Fertility patients awareness on the effect of lifestyle and maternal age on pregnancy and miscarriage rates

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1 Katholieke Universiteit Leuven Departement Maatschappelijke Gezondheidszorg Centrum voor Ziekenhuis- en Verplegingswetenschap Master in de Verpleegkunde en de Vroedkunde Fertility patients awareness on the effect of lifestyle and maternal age on pregnancy and miscarriage rates Auteur: Promotor: Co-promotor: Co-promotor: Fieke van Asseldonk Dr. E. Dancet Prof. Dr. T. D Hooghe Prof. Dr. W. Sermeus Projectthesis aangeboden tot het verkrijgen van de graad van Master in de Verpleegkunde en de Vroedkunde Academiejaar

2 Table of Contents Abstract... 3 Abstract (Nederlands)... 4 Introduction... 5 Method... 6 Questionnaire... 6 Questionnaire dissemination... 6 Analysis... 7 Results... 8 A priori assessment of the questionnaire... 8 Respondents... 8 Knowledge regarding factors associated with spontaneous pregnancy rates Healthy habits Myths Low risks High risks Knowledge regarding factors associated with success rates of MAR Knowledge regarding factors associated with miscarriage rates Discussion Novelty Main results Critical appraisal of methodology Critical appraisal of results Recommendations Recommendations for research Recommendations for daily practice of fertility clinics Recommendations for policy References APPENDIX I APPENDIX II APPENDIX III

3 Abstract Background: Previous research focused on the association between lifestyle and fertility and on the public s awareness of the association between lifestyle and spontaneous pregnancy chance. Objective: This study aimed to explore fertility patients awareness of the association between lifestyle and spontaneous pregnancy chance and MAR-pregnancy chance and the probability of miscarriage. Methods: A four-part anonymous questionnaire was disseminated to women in the waiting room of a fertility clinic. The questionnaire included: demographic and reproductive questions (part I), the FAFS-questionnaire (i.e. on association between lifestyle and spontaneous pregnancy rates; part II), application of FAFS-questions (all but those concerning sexuality) on, respectively, MAR-pregnancy chance (part III) and the probability of miscarriage (part IV) based on literature review and an expert panel. The questionnaire was reciprocally translated and pilot tested to increase feasibility. For analysis the questions of the latter three parts were categorized in: risk factors, myths and healthy habits. Data were analyzed with descriptive and explanatory statistics using SPSS. Results: In total, 155 women (response rate= 83%) took part. Most women had a university degree and had been trying to conceive for an average 39 months of which they consulted a fertility clinic for an average 20 months. Women were more aware of the negative effects of risk factors than of the null effects of healthy habits and myths on their chance of spontaneous pregnancy, MAR-pregnancy and miscarriage. Per phase, the risk factors of which the smallest proportion of women were aware was: having ever had chlamydia for spontaneous pregnancy chance, doing 7 59 minutes of exercise per day for MAR-pregnancy chance, having ever had chlamydia for miscarriage. Conclusion: Fertility patients consulting a clinic do not seem more aware of lifestyle fertility risks than the general public. Fertility clinics should educate their patients on the association between their lifestyle and their chance of carrying a pregnancy to term. Study should explore whether knowledge of the association between lifestyle and fertility affects fertility patients lifestyle. 3

4 Abstract (Nederlands) Inleiding: Het verband tussen levensstijl en vruchtbaarheid werd reeds veelvuldig onderzocht. Eveneens werd in de algemene populatie onderzocht in welke mate men zich bewust is van het verband tussen levensstijl en de kans op een spontane zwangerschap. Doel: Deze studie onderzoekt de kennis van fertiliteitspatiënten over het verband tussen enerzijds levensstijl en leeftijd en anderzijds de kans op een spontane zwangerschap, de zwangerschapskans na vruchtbaarheidsbehandelingen en de kans op een miskraam. Methodologie: Een vierdelige vragenlijst werd uitgedeeld aan vrouwen in de wachtruimte van een fertiliteitscentrum. De vragenlijst bestond uit demografische en medische vragen (deel I), de FAFS-vragenlijst (vragen betreffende het verband tussen levensstijl en vruchtbaarheid; deel II), de FAFS-vragenlijst toegepast op respectievelijk de slagingskans van vruchtbaarheidsbehandelingen (deel III), en de kans op een miskraam (deel IV), met uitzondering van de vragen betreffende seksualiteit, en gebaseerd op een literatuurstudie en expert panel. De oorspronkelijke vragenlijst werd vertaald volgens de reciproke methode en de betrouwbaarheid van de nieuw ontworpen vragenlijst werd getest in een pilootstudie. Alle kennisvragen in de drie genoemde componenten werden met het oog op de analyse gecategoriseerd naar risicofactoren, fabels en gezonde leefgewoonten. Beschrijvende en verklarende statistische testen werden toegepast om de data te analyseren in SPSS. Resultaten: In totaal namen 155 vrouwen deel aan de studie (percentage respons: 83%). De meeste vrouwen hadden hoger onderwijs genoten, trachtten reeds zwanger te worden gedurende gemiddeld 39 maanden en waren reeds in behandeling voor fertiliteitsproblemen gedurende gemiddeld 20 maanden. Van gezonde leefgewoonten en fabels dachten veel vrouwen foutief dat deze factoren een positieve invloed hadden op zowel de vruchtbaarheid als de slaagkans van vruchtbaarheidsbehandelingen, en dat de kans op een miskraam afnam. De risicofactoren, daarentegen, werden meestal herkend door de vrouwen. De risicofactor die door het minste aantal vrouwen werd herkend in zowel het component vruchtbaarheid als het component miskraam was ooit chlamydia gehad hebben. In het component vruchtbaarheidsbehandeling werd de risicofactor sporten gedurende 7 59 minuten per dag het minst herkend door de vrouwen. Conclusie: Fertiliteitspatiënten blijken niet beter op de hoogte te zijn van de levensstijlfactoren die de vruchtbaarheid beïnvloeden dan de algemene populatie. Fertiliteitsklinieken zouden hun patiënten moeten informeren over het verband tussen levensstijl en de kans op een succesvolle zwangerschap. Het verband tussen kennis van de levensstijlfactoren en de daadwerkelijke levensstijl van de patiënt zou verder onderzocht moeten worden. 4

5 Introduction In developed countries 9-15% of the couples are faced with infertility (i.e. when a couple does not conceive within one year of unprotected intercourse; Boivin et al., 2007; Ata & Seli, 2010). Approximately 42-72% of these couples seek fertility care (Boivin et al., 2007). In developed countries, factors contributing to the increase in fertility problems are women frequently delaying motherhood (Evers, 2002; In the Netherlands 7% of mothers have their first child when they are older than 36 years; Bonneux et al., ) and prevalent negative lifestyle factors (e.g. one in three women of reproductive age smokes; Huisman et al., 2005) which are related to female fertility (i.e. overweight, underweight, alcohol, caffeine (>2cups/day), smoking (active and passive), sexual transmitted diseases (STD s) and recreational drugs (Anderson et al., 2010a; Anderson et al., 2010b)). Several studies have explored the population s awareness, especially of university students, of the association between on the one hand life style factors and/or maternal age and on the other hand fertility (Bretherick et al, 2010; ; Hashiloni-Dolev et al, 2011; Lampic et al, 2005; Maheshwari et al, ; Skoog Svanberg et al, 2006; Ali et al, 2011). These studies indicate that European university students have acceptable knowledge on the recommended maternal age to pursue child wish (Lampic et al., 2005) and are aware of the negative influence of certain lifestyle factors on fertility ( ). To our knowledge, two studies examined the knowledge of fertility patients on the association between lifestyle factors and/or maternal age on the one hand and fertility on the other hand (Hughes et al., 2000; Maheshwari et al., ). However, these studies showed limited knowledge of fertility patients. For example, only 47% of infertile women believed that smoking significantly impairs fertility (Hughes et al., 2000) and only 53,0% of fertility patients knew that being aged 30 or older decreases medically assisted reproduction (MAR) success rates (Maheshwari et al., ). For fertility patients it is relevant to be aware that lifestyle factors and maternal age influence MAR success rates, besides influencing spontaneous pregnancy rates. Smoking, for example, and advanced age decrease the chance of a successful in vitro fertilization (IVF; Homan, et al. 2007; Klonoff-Cohen, 2005). Surprisingly, misconceptions on the association between lifestyle and fertility treatment success rates are more prevalent in fertility patients than in spontaneously pregnant women. For example, infertile women are more likely than pregnant women to expect IVF to overcome the effect of maternal age on pregnancy rate (Maheshwari et al., ). There is also evidence that fertility care providers fail to educate their patients on the effect of lifestyle factors and maternal age on their fertility. For example, only 18% of infertile women would be advised about smoking cessation by their physicians (Hughes et al., 2000). Additionally, patients knowledge of the effect of lifestyle factors and maternal age on miscarriage is also of interest. Evidence shows, for example, that smoking and being overweight increase miscarriage rates (Kumar, 2011; Metwally et al., ; Rittenberg et al., 2011). The aim of this study was to assess the knowledge of fertility patients on the effect of on the one hand lifestyle factors and maternal age and on the other hand spontaneous pregnancy chance, MAR-pregnancy chance and the risk of miscarriage. 5

6 Method Based on the literature and advised by an expert panel, a questionnaire on the knowledge of female fertility patients was designed regarding the association between on the one hand lifestyle factors and maternal age and on the other hand the probabilities of spontaneous pregnancy, MAR-pregnancy and miscarriage. The questionnaire was disseminated to women in the waiting room of a university fertility clinic. The study was approved by an Ethical Committee (ML8332). Prior to filling out the questionnaire patients received written information and gave their consent for participation. Data were analyzed in the Statistical Package for Social Sciences (SPSS 17.0 Inc., Chicago, IL). Questionnaire Of the eight questionnaires (appendix I) on the effect of lifestyle factors and maternal age on fertility, identified by the literature review (Ali et al., 2011; Bretherick et al., 2010; ; 2010; Hashiloni-Dolev et al., 2011; Lampic et al., 2005; Maheshwari et al., ; Skoog Svanberg et al., 2006), the FAFS-questionnaire ( ) was selected based on its methodology and the fact that it covers both risks, healthy habits and myths, and was requested from the authors. The FAFS-questionnaire had previously been used in a population of university students but not by fertility patients. Two questionnaires on the association between maternal age and the success rates of MAR were identified by the literature search (Maheshwari et al., 2007; Hashiloni-Dolev et al., 2011). These questionnaires did not focus on lifestyle factors. No questionnaires to evaluate the knowledge on the association between maternal age and/or lifestyle and miscarriage rates were identified by the literature search. The English FAFS-questionnaire was reciprocally translated to Dutch. Based on literature review on the effect of lifestyle factors and maternal age on fertility treatment (Klonoff-Cohen, 2005; Klonoff-Cohen et al., 2006; Matthiesen et al., 2011; Morris et al., 2006; Neuer et al., 2000; Pasch et al., 2012; Rittenberg et al., 2011; Stephens et al., 2011; Wiser et al., 2012) and miscarriage (Blohm et al., ; Keegan et al., 2010; Kumar, 2011; Maconochie et al., 2007; Metwally et al., ; Nelson et al., 2003; Rittenberg et al., 2011; Stephens et al., 2011; Xueyan et al., 2011) and consulting an expert panel (two midwifes and two gynecologists) it was decided to apply all the questions of the FAFS-questionnaire, but those concerning sexuality, to MAR-pregnancy chance and the probability of miscarriage. A pilot test with ten fertility patients evaluated and increased feasibility of the questionnaire. This was also relevant for the FAFS-questionnaire as it had not been administered in a paper-pencil form (instead of online) and in Dutch (instead of in English). The expert panel and the fertility patients of the pilot test also gave their opinion on the face-validity of the questionnaire (appendix II; Polit & Beck, ). Finally, a four-part 98 item anonymous questionnaire was composed (appendix III) and included: two demographic and 12 reproductive questions (part I), the FAFS-questionnaire (i.e. 30 questions on the association between lifestyle and spontaneous pregnancy rates; part II), application of FAFS-questions (all but those on sexuality) to MAR-pregnancy rate (27 questions; part III) and to the probability of miscarriage (27 questions; part IV). No adjustments were made to the content of the FAFS-questionnaire (Bunting & Boivin. ). In the latter three parts respondents were asked to rank the possible effect of different factors on spontaneous pregnancy chance, MAR-pregnancy chance and the probability of miscarriage on a scale from 1 (most negative effect) to 100 (most positive effect), with 50 representing no effect. For analysis the questions of the latter three parts were categorized into: risk factors, myths and healthy habits. Data were analyzed with descriptive and explanatory statistics using SPSS. Questionnaire dissemination Dutch speaking women consulting a university fertility clinic for diagnosis or treatment were addressed in the waiting room of a tertiary university fertility clinic between August and September A researcher approached respondents face-to-face, orally informed them and handed out anonymous paper-pencil 6

7 questionnaires and an information and consent form to those willing to take part. Respondents filled the questionnaires out while waiting (for an ultrasound during ovarian stimulation, a consultation, a pick-up, intrauterine insemination or embryo transfer) and were not allowed to use electronic devices to search for information, nor to ask help from others. Anonymity was reassured by collecting the filled out questionnaires in a sealed box. The number of patients refusing to participate and their reasons were logged. About 25% of the women was initially approached while waiting for an ultrasound during ovarian stimulation but agreed to fill out the questionnaire before or after their pick-up, intra-uterine insemination or embryo transfer. On these occasions they had more time as they did not have to go to their work afterwards. Analysis Data were analyzed in SPSS 17.0 (SPSS Inc., Chicago, IL) and a probability value of p<0.05 was considered significant. Questionnaires filled out for less than 50% were excluded from further analysis (Bunting and Boivin, ). Percentage correct scores were calculated based on the number of responded questions. Descriptive statistics including measures of central tendency and variability were computed to describe the samples demographic and reproductive characteristics. Patients knowledge on the association with spontaneous pregnancy chance was assessed as indicated for the FAFS-questionnaire by Bunting and Boivin (). The following three categories were distinguished; risks, healthy habits and myths. First, percentage correct scores were calculated per category. Correctly identifying the direction of a factor (decreased for risk factors or no effect for healthy habits or for misconceptions) was assigned one point and an incorrect response was assigned zero points. Total scores per category were calculated and divided by the maximum score per category and multiplied by 100, to give the percentage correct score. This resulted in three percentage correct scores, one overall score for risk, one overall score for healthy habits and one overall score for misconception. For those factors explored with multiple questions (e.g. smoking) respondents had to correctly identify all questions in order to get one point ( ). Second, a pregnancy gain/loss score was calculated to express the average degree to which women believed a factor increased or decreased spontaneous pregnancy chances. Therefore, the average deviation score from 50 (no effect) was calculated for each factor ( ). Third, an analysis of variance, more specifically a repeated measures ANOVA (i.e. Willks Lambda), assessed whether there was a difference among the categories in the percentage correct scores (i.e. dependent variable). Paired t-tests further explored the differences one-on-one, using the Bonferroni correction (p<0,017). Fourth, the association between demographic and reproductive respondents characteristics on the one hand and respondents knowledge on the association between lifestyle factors and spontaneous pregnancy chance (the percentage correct scores per category) were explored with ANOVA, independent T-tests and linear regression (statistically significant at p<0.05). Respondents knowledge on the association with MAR-pregnancy chance and the probability of miscarriage were also explored. First, the literature was examined for evidence on whether there was an association or not. For the questions on which evidence was retrieved (15/27 for MAR-pregnancy chance, 18/27 for miscarriage), the proportion of respondents providing a correct answer was assessed with descriptive statistics. For the remaining questions (e.g. on being of normal weight ) respondents answers were described. The proportion of respondents that correctly identified the association between lifestyle factors and MARpregnancy chance was compared to the proportion of respondents that correctly identified the association between lifestyle factors and spontaneous pregnancy chance with McNemar s tests. The same was performed for the probability of miscarriages. 7

8 Results A priori assessment of the questionnaire The pilot test improved the questionnaire s feasibility by making slight adaptations to the patient information, wording and layout. The patients of the pilot test and the experts of the expert panel shared the opinion that the questionnaire was face-valid (appendix II). Respondents A total of 186 eligible fertility patients were asked to participate in the course of August and September In total, 156 women filled out the questionnaire (response rate= 83%). The main reason for not participating was time constraints. Other reported reasons were feeling emotional (n=3), being in physical pain (n=1), finding the subject too sensitive (n=1) and filled in lots of questionnaires lately (n=1). Only one questionnaire was excluded because it was filled out too incompletely. In the remaining questionnaires (n=155), there was only 0,42% missing data. The questions on chlamydia were most often not understood as three respondents left all three questions about chlamydia unanswered. The majority of the respondents (73,4%) had a higher education. About a third of the respondents had one or more children (29.7%), and/or had ever had a miscarriage (27,5%; table I). The most common cause of fertility problems was male (35,5%), followed by female (29,7%), unknown (23,2%) and both male and female (11,6%; table I). The vast majority of the women (94,8%) considered their personal health to be good, very good or outstanding and no women considered their health to be poor (table I). Respondents had been trying to conceive for an average 39 months of which they consulted a fertility clinic for an average 20 months (table I). Intra-uterine insemination (IUI), IVF and intra-cytoplasmic sperm injection (ICSI) were the most common fertility treatments among the respondents (table I). For example, 43,2% of the women underwent one or more IVF-cycles. About a quarter of the respondents (24,5%) visited more than one fertility clinic, the majority of the women consulted their general practitioner (57,4%) and/or a gynecologist (65,8%) for their fertility problems (table I). 8

9 Characteristic n Mean (SD) or % Range Age (3,9) Degree of education -No higher education -(University) college degree 41/ /154 26,6% 73,4% Duration of infertility in months (27,1) Duration of consulting a fertility clinic in months (20,8) Having children -Having one or more children -Are these children conceived by MAR? 46/155 35/155 29,7% 76,1% 1 3 Having ever had a miscarriage 42/153 27,5% Cause of infertility -male -female -male and female -unknown 55/155 46/155 18/155 36/155 35,5% 29,7% 11,6% 23,2% Ranked health -poor -moderate -good -very good -outstanding 0/153 8/153 76/153 55/153 14/153 0% 5,2% 49,7% 35,9% 9,2% Type of treatment -Monitoring menstrual cycle (without hormonal stimulation) -Monitoring menstrual cycle (with hormonal stimulation) -IUI (without hormonal stimulation) -IUI (with hormonal stimulation) -IVF -ICSI -Other 14/155 32/155 26/155 60/155 67/155 50/155 1/155 15,5% 20,6% 16,8% 38,7% 43,2% 32,3% 0,6% Visited more than one fertility center 38/155 24,5% Visited general practitioner for fertility problems 89/155 57,4% Visited gynecologist for fertility problems 102/155 65,8% Table I: Socio-demographic and reproductive characteristics of the respondents 9

10 Knowledge regarding factors associated with spontaneous pregnancy rates The risk factors that influence spontaneous pregnancy rates were correctly identified in the vast majority of the cases (percentage correct score= 82,7%; figure I). However, many respondents falsely believed in myths, as almost half of these questions were answered incorrect (percentage correct score= 48,8%; figure I). Healthy habits, such as sports or never smoking, were often considered to contribute to a woman s fertility. Only 32,8% of these factors were correctly identified to have no effect (figure I). The ANOVA showed that there was a difference in percentage correct scores across the three categories, including risks, myths and healthy habits. Respondents were significantly better at identifying risks compared with myths (p= <0,01), risks compared with healthy habits (p= <0,01) and myths compared with healthy habits (p= <0,01) *** *** *** Risk Myths Healthy Habits ***P<0,01 Category Figure I: Average percentage correct score per category (n=146) 10

11 The knowledge of the respondents (i.e. the total amount of points scored on the FAFS-questionnaire) was not associated with respondents age, degree of education, duration of infertility, duration of consulting a fertility clinic, cause of infertility and whether the respondent had consulted a gynecologist for her fertility problems (table II). An association was found between knowledge of the respondents and whether they consulted a general practitioner for their fertility problems. Surprisingly, respondents who did not consult a general practitioner had higher knowledge scores (table II). Characteristic Age Degree of education Number of respondents that provided answer (n) P-value 0,33 0,73 Duration of infertility in months 139 1,00 Duration of consulting a fertility clinic in months 140 0,31 Cause of infertility 147 0,47 Visited gynecologist for fertility problems 147 0,15 Visited general practitioner for fertility problems 147 0,04 Table II: Association between demographic and reproductive factors and knowledge about the effect of lifestyle on spontaneous pregnancy chance Healthy habits Of the nine healthy habits that are all not associated with spontaneous pregnancy chance addressed by the FAFS-questionnaire, only three were correctly identified as not having an effect by the majority of the respondents (table III). The healthy habits least often and most often correctly scored were, respectively, being aged 24 or younger (3.9%) and experiencing an event that one can cope with (76.1%; table III). On average, the respondents considered all the healthy habits to have a positive effect on spontaneous pregnancy chance, except for less than 7 minutes of exercise per day, which was considered to have a negative effect (table III; figure II). Experiencing an event that one can cope with was considered to have the smallest effect and being aged 24 or younger was considered to have the greatest effect (table III; figure II). Myths Of the seven myths that are all not associated with spontaneous pregnancy chance addressed by the FAFSquestionnaire, five were correctly identified as not having an effect by the majority of the respondents (table III). The healthy myths least often and most often correctly scored were, respectively, eating 5 portions of fruit and vegetables a day (25.2%) and not urinating after sex (72,3%). On average, all myths were rated as increasing spontaneous pregnancy chances, except for living in the city, which was considered to decrease the number of women getting pregnant. Not urinating after sex was considered to have the smallest impact and eating five portions of fruits and vegetables was considered to have the greatest impact. Low risks All four low risk factors were, on average, considered to have a negative effect on spontaneous pregnancy chance (figure II). The number of women that correctly estimated these factors to have a negative effect was not as high as the number that correctly identified the high risk factors. Only 78,7% of the respondents correctly identified smoking on average 1 9 cigarettes a day as a risk factor, smoking marijuana less than 4 11

12 times a week was considered to be a risk factor by only 80,0% of the respondents, and moderate stress was identified as a risk factor by 74,8% of the respondents (table III). High risks All 10 high risk factors were considered to decrease spontaneous pregnancy rates by the majority of the respondents (table III). Being aged over 45 years of age was considered to have the greatest effect. Having ever had chlamydia was considered to have the smallest effect (figure II). Maternal age was considered to be associated with spontaneous pregnancy rates by most respondents. Being aged between was correctly identified as a risk factor by 98,1% of the respondents, and being aged 45 or older by 98,7% of the respondents. Being aged between 35 39, however, was less frequently identified as a risk factor (85,2%; table III). These results show that not all women are aware of the age at which spontaneous pregnancy rates start to decrease. As mentioned before, only 78,7% of the respondents correctly identified smoking on average 1 9 cigarettes a day as a risk factor, compared to 92,9% of the respondents identifying smoking on average cigarettes a day and 95,5% of the respondents correctly identifying smoking on average more than 20 cigarettes a day as a risk factor. These results show that the majority of respondents were aware of the negative effect of smoking, but not all women knew that this negative effect also occurs in moderate smokers. This trend was also found with the use of marijuana. Smoking marijuana more than 4 times a week was considered to be a risk factor by 94,8% of the respondents, whereas smoking marijuana less than 4 times a week was considered to be a risk factor by only 80,0% of the respondents. Severe stress ( experiencing an event that one finds almost impossible to cope with ) was correctly identified as a risk factor by 89,0% of the respondents. Moderate stress, however, was not identified as a risk factor by as many respondents (74,8%). Being overweight and drinking more than 14 units of alcohol a week were correctly identified as decreasing spontaneous pregnancy chances by respectively 91,6% and 93,5% of the respondents. All questioned factors (risk factors, healthy habits and myths) and their effect on spontaneous pregnancy chance are presented in table III. At first the direction of the effect according to the literature is presented. Then, the number and percentage of respondents who correctly identified the effect is presented, as well as the average perceived effects, which shows how many extra or less women would get pregnant, on average, according to the respondents. 12

13 Lifestyle and age items Effect of items on spontaneous pregnancy chance Effect of items on MAR success-rates Effect of items on miscarriage rates Effect of factor reported in the Effect perceived by Effect of factor reported in the Effect perceived by patients Effect of factor reported in the literature patients literature literature Reference for the Reference for the Reference for the effect effect effect Direction of the effect Proportion and percentage correct scores The average perceived effect Items classified as healthy habits based on their association with spontaneous pregnancy chance Being aged 24 or younger Being aged between 25 and 34 years old Being of normal weight Never smoking Never drinking alcohol Experiencing an event that one can cope with Doing less than 7 minutes of exercise per day Doing 7 59 minutes of exercise per day Never used marijuana 6/155 3,9% 29/155 18,8% 30/155 19,4% 24/155 15,5% 55/155 35,5% 118/155 76,1% 88/155 56,8% 56/154 36,4% 81/154 52,6% Items classified as myths based on their association with spontaneous pregnancy chance Eating five portions of fruit and vegetables a day Not urinating after sex 39/155 25,2% 112/155 72,3% Direction of the effect Proportion and percentage correct scores +27 Homan et al., /155 12,3% +9 Homan et al., /154 22,7% Difference in proportion correct answer with FAFSquestion * Patients answer if no evidence on correct answer ,0% 0,6% 70,3% ,7% 0,6% 69,5% ,6% 0,6% 58,7% +3 71% 14,2% 14,8% -2 63,9% 26,5% 9,7% +8 Morris et al., 6/155 3,9% +7 58,1% 3,9% 38,1% 0,01 Blohm et al., ; Maconochie et al., ,35 Xueyan et al., 2011; Blohm et al., ; Maconochie et al., 2007 <0,01 Blohm et al., ; Maconochie et al., ,0% 0,7% 37,0% Direction of the effect Effect perceived by patients Proportion and percentage correct scores 41/155 26,5% 45/155 29,0% Xueyan et al., /154 12,3% 77/154 50,0% Difference in proportion correct answer with FAFSquestion * <0,01 0,03 <0,01 <0,01 Patients answer if no evidence on correct answer 54,8% 43,2% 12,0% 32,9% 64,5% 2,6% 42,6% 56,1% 1,3% 74,7% 16,9% 8,4% 61,9% 36,1% 2,0% 48,7% 49,4% 1,9%

14 Placing a pillow under the woman s hips during and after sex Lying down for 10 minutes after sex 86/155 55,5% 52/154 33,8% Living in the countryside Living in the city Adopting a baby 90/155 58,1% 86/155 55,5% - 102/155 65,8% Items classified as low risk items based on their association with spontaneous pregnancy chance Smoking on average 1 9 cigarettes a day Drinking less than 14 units of alcohol a week Experiencing an event that one finds difficult to cope with Smoking marijuana less than 4 times a week 122/155 78,7%? 32,5% 42,2% 25,6% 116/155 74,8% 124/155 80,0% +4 62,3% 0,6% 37,0% -2 61,7% 32,5% 5,8% +3 69,5% 3,9% 26,6% -10 Klonoff-Cohen, 2005; Homan et al., /155 79,4% -1 Klonoff-Cohen, 2005? 23,9% 61,3% 14,8% -9 Klonoff-Cohen, 2005; Pasch et al., 2012; Matthiesen et al., Klonoff-Cohen et al., /154 24,0% 127/155 81,9% 1,00 Klonoff-Cohen, 2005; Kumar, 2011; Blohm et al., ; Keegan et al., 2010 Klonoff-Cohen, 2005; Kumar, 2011; Maconochie et al., 2007 <0,01 Xueyan et al., 2011; Nelson et al., ,70 Klonoff-Cohen et al., /155 72,3% 30/155 19,4% 28/155 18,1% 23/155 14,8% 0,14 <0,01 <0,01 73,2% 25,5% 1,3% 70,6% 5,9% 23,5% 86,3% 12,4% 1,3% Items classified as high risk items based on their association with spontaneous pregnancy chance Being aged between 35 and 39 years old Being aged between 40 and 44 years old Being aged 45 years and older Being overweight 132/155 85,2% 152/155 98,1% 153/155 98,7% 142/155 91,6% -15 Homan et al., /155 68,4% -29 Wiser et al., /155 91,6% -38 Wiser et al., /155 92,9% -17 Rittenberg et al., 2011; Homan et al., /155 87,1% <0,01 Xueyan et al., 2011; Blohm et al., ; Maconochie et al., 2007; Homan et al ,01 Xueyan et al., 2011; Maconochie et al., 2007; Homan et al ,01 Xueyan et al., 2011; Maconochie et al., 2007; Homan et al ,09 Rittenberg et al., 2011; Kumar, 2011; Metwally et al., 119/155 76,8% 140/155 90,3% 141/155 91,0% 104/155 67,1% 0,04 <0,01 <0,01 <0,01 14

15 Smoking on average cigarettes a day 144/155 92,9% -20 Klonoff-Cohen, 2005; Homan et al., /155 95,5% 0,29 Klonoff-Cohen, 2005; Kumar, 2011; Blohm et al., ; Keegan et al., /155 82,6% 0,01 Smoking on average more than 20 cigarettes a day Drinking more than 14 units of alcohol a week Experiencing an event that one finds almost impossible to cope with Having ever had Chlamydia (a Sexually Transmitted Disease) Smoking marijuana more than 4 times a week 147/154 95,5% 144/154 93,5% 138/155 89,0% 106/150 70,7% 147/155 94,8% -28 Klonoff-Cohen, 2005; Homan et al., /155 96,8% -16 Klonoff-Cohen, 2005? 1,9% 97,4% 0,6% -20 Klonoff-Cohen, 2005; Pasch et al., 2012; Matthiesen et al., Neuer et al., 2000; Stephens et al., Klonoff-Cohen et al., /155 8,4% 104/152 68,4% 145/153 94,8% 0,38 Klonoff-Cohen, 2005; Kumar, 2011; Blohm et al., ; Keegan et al., 2010 Klonoff-Cohen, 2005; Kumar, 2011; Maconochie et al., 2007 <0,01 Xueyan et al., 2011; Nelson et al., /155 86,5% 139/155 89,7% 14/155 9,0% 0,71 Stephens et al., /149 55,7% 1,00 Klonoff-Cohen et al., /155 6,5% 0,01 0,26 <0,01 <0,01 <0,01 Table 3: The questioned items for risk items, healthy habits and myths and their effect reported in the literature and perceived by fertility patients on spontaneous pregnancy chance, MAR success-rates and miscarriage rates *p-value of the McNemar s test 15

16 Questions Percieved decrease (-) or increase (+) in fertility caused by presence of factor HIGH RISK FACTORS Being aged between 35 and 39 years old Being aged between 40 and 44 years old Being aged over 45 years old Being overweight Smoking cigarettes per day Smoking more than 20 cigarettes per day Drinking more than 14 units of alcohol per week Stress that a person finds unable/impossible to cope with Ever having Chlamydia (a Sexually Transmitted Disease, STD) Smoking marijuana more than 4 times per week MYTHS Eating five portions of fruit and vegetables a day Not urinating after sex Lying down for 10 minutes after sex Placing a pillow under the women's hips during and after sex Living in the countryside Living in the city Adopting a baby HEALTHY HABITS Being aged 24 or younger Being aged between 25 and 34 years old Being of normal weight Never smoking Never drinking alcohol Experiencing an event that one can cope with Less than 7 minutes of exercise per day 7-59 minutes of exercise per day Never smoking marijuana LOW RISK FACTORS Smoking 1-9 cigarettes per day Drinking less than 14 units of alcohol per week Experiencing an event that one finds difficult to cope with Smoking marijana less than 4 times per week Figure II: Average pregnancy gain/loss scores per item, according to the category in a survey on knowledge about spontaneous pregnancy chance in fertility patients. Knowledge regarding factors associated with success rates of MAR Evidence on the association between the 27 items for which questioned for their relation to MAR-pregnancy chance, was only found for 15 items, by reviewing the literature (56%). For those factors for which evidence on the correct answer was identified, the effect of the factors on MAR-pregnancy chances sometimes differs from the effect they have on fertility, (table III, e.g. stress was found to decrease fertility but was found to not affect the success rates of MAR ( ; Matthiessen et al., 2011)). Of the 15 items for which there is evidence on the correct answer, 10 were correctly identified by the majority of patients (table III). More specifically: being aged between years old was correctly identified by 68,4% of the respondents, being aged between years old by 91,6%, being aged 45 years and older by

17 92,9%, being overweight by 87,1%, smoking on average 1 9 cigarettes a day by 79,4%, smoking on average cigarettes a day by 95,5%, smoking on average more than 20 cigarettes a day by 96,8%, having ever had chlamydia by 68,4%, smoking marijuana less than 4 times a week by 81,9% and smoking marijuana more than 4 times a week by 94,8% of the respondents. The remaining five items, for which there is evidence on the correct answer, were correctly identified by a minority of respondents (table III). More specifically: being aged 24 or younger was correctly identified by 12.3% of the respondents, being aged between 24 and 34 years old by 22,7%, experiencing an event that one finds difficult to cope with by 24,0%, experiencing an event that one finds almost impossible to cope with by 8,4% and doing 7 59 minutes of exercise per day by 3,9% of the respondents. Of the 15 items for which the correct answer is known, for three factors a different direction of the association with spontaneous pregnancy chance and with MAR-pregnancy chance was found (table III). On average, respondents were not once capable of correctly identifying the correct answer if a different direction of the association was found. Of the 12 items for which the direction of the association with MAR-pregnancy chance is known and is equal to the direction of the association with spontaneous pregnancy chance, awareness of the association with MARpregnancy chance is more likely for one item and less likely for six items compared to the awareness of the association with spontaneous pregnancy chance. Knowledge regarding factors associated with miscarriage rates Evidence on the association between the 27 items for which questioned for their relation to miscarriage chance, was only found for 18 items, by reviewing the literature (67%). For those factors for which evidence on the correct answer was identified, the effect of the factors on miscarriage rates sometimes differs from the effect they have on fertility, (table III, e.g. smoking marijuana decreases spontaneous pregnancy chances but is not associated with miscarriage rates ( ; Klonoff-Cohen et al., 2006)). Of the 18 items for which there is evidence on the correct answer, nine were correctly identified by the majority of patients (table III). More specifically: being aged between years old was correctly identified by 76,8% of the respondents, being aged between years old by 90,3%, being aged 45 years and older by 91,0%, being overweight by 67,1%, smoking on average 1 9 cigarettes a day by 72,3%, smoking on average cigarettes a day by 82,6%, smoking on average more than 20 cigarettes a day by 86,5%, drinking more than 14 units of alcohol a week by 89,7% and having ever had chlamydia by 55,7% of the respondents. Doing 7 59 minutes of exercise per day was correctly identified by half of the respondents. The remaining eight items, for which there is evidence on the correct answer, were correctly identified by a minority of respondents (table III). More specifically: being aged 24 or younger was correctly identified by 26,5% of the respondents, being aged between 24 and 34 years old by 29,0%, drinking less than 14 units of alcohol a week by 19,4%, experiencing an event that one finds difficult to cope with by 18,1%, experiencing an event that one finds almost impossible to cope with by 9,0%, doing less than 7 minutes of exercise per day by 12,3%, smoking marijuana less than 4 times a week by 14,8% and smoking marijuana more than 4 times a week by 6,5% of the respondents. Of the 18 items for which the correct answer is known, for six factors a different direction of the association with spontaneous pregnancy chance and with miscarriage chance was found (table III). On average, respondents were not once capable of correctly identifying the correct answer if a different direction of the association was found for spontaneous pregnancy chance and for miscarriage chance. Of the 12 items for which the direction of the association with miscarriage chance is known and is equal to the direction of the association with spontaneous pregnancy chance, awareness of the association with miscarriage chance is more likely for three item and less likely for seven items compared to the awareness of the association with spontaneous pregnancy chance. 17

18 Discussion Novelty This is the first study to assess fertility patients awareness on the effect of lifestyle and maternal age on spontaneous pregnancy chance, MAR-pregnancy chance and the probability of miscarriage. Main results Most female fertility patients are aware of the negative association between on the one hand advanced maternal age and on the other hand spontaneous pregnancy chance, as well as MAR-pregnancy chance and the probability of miscarriage. Regarding lifestyle factors, female patients are aware of risks factors associations with spontaneous pregnancy chance, MAR-pregnancy chance and the probability of miscarriage. Awareness of the null-effects of healthy habits and myths on spontaneous pregnancy chance, MAR-pregnancy chance and the probability of miscarriage was limited. Many female fertility patients falsely believed in the protective effect of healthy habits instead of considering them just part of a normal and healthy lifestyle. Additionally many female fertility patients falsely believed in treats of myths. A majority of the female fertility patients correctly identified all factors that decrease spontaneous pregnancy chances, all factors that decrease MAR-pregnancy chances, but doing 7 59 minutes of exercise per day and all factors that increased the probability of miscarriage. Only a minority of the female fertility patients were aware that the only factor with a positive effect doing less than 7 minutes of exercise per day, could decrease the probability of miscarriage according to one study. Critical appraisal of methodology The methodology used by this study has several strengths. First, which questionnaire to use was carefully considered with the aid of a literature review. Moreover, the best available questionnaire was extended in order to be able to answer our entire research question with the aid of literature review and an expert panel. Second, the methodology for patient recruitment maximized response rates up to 83% with a face-to-face approach (Polit & Beck, ) and researchers flexibility (the possibility to fill out the questionnaire at a more convenient time). However, the high response rate can also be attributed to fertility patients wanting to learn how to contribute more to becoming pregnant (Porter & Bhattacharya, 2007). Third, as there was hardly any missing data (0,42%), it was possible to draw reliable conclusions. Fourth, it can be considered a strength that data were collected within a short period of time as variable media coverage over time was kept constant this way. Fifth, as respondents were not allowed to take the questionnaire home or consult data sources like the internet, this could not cause bias and patients actual active knowledge was assessed. However, several critical remarks should also be made. First, respondents were recruited from only one fertility clinic and a multicenter study would have given a better and less clinic dependent impression of European clinic s education of fertility patients on maternal age and lifestyle effect on the chance of carrying a pregnancy to term. Second, only Dutch speaking women were included and therefore most immigrants are not well represented in the sample. Since local media coverage of these topics does not reach these women this might actually be an important target group for educational campaigns. Third, more in-depth qualitative research of how patients build and communicate their knowledge might be indicated as the pilot study revealed that two patients answered the questions taking their own lifestyle in consideration (e.g. a woman s quote I m a smoker so I can t answer that smoking has a negative effect on fertility ). It could be that the anonymity of the questionnaire dissemination protected for this effect but this is 18

19 unknown. Future studies should ask respondents about their personal lifestyle, in order to study the association between patients answers and their lifestyle. Fourth, the question arises whether women were actually aware of the effect of a lifestyle factor on the different questioned aspects of their fertility if they answered a question correctly. It could be that they believed a risk factor had a negative effect based on the knowledge that this risk factor affects health in general. Our analysis showed that if a lifestyle factor had different effects on the three fertility aspects (spontaneous and MAR-pregnancy chance and probability of miscarriage), patients most commonly estimated them to be risk factors in all three fertility aspects. Furthermore, Bunting & Boivin pointed out that women might assume that any factor questioned must have some effect ( ). The latter could explain the small number of correctly identified healthy habits and myths. Critical appraisal of results Compared to previous studies on fertility patients, the respondents in this study were more aware of risk factors. Almost all our respondents (91,6%) were aware of the decreased MAR success rates when being aged 40 or older, compared to 74,7% of the fertility patients in a previous study (Maheshwari et al., ). Our respondents were also more aware of the association between smoking and spontaneous pregnancy rates (78,7 95,5%), compared with fertility patients in a previous study (47%; Hughes et al., 2000). Our respondents were significantly better at identifying the association between maternal age and spontaneous pregnancy rates, than between maternal age and MAR success rates (p=<0,01, p=0,01 and p=0,01), which reinforces the previous finding that some respondents believe MAR can overcome the effect of maternal age (Maheshwari et al., ). Compared to the general population that was studied with the same FAFS-questionnaire by the fertility patients of this study also correctly identified all the high risk factors for spontaneous pregnancy chance ( ). The same risk factor being aged over 45 years of age was considered to have the greatest impact on spontaneous pregnancy rates, by both the general population and the fertility patients ( ). Furthermore, in both the general population sample ( ) and the current fertility patient sample awareness was higher for risks than for healthy habits and even lower for myths. Overall, the general population seemed slightly better at identifying the risks (percentage correct score of 90,7%) compared with fertility patients (percentage correct score of 82,7%). Whereas fertility patients seemed slightly better at identifying healthy habits (percentage correct score of 32,8%) and myths (percentage correct score of 51,2%) compared with the general population (percentage correct scores of 26,5% and 41,5%, respectively). However, it is difficult to compare the general population sample ( ) with the current sample as data were collected with a four year interval in other European countries. Additionally, Bunting & Boivin used an online survey with scales providing pop-ups that gave the respondent additional information such as 35 extra women will get pregnant when hovering the mouse over the number 85. It is unclear from the study of Bunting & Boivin if students could select themselves for participation based on their knowledge on lifestyle factors that influence fertility as response rates were not reported. Details about questionnaire dissemination were not reported either and therefore we do not know if the student might have consulted, for example the internet, in answering the questions ( ). The fact that Bunting & Boivin included both women and men instead of only women in this study is less important as gender does not affect awareness on this topic ( ). The finding of another general population sample study using another questionnaire that higher educational level was associated with better knowledge (Ali et al., 2011) could not be confirmed. Our study shows that of the four items of this questionnaire on which patients knowledge in poorest (<10% gave a correct answer), three include items with a different direction or effect on the three investigated fertility aspects (spontaneous pregnancy chance, MAR-pregnancy chance, the probability of miscarriage). One should wonder whether it is relevant or confusing to educate patients on these differences. 19

20 Recommendations Recommendations for research This study only focused on female lifestyle factors, whereas male lifestyle factors such as smoking, being overweight and drinking coffee can decrease spontaneous pregnancy rates and successful MAR outcomes as well (Anderson et al., 2010; Cabler et al., 2010; Varghese et al., ), and possibly even miscarriage rates when it comes to, for example, passive smoking. Further research on the knowledge, of especially male patients, on male lifestyle is needed. It would be interesting to find out if there is a difference between clinics in the knowledge of their patients and if fertility patients knowledge is better or worse than the knowledge of women of comparable age from the same country. Interventions to influence fertility patients knowledge and behavior regarding lifestyle factors should be studied. The first fertility clinic lifestyle intervention study was recently reported (Homan et al., 2012) after the same research group reported in their pilot that patients awareness of the possible impact of lifestyle factors on their chances of spontaneous pregnancy, does not necessarily connect to their own lifestyle (Homan & Norman, 2009). An intervention program including: a lifestyle interview, an individual plan for lifestyle adjustment and several months of supportive phone calls, changed fertility patients lifestyle (Homan et al., 2012). The authors attribute their success to motivational interviewing (with a ladder scale and a decision balance), individualized care, ongoing support, empathy and reflective listening (Homan et al., 2012). Another individualized tool for fertility clinics to increase awareness of their patients that should be tested in clinical practice is the FertiSTAT-tool ( 2010). Recommendations for daily practice of fertility clinics Fertility clinics need to improve the knowledge of their patients. First, the majority but not all fertility patients are aware of the risks that limit their chances of having a child. Second, although the limited awareness of the null effects of healthy habits and myths will not influence baby-take-home-rates, it might prevent patients from thinking their behavior regarding healthy habits and myths compensates their risk behavior. Third, the fact that no association was found between duration of infertility treatment and knowledge might indicate that the investigated fertility clinic does not educate its patients well enough. Fourth, a previous qualitative study showed fertility patients need for more practical information of their fertility clinic and showed that fertility patients adjusted their lifestyle based on information from the internet (Porter & Bhattacharya, 2007). The first evidence that interventions of fertility clinics can help fertility patients change their lifestyle has been published (Homan et al., 2012). All fertility clinics should provide education on and interventions to change their patients lifestyle. This is especially relevant when tailored expectant management is offered as a treatment to patients. Recommendations for policy Results demonstrated that patients consulting a general practitioner (GP) for their fertility problems had less knowledge on the effect of lifestyle and maternal age on their spontaneous pregnancy chance. The advice provided by GP s should therefore be addressed. It could also be that patients consulting their GP and not being fully informed do not search the internet for advice because they falsely believe their GP has taken the time to fully inform them. Media coverage of factors that influence pregnancy rates and miscarriage rates can probably increase the general public and patients knowledge. However, so far the written media has not been taking up this task (Dancet et al., 2013 submitted; Ingram et al., 1990; Johnson et al., 1999; Moyer et al., 2001; Noble & Bell, 1992; Shugg & Liamputtong, 2002; Weston & Ruggiero, 1985). Internet can also be of great use in distributing information among fertility patients (Porter & Bhattacharya, 2007), and social media also have high potential. The effect of media information campaigns on the knowledge of patients and the general public on the effects of lifestyle and maternal age on fertility should be studied. 20

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