling 13Completed secondary school (year 12) 37Post-school diploma or trade certicate 28University degree 18Did not respond 4

Relationship status %Married/de facto (including 2% same-sex) 49In a relationship but not living together

(including 1% same-sex)11

Not currently in a relationship 39

Have one or more children, % 30Hammarberg. Fertility awareness among Australians. Fertil Steril 2013.

VOL. 99 NO. 2 / FEBRUARY 2013

TABLE 2

Agewhen female fertility starts to decline: participant responses (%).

Age All Women Men

2000;15:17038.understanding about the limits of female reproductive life,which suggests that men should be targeted in educationand information campaigns such as Your Fertility. Generalpublic knowledge about the impact of increasing male ageon fertility has to our knowledge not previously beeninvestigated. Although male age is a less signicant factorin couple fertility than female age, it contributes to thechance of conception occurring (11). Almost one third ofparticipants in this study stated that male fertility starts todecline after age 50, and more than a quarter said that agedoes not inuence male fertility or that they did not knowwhether male fertility is affected by age. Taken together,this suggests that almost 60% of people underestimate therole of male age on fertility.

More than 40% of participants were unaware that smok-ing and obesity signicantly reduce women's fertility, andaround two thirds were unaware that these factors also affectmen's fertility. Smoking and obesity are lifestyle factors thatare potentially amenable to change. In addition to informingabout the risks to general health of obesity and smoking,health education and health promotion messages should in-clude information about the adverse effects of smoking andobesity on women's and men's fertility.

Only about one third of participants correctly identiedthe middle week between periods as the fertile time in themenstrual cycle. However, it could be argued that the re-sponse alternatives were ambiguous and that some of thosewho responded the week after the period were in fact awareof the fertile window. Nevertheless, around 40% of partici-pants were clearly ill-informed about when in the menstrualcycle conception is most likely to occur. Therefore, one ofthe key messages of the Your Fertility education campaignis that knowledge about the fertile window can improve cou-ples' chance of conceiving.

Increasingly, people seek health information from the In-ternet (52). This was conrmed in this study where the major-ity stated that their preferred source of reproductive healthinformation is the Internet. Therefore, the main platform fordissemination of fertility related information for the YourFertility campaign will be the Web site www.yourfertility.org.au. Health promotionmessages based on current evidenceabout the negative effects of age, obesity, and smoking on thechance of having a healthy baby, and the importance ofknowing when in the menstrual cycle a woman is most likelyto conceive are made available to the general public throughthis Web site and social networks. The Your Fertility Website ranks second in a Google search of the word fertility,suggesting that its relevance to the search word and trustwor-thiness are considered high. The not-for-prot status andreputation of the Fertility Coalition partners and the scientif-ically based information contribute to this high ranking.

A potential limitation of the study was the relatively lowparticipation rate. As requests for information through unso-licited phone calls are becoming more common, they areincreasingly being declined. According to the Pew ResearchCenter, the response rate of a typical telephone survey hasdeclined from 36% in 1997 to 9% in 2012 (53). The 18%

ORIGINAL ARTICLE: INFERTILITYresponse rate achieved in this survey suggests that the topicmay have been perceived as more relevant and important

50610. Fretts RC. Older women have increased risk of unexplained fetal deaths. BMJ2001;322:429.

11. Hassan MAM, Killick SR. Effect of male age on fertility: evidence for thedecline in male fertility with increasing age. Fertil Steril 2003;79:15207.

12. Jolly M, Sebire N, Harris J, Robinson S, Regan L. The risks associated withpregnancy in women aged 35 years or older. Hum Reprod 2000;15:24337.

13. Joseph K, Allen A, Dodds L, Turner L, Scott H, Liston R. The perinatal effectsof delayed childbearing. Obstet Gynecol 2005;105:14108.

14. Schmidt L, Sobotka T, Bentzen JG, Nyboe Andersen A. Demographic andmedical consequences of the postponement of parenthood. Hum ReprodUpdate 2012;18:2943.

15. Wiener-Megnazi Z, Auslender R, Dirnfeld M. Advanced paternal age andreproductive outcome. Asian J Androl 2012;14:6976.

16. Li Z, McNally L, Hilder L, Sullivan E. Australia's mothers and babies 2009.Sydney: AIHW National Perinatal Epidemiology and Statistics Unit; 2011.

17. Mills M, Rindfuss RR, McDonals P, te Velde E. Why do people postpone par-enthood? Reasons and social policy incentives. Hum Reprod Update 2011;17:84860.than some other survey topics. Despite diminishing responserates, telephone surveys that include landlines and cellphones and are weighted to match the demographic composi-tion of the population continue to provide accurate informa-tion about the surveyed populations (53).

In conclusion, a large proportion of people of reproduc-tive age in Australia have a considerable knowledge gap relat-ing to the potentially modiable factors that affect fertility. Abroad-based approach is needed to improve knowledge in thisarea and should include: information about fertility protec-tion in sex education and other reproductive health curricula;health care providers gauging people's childbearing inten-tions and desires, providing information that can help themrealize their goals (54, 55); and promotion of factual andaccessible information through public education initiativessuch as Your Fertility.

REFERENCES1. Holton S, Fisher J, Rowe H. To have or not to have? Australian women's

childbearing desires, expectations and outcomes. J Pop Res 2012;28:35379.

2. Lampic C, Skoog-Svanberg A, Karlstrom P, Tyden T. Fertility awareness, in-tentions concerning childbearing, and attitudes towards parenthood amongfemale and male academics. Hum Reprod 2006;21:55864.

3. Langdridge D, Sheeran P, Connolly K. Understanding the reasons for parent-hood. J Reprod Infant Psychol 2005;23:12133.

4. Peterson BD, PirritanoM, Tucker L, Lampic C. Fertility awareness and parent-ing attitudes among American male and female undergraduate universitystudents. Hum Reprod 2012;27:137582.

5. Roberts E, Metcalfe A, Jack M, Tough SC. Factors that inuence the child-bearing intentions of Canadian men. Hum Reprod 2011;25:12028.

6. Biro MA, Davey M-A, Carolan M, Kealy M. Advanced maternal age and ob-stetric morbidity for women giving birth in Victoria, Australia: a populationbased study. Aust NZ J Obstet Gynaecol 2012;52:22934.

7. Chapman MG, Driscoll GL, Jones B. Missed conceptions: the need for edu-cation. Med J Aust 2006;184:3612.

8. De Graaff AA, Land JA, Kessels AGH, Evers JLH. Demographic age shift to-ward later conception results in an increased age in the subfertile populationand an increased demand for medical care. Fertil Steril 2011;95:617.

9. FordWCL, North K, Taylor H, Farrow A, Hull MGR, Golding J, et al. Increasingpaternal age is associated with delayed conception in a large population offertile couples: evidence for declining fecundity in older men. Hum Reprod18. Utting D, Bewley S. Family planning and age-related reproductive risk. Ob-stetrician Gynecologist 2011;13:3541.

VOL. 99 NO. 2 / FEBRUARY 2013

19. Eskenazi B, Wyrobek A, Sloter E, Kidd S, Morre L, Young S, et al. The asso-ciation of age and semen quality in healthy men. Hum Reprod 2003;18:44754.

20. Homan GF, Davies MJ, Norman RJ. The impact of lifestyle factors on repro-ductive performance in the general population and those undergoing infer-tility treatment: a review. Hum Reprod Update 2007;13:20923.

21. Bavan B, Porzig E, Baker VL. An assessment of female university students'attitudes toward screening technologies for ovarian reserve. Fertil Steril2011;96:11959.

22. Bretherick KL, Fairbrother N, Avila L, Harbord SH, Robinson WP. Fertility andaging: do reproductive-aged Canadian women know what they need toknow? Fertil Steril 2010;93:21628.

38. Australian Bureau of Statistics. Smoking, risky drinking and obesity. In: Aus-tralian Social Trends, cat. no. 41020. Canberra: ABS; 2009.

39. Joint Health Surveys Unit. Health survey for England 2007 latest trends. Lon-don: NHS Information Centre for Health and Social Care; 2008.

40. McTigue K, Garrett J, Popkin B. The natural history of the development ofobesity in a cohort of young US adults between 1981 and 1998. Ann InternMed 2002;136:85764.

41. Australian Bureau of Statistics. National Health Survey: summary of results20072008. Canberra: ABS; 2009.

42. Callaway L, O'Callaghan M, McIntyre H. Barriers to addressing overweightand obesity before conception. Med J Aust 2009;191:4258.

43. Thompson M, Nassar N, Robertson M, Shand A. Pregnant women's knowl-edge of obesity and ideal weight gain in pregnancy, and health behaviours

Fertility and Sterilityand assisted reproduction: identifying the gaps. Fertil Steril 2012;97:4206.

24. Maheshwari A, Porter M, Shetty A, Bhattacharya S. Women's awarenessand perceptions of delay in childbearing. Fertil Steril 2008;90:103642.

25. Tough SC, Benzies K, Newburn-Cool C, Tofemire K, Fraser-Lee N, Faber A,Sauve R. What do women know about the risks of delayed childbearing?Can J Public Health 2006;97:3304.

26. Hammarberg K, Clarke VE. Reasons for delaying childbearing: a survey ofwomen aged over 35 years seeking assisted reproductive technology.Aust Fam Physician 2005;34:1879.

27. Athukorala C, Rumbold A, Willson KJ, Crowther CA. The risk of adversepregnancy outcomes in women who are overweight or obese. BMC Preg-nancy Childbirth 2010;10:56.

28. Ayer J, Belousova E, Harmer J, David C, Marks GB, Celermajer D. Maternalcigarette smoking is associated with reduced high-density lipoprotein cho-lesterol in healthy 8-year-old children. Eur Heart J 2011;32:244653.

29. Barau G, Robillard P-Y, Hulsey TC, Dedecker F, Latte A, Gerardin P, et al.Linear association between maternal pre-pregnancy body mass index andrisk of caesarean section in term deliveries. BJOG 2006;113:11737.

30. Fakuda M, Fakuda K, Shimizu T, Nobunaga M, Wreford Andersen E,Byskov AG, et al. Paternal smoking habits affect the reproductive life spanof daughters. Fertil Steril 2011;95:25424.

31. Gesink Law DC, Maclehose RF, Longnecker MP. Obesity and time to preg-nancy. Hum Reprod 2007;22:41420.

32. Hackshaw A, Rodeck C, Boniface S. Maternal smoking in pregnancy andbirth defects: a systematic review based on 173 687 malformed cases and11.7 million controls. Hum Reprod Update 2011;17:589604.

33. Hassan MAM, Killick SR. Negative lifestyle is associated with signicant re-duction in fecundity. Fertil Steril 2004;81:38492.

34. Hull MGR, North K, Taylor, Farrow A, Ford C. Delayed conception and activeand passive smoking. Fertil Steril 2000;74:72533.

35. Koepp U, Andersen L, Dahl-Joergensen K, Stigum H, Nass O, NystadW. Ma-ternal pre-pregnant body mass index, maternal weight change and off-spring birth weight. Acta Obstet Gynecol Scand 2012;91:2439.

36. Pasquali R, Gambineri A, Pagotto U. The impact of obesity on reproductionin women with polycystic ovary syndrome. BJOG 2006;113:114859.

37. Tennant PWG, Rankin J, Bell R. Maternal body mass index and the risk offetal and infant death: a cohort study from the north of England. HumReprod 2011;26:150111.VOL. 99 NO. 2 / FEBRUARY 2013of pregnant women and their partners. Aust NZ J Obstet Gynaecol 2011;51:4603.

44. Frank-Herrmann P, Gnoth C, Baur S, Strowitzki T, Freundl G. Determinationof the fertile window: reproductive competence of womenEuropean cycledatabases. Gynecol Endocrinol 2005;20:30512.

45. Practice Committee of the American Society for Reproductive Medicine incollaboration with the Society for Reproductive Endocrinology and Infertility.Optimizing natural fertility. Fertil Steril 2008;90(Suppl):S16.

46. Stanford J, White G, Hataska H. Timing intercourse to achieve pregnancy:current evidence. Obstet Gynecol 2002;100:133341.

47. Assisted Reproductive Treatment Act of 2008. Victoria, Australia, 2008.Available at: http://www.legislation.vic.gov.au/Domino/Web_Notes/LDMS/PubStatbook.nsf/f932b66241ecf1b7ca256e92000e23be/3ADFC9FBA2C0F526CA25751C0020E494/$FILE/08-076a.pdf. Accessed October 22, 2012.

48. Bunting L, Boivin J. Knowledge about infertility risk factors, fertility mythsand illusory benets of healthy habits in young people. Hum Reprod2008;23:185864.

49. Fisher J, Hammarberg K. Psychological and social aspects of infertility inmen: an overview of the evidence and implications for psychologically in-formed clinical care and future research. Asian J Androl 2012;14:1219.

50. Stobel-Richter Y, Beutel ME, Finck C, Braler E. The wish to have a child,childlessness and infertility in Germany. Hum Reprod 2005;20:28507.

51. Domar A, Conboy L, Denardo-Roney J, Rooney KL. Lifestyle behaviors inwomen undergoing in vitro fertilization: a prospective study. Fertil Steril2012;97:697701.

52. Baurele Bass S. How will Internet use affect the patient? A review of com-puter network and closed Internet-based system studies and the implica-tions in understanding how the use of the Internet affect patientpopulations. J Health Psychol 2011;8:2538.

53. Pew Research Center for the People and the Press. Assessing the represen-tativeness of public opinion surveys.Pew Research Center, May 15, 2012.Available at: http://www.people-press.org/2012/05/15/assessing-the-representativeness-of-public-opinion-surveys/. Accessed October 22, 2012.

54. Hammarberg K. Making healthy babies. Medical Observer, May 29, 2012Available at: http://www.medicalobserver.com.au/news/making-healthy-babies. Accessed October 22, 2012.

55. Mazza D, Cannold L, Nagle C, McKay F, Brijnath B. Making decisions aboutfertility: three facts GPs need to communicate to women. Aust Fam Physi-cian 2012;41:3436.23. Daniluk J, Koert E, Cheung A. Childless women's knowledge of fertility507

Knowledge about factors that influence fertility among Australians of reproductive age: a population-based surveyMaterials and methodsSettingParticipantsMethodMaterialsData Management and Analysis

ResultsDiscussionReferences