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

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:

Fieke van Asseldonk

Promotor:

Dr. E. Dancet

Co-promotor:

Prof. Dr. T. D’Hooghe

Co-promotor:

Prof. Dr. W. Sermeus

Projectthesis aangeboden tot het verkrijgen van de graad van Master in de Verpleegkunde en de Vroedkunde Academiejaar 2012– 2013

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.................................. 10 Healthy habits................................................................................................................................ 11 Myths ............................................................................................................................................. 11 Low risks ........................................................................................................................................ 11 High risks ....................................................................................................................................... 12 Knowledge regarding factors associated with success rates of MAR ............................................... 16 Knowledge regarding factors associated with miscarriage rates ...................................................... 17 Discussion.............................................................................................................................................. 18 Novelty .............................................................................................................................................. 18 Main results ....................................................................................................................................... 18 Critical appraisal of methodology ..................................................................................................... 18 Critical appraisal of results ................................................................................................................ 19 Recommendations ............................................................................................................................ 20 Recommendations for research .................................................................................................... 20 Recommendations for daily practice of fertility clinics ................................................................. 20 Recommendations for policy......................................................................................................... 20 References............................................................................................................................................. 22 APPENDIX I ............................................................................................................................................ 25 APPENDIX II ........................................................................................................................................... 27 APPENDIX III .......................................................................................................................................... 29

2

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

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

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., 2008) 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; Bunting & Boivin, 2008; Hashiloni-Dolev et al, 2011; Lampic et al, 2005; Maheshwari et al, 2008; 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 (Bunting & Boivin, 2008). 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., 2008). 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., 2008). 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., 2008). 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., 2008; 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

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; Bunting & Boivin, 2008; Bunting & Boivin, 2010; Hashiloni-Dolev et al., 2011; Lampic et al., 2005; Maheshwari et al., 2008; Skoog Svanberg et al., 2006), the FAFS-questionnaire (Bunting & Boivin, 2008) 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., 2008; Keegan et al., 2010; Kumar, 2011; Maconochie et al., 2007; Metwally et al., 2008; 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, 2008). 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. 2008). 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 2012. A researcher approached respondents face-to-face, orally informed them and handed out anonymous paper-pencil

6

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, 2008). 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 (2008). 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 (Bunting & Boivin, 2008). 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 (Bunting & Boivin, 2008). 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

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 2012. 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

Characteristic

n

Mean (SD) or %

Range

Age

155

32 (3,9)

23 – 43

Degree of education -No higher education -(University) college degree

41/154 113/154

26,6% 73,4%

Duration of infertility in months

146

39 (27,1)

0 – 152

Duration of consulting a fertility clinic in months

147

20 (20,8)

0 – 126

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%

1 – 10 1–8 1 – 10 1 – 10 1–9 1–8 2

Table I: Socio-demographic and reproductive characteristics of the respondents

9

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).

100

*** ***

90 80 70

***

60 50 40 30 20 10 0 Risk ***P<0,01

Myths

Healthy Habits

Category

Figure I: Average percentage correct score per category (n=146)

10

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

Number of respondents that provided answer (n)

P-value

Age

147

0,33

Degree of education

146

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

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 40 – 44’ 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 10 – 19 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

Lifestyle and age items

Effect of items on spontaneous pregnancy chance Effect of factor reported in the Effect perceived by literature patients Reference for the Direction ProporThe effect of the tion and average effect percenperceitage ved correct effect scores

Effect of items on MAR success-rates Effect of factor reported in the literature Reference for the Direction effect of the effect

Items classified as healthy habits based on their association with spontaneous pregnancy chance Being aged 24 or younger Bunting & Boivin, − 6/155 +27 Homan et al., 2007 2008 3,9% Being aged between 25 and 34 years old

Bunting & Boivin, 2008

−

29/155 18,8%

+9

Being of normal weight


−

30/155 19,4%

+18

Never smoking


−

24/155 15,5%

+19

Never drinking alcohol


−

55/155 35,5%

+13

Experiencing an event that one can cope with


−

118/155 76,1%

+3

Doing less than 7 minutes of exercise per day


−

88/155 56,8%

-2

Doing 7 – 59 minutes of exercise per day


−

56/154 36,4%

+8

Never used marijuana


−

81/154 52,6%

+7

Homan et al., 2007


−

112/155 72,3%

+1

Proportion and percentage correct scores

Difference in proportion correct answer with FAFSquestion *

−

19/155 12,3%

0,01

−

35/154 22,7%

0,35

Patients’ answer if no evidence on correct answer

Morris et al., 2008

-

↓

6/155 3,9%

Effect of items on miscarriage rates Effect of factor reported in the literature Reference for the Direction effect of the effect

Blohm et al., 2008; Maconochie et al., 2007 Xueyan et al., 2011; Blohm et al., 2008; Maconochie et al., 2007 − 29,0% ↓ 0,6% ↑70,3% − 29,7% ↓ 0,6% ↑69,5% − 40,6% ↓ 0,6% ↑58,7% − 71% ↓14,2% ↑14,8% − 63,9% ↓26,5% ↑9,7%

Items classified as myths based on their association with spontaneous pregnancy chance Eating five portions of fruit Bunting & Boivin, − 39/155 +11 and vegetables a day 2008 25,2% Not urinating after sex

Effect perceived by patients

<0,01

Effect perceived by patients Proportion and percentage correct scores

Difference in proportion correct answer with FAFSquestion *

−

41/155 26,5%

<0,01

−

45/155 29,0%

0,03

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% Xueyan et al., 2011

↓

19/154 12,3%

<0,01

Blohm et al., 2008; Maconochie et al., 2007

−

77/154 50,0%

<0,01

− 58,1% ↓3,9% ↑38,1%

− 61,9% ↓36,1% ↑2,0%

− 34,0% ↓0,7% ↑37,0%

− 48,7% ↓49,4% ↑1,9% -

Placing a pillow under the woman’s hips during and after sex Lying down for 10 minutes after sex


−

86/155 55,5%

+4

-

-


−

52/154 33,8%

+7

-

-

Living in the countryside


−

90/155 58,1%

+4

Living in the city


−

86/155 55,5%

-2

Adopting a baby


-

102/155 65,8%

+3

− 62,3% ↓0,6% ↑37,0% − 61,7% ↓32,5% ↑5,8% − 69,5% ↓3,9% ↑26,6%

Items classified as low risk items based on their association with spontaneous pregnancy chance Smoking on average 1 – 9 Bunting & Boivin, ↓ 122/155 -10 Klonoff-Cohen , 2005; cigarettes a day 2008 78,7% Homan et al., 2007

↓

123/155 79,4%

1,00

Klonoff-Cohen, 2005; Kumar, 2011; Blohm et al., 2008; Keegan et al., 2010 Klonoff-Cohen, 2005; Kumar, 2011; Maconochie et al., 2007 Xueyan et al., 2011; Nelson et al., 2003

↑

112/155 72,3%

0,14

−

30/155 19,4%

−

28/155 18,1%

<0,01

Drinking less than 14 units of alcohol a week


?

− 32,5% ↓42,2% ↑25,6%

-1

Klonoff-Cohen, 2005

?

Experiencing an event that one finds difficult to cope with Smoking marijuana less than 4 times a week


↓

116/155 74,8%

-9

−

37/154 24,0%

<0,01


↓

124/155 80,0%

-10

Klonoff-Cohen, 2005; Pasch et al., 2012; Matthiesen et al., 2011 Klonoff-Cohen et al., 2006

↓

127/155 81,9%

0,70

Klonoff-Cohen et al., 2006

−

23/155 14,8%

<0,01

↓

106/155 68,4%

<0,01

Xueyan et al., 2011; Blohm et al., 2008; Maconochie et al., 2007; Homan et al. 2007 Xueyan et al., 2011; Maconochie et al., 2007; Homan et al. 2007 Xueyan et al., 2011; Maconochie et al., 2007; Homan et al. 2007 Rittenberg et al., 2011; Kumar, 2011; Metwally et al., 2008

↑

119/155 76,8%

0,04

↑

140/155 90,3%

<0,01

↑

141/155 91,0%

<0,01

↑

104/155 67,1%

<0,01

Items classified as high risk items based on their association with spontaneous pregnancy chance Being aged between 35 Bunting & Boivin, ↓ 132/155 -15 Homan et al., 2007 and 39 years old 2008 85,2%

− 23,9% ↓61,3% ↑14,8%

− 73,2% ↓25,5% ↑1,3% − 70,6% ↓5,9% ↑23,5% − 86,3% ↓12,4% ↑1,3%

Being aged between 40 and 44 years old


↓

152/155 98,1%

-29

Wiser et al., 2012

↓

142/155 91,6%

0,01

Being aged 45 years and older


↓

153/155 98,7%

-38

Wiser et al., 2012

↓

144/155 92,9%

0,01

Being overweight


↓

142/155 91,6%

-17

Rittenberg et al., 2011; Homan et al., 2007

↓

135/155 87,1%

0,09

14

Smoking on average 10 – 19 cigarettes a day


↓

144/155 92,9%

-20

Klonoff-Cohen , 2005; Homan et al., 2007

↓

148/155 95,5%

0,29

Klonoff-Cohen, 2005; Kumar, 2011; Blohm et al., 2008; Keegan et al., 2010

↑

128/155 82,6%

0,01

Smoking on average more than 20 cigarettes a day


↓

147/154 95,5%

-28

Klonoff-Cohen, 2005; Homan et al., 2007

↓

150/155 96,8%

0,38

↑

134/155 86,5%

0,01

Drinking more than 14 units of alcohol a week


↓

144/154 93,5%

-16

Klonoff-Cohen, 2005

?

↑

139/155 89,7%

0,26

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


↓

138/155 89,0%

-20

−

13/155 8,4%

<0,01

−

14/155 9,0%

<0,01


↓

106/150 70,7%

-11

Klonoff-Cohen, 2005; Pasch et al., 2012; Matthiesen et al., 2011 Neuer et al., 2000; Stephens et al., 2011

Klonoff-Cohen, 2005; Kumar, 2011; Blohm et al., 2008; Keegan et al., 2010 Klonoff-Cohen, 2005; Kumar, 2011; Maconochie et al., 2007 Xueyan et al., 2011; Nelson et al., 2003

↓

104/152 68,4%

0,71

Stephens et al., 2011.

↑

83/149 55,7%

<0,01


↓

147/155 94,8%

-22


↓

145/153 94,8%

1,00


−

10/155 6,5%

<0,01

− 1,9% ↓97,4% ↑0,6%

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

Percieved decrease (-) or increase (+) in fertility caused by presence of factor -40

-30

-20

-10

0

10

20

30

40

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 10-19 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

Questions

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 (Bunting & Boivin, 2008; 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 35 – 39 years old’ was correctly identified by 68,4% of the respondents, ‘being aged between 40 – 44 years old’ by 91,6%, ‘being aged 45 years and older’ by

92,9%, ‘being overweight’ by 87,1%, ‘smoking on average 1 – 9 cigarettes a day’ by 79,4%, ‘smoking on average 10 – 19 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 (Bunting & Boivin, 2008; 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 35 – 39 years old’ was correctly identified by 76,8% of the respondents, ‘being aged between 40 – 44 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 10 – 19 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

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, 2008) 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

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 (Bunting & Boivin, 2008). 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., 2008). 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., 2008). Compared to the general population that was studied with the same FAFS-questionnaire by Bunting & Boivin, the fertility patients of this study also correctly identified all the high risk factors for spontaneous pregnancy chance (Bunting & Boivin, 2008). 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 (Bunting & Boivin, 2008). Furthermore, in both the general population sample (Bunting & Boivin, 2008) 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 (Bunting & Boivin, 2008) 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 (Bunting & Boivin, 2008). 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 (Bunting & Boivin, 2008). 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

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., 2008), 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 (Bunting & Boivin, 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

An aspect for health care policy around which to design a preventive education campaign for the general public is chlamydia for the following reasons: (i) chlamydia decreases the chance of spontaneous pregnancy (Bunting & Boivin), MAR-pregnancy chance (Neuer et al., 2000; Stephens et al., 2011) and increases miscarriage rates (Stephens AJ, et al. 2011), (ii) of all investigated risk factors ‘having ever had Chlamydia’ is the most unknown risk factor among fertility patients, (iii) chlamydia rates are rising (Land et al., 2010) and (iv) chlamydia should be tackles by preventive instead of curative measures.

21

References Ali, S., Sophie, R., Imam, A.M., Khan, F.I., Ali, S.F., Shaikh, A., Farid-ul-Hasnain, S., 2011. Knowledge, perceptions and myths regarding infertility among selected adult population in Pakistan: a cross-sectional study. BMC Public Health. 11 (760). Anderson, K., Nisenblat, V., Norman, R., 2010. Lifestyle factors in people seeking infertility treatment, a review. Australian and New Zealand Journal of Obstetrics and Gynaecology. 50, 8–20. Anderson, K., Norman, R.J., Middleton, P., 2010. Preconception lifestyle advice for people with subfertility. Cochrane Database of Systematic Reviews. 4. Ata, B., Seli, E., 2010. Economics of assisted reproductive technologies. Current Opinion in Obstetrics and Gynecology. 22, 183-188. Baruch, Y., 1999. Response rate in academic studies, a comparative analysis. Human relations. 52 (4). Blohm, F., Fridén, B., Milsom, I., 2008. A prospective longitudinal population-based study of clinical miscarriage in an urban Swedish population. International Journal of Obstetrics and Gynaecology. 115, 176–183. Boivin, J., Bunting, L., Collins, J.A., Nygren, K.G., 2007. International estimates of infertility prevalence and treatment-seeking: potential need and demand for infertility medical care. Human Reproduction. 22 (6), 1506-1512. Bretherick, K.L., Fairbrother, N., Avila, L., Harbord, S.H., Robinson, W.P., 2010. Fertility and aging: do reproductive-aged Canadian women know what they need to know? Fertility and Sterility. 93 (7), 2162-2168. Bunting, L., Boivin, J., 2008. Knowledge about infertility risk factors, fertility myths and illusory benefits of healthy habits in young people. Human Reproduction. 23 (8), 1858–1864. Bunting, L., Boivin, J., 2010. Development and preliminary validation of the fertility status awareness tool: FertiSTAT. Human Reproduction. 25 (7), 1722–1733. Cabler, S., Agarwal, A., Flint, M., Du Plessis, S.S., 2010. Obesity: modern man’s fertility nemesis. Asian Journal of Andrology. 12, 480–489. Ebbesen, S., Zachariae, R., Mehlsen, M.Y., Thomsen, D., Højgaard, A., Ottosen, L., Petersen, T., Ingerslev, H.J., 2009. Stressful life events are associated with a poor in-vitro fertilization (IVF) outcome: a prospective study. Human Reproduction. 24 (9), 2173–2182. Evers, J.L., 2002. Female subfertility. Lancet. 360 (9327), 151-159. Hashiloni-Dolev, Y., Kaplan, A., Shkedi-Rafid, S., 2011. The fertility myth: Israeli students’ knowledge regarding age-related fertility decline and late pregnancies in an era of assisted reproduction technology. Human Reproduction. 26 (11), 3045-3053.

22

Homan, G.F., Davies, M., Norman, R., 2007. The impact of lifestyle factors on reproductive performance in the general population and those undergoing infertility treatment: a review. Human Reproduction Update. (3), 209–223. Hughes, E.G., Lamont, D.A., Beecroft, M.L., Wilson, D.M.C., Brennan, B.G., Rice, S.C., 2000. Randomized trial of a “stage-of-change” oriented smoking cessation intervention in infertile and pregnant women. Fertility and Sterility. 74, 498-503. Huisman, M., Kunst, A.E., Mackenbach, J.P., 2005. Inequalities in the prevalence of smoking in the European Union: comparing education and income. Preventive Medicine. 40, 756-764. Keegan, J., Parva, M., Finnegan, M., Gerson, A., Belden, M., 2010. Addiction in Pregnancy. Journal of Addictive Diseases. 29, 175–191. Kelley, K., Clark, B., Brown, V., Sitzia, J., 2003. Good practice in the conduct and reporting of survey research. International Journal for Quality in Healthcare. 15 (3), 261-266. Klonoff-Cohen, H., 2005. Female and male lifestyle habits and IVF: what is known and unknown. Human Reproduction Update. 11 (2), 180-204. Klonoff-Cohen, H.S., Natarajan, L., Chen, R.V., 2006. A prospective study of the effects of female and male marijuana use on in vitro fertilization (IVF) and gamete intrafallopian transfer (GIFT) outcomes. American Journal of Obstetrics and Gynecology. 194, 369 – 376. Kumar, S., 2011. Occupational, Environmental and lifestyle factors associated with spontaneous abortion. Reproductive Sciences. 18 (10), 915-930. Lampic, C., Skoog Svanberg, A., Karlström, P., Tydén, T., 2005. Fertility awareness, intentions concerning childbearing and attitudes towards parenthood among female and male academics. Human Reproduction. 21 (2), 558-564. Land, J.A., Van Bergen, J.E.A.M., Morré, S.A., Postma, M.J., 2010. Epidemiology of Chlamydia trachomatis infection in women and the cost-effectiveness of screening. Human Reproduction Update. 16 (2), 189 – 204. Maconochie, N., Doyle, P., Prior, S., Simmons, R., 2007. Risk factors for first trimester miscarriage—results from a UK-population-based case–control study. 114, 170–186. Maheshwari ,A., Porter, M., Shetty, A., Bhattacharya, S., 2008. Women’s awareness and perceptions of delay in childbearing. Fertility and Sterility. 90, 1036-1042. Matthiesen, S.M.S., Frederiksen, Y., Ingerslev, H.J., Zachariae, R., 2011. Stress, distress and outcome of assisted reproductive technology (ART): a meta-analysis. Human reproduction. 26 (10), 2763 – 2776. Metwally, M., Ong, K.J., Ledger, W.L., Li, T.C., 2008. Does high body mass index increase the risk of miscarriage after spontaneous and assisted conception? A meta-analysis of the evidence. Fertility and Sterility. 90 (3), 714-726. Morris, S.N., Missmer, S.A., Cramer, D.W., Powers, R.D., McShane, P.M., Hornstein, M.D., 2006. Effects of Lifetime Exercise on the Outcome of In Vitro Fertilization. Obstetrics & Gynecology. 108 (4), 938 – 945.

23

Nelson, D.B., Grisso, J.A., Joffe, M.M., Brensinger, C., Shaw, L., Datner, E., 2003. Does Stress Influence Early Pregnancy Loss? Ann Epidemiol. 13, 223–229. Neuer, A., Spandorfer, S.D., Giraldo, P., Dieterie, S., Rosenwaks, Z., Witkin, S.S., 2000. The role of heat shock proteins in reproduction. Hum Reprod Update. 6 (2), 149 – 159. Pandey, S., Maheshwari, A., Bhattacharya, S., 2010. Should access to fertility treatment be determined by female body mass index? Human Reproduction. 25 (4), 815-820. Pasch, L.A., Gegorich, S.E., Katz, P.K., Millstein, S.G., Nachtigall, R.D., Bleil, M.E., Adler, N.E., 2012. Psychological distress and in Vitro fertilization outcome. Fertility and Sterility. 98 (2), 459 – 464. Polit, D.E., Beck, C.T., 2008. Nursing Research. Generating and assessing evidence for nursing practice. Wolters Kluwer health. Porter, M., Bhattacharya, S., 2007. Helping themselves to get pregnant: a qualitative longitudinal study on the information-seeking behaviour of infertile couples. Human reproduction. 23 (3), 567 – 572. Rittenberg, V., Seshadri, S., Sunkara, S.K., Sobaleva, S., Oteng-Ntim, E., El-Toukhy, T., 2011. Effect of body mass index on IVF treatment outcome: an updated systematic review and meta-analysis. Reproductive Biomedicine Online. 23, 421-439. Shugg, J., Liamputtong, P., 2002. Being female: the portrayal of women’s health in print media. Health Care for Women International. 23, 715-728. Skoog Svanberg, A., Lampic, C., Karlström, P.O., Tydén, T., 2006. Attitudes toward parenthood and awareness of fertility among postgraduate students in Sweden. Gend Med. 3 (3), 187-195. Stephens, A.J., Aubuchon, M., Schust, D.J., 2011. Antichlamydial Antibodies, Human Fertility, and Pregnancy Wastage. Infectious diseases in obstetrics and gynecology. Varghese, A.C., du Plessis, S.S., Agarwal, A., 2008. Male gamete survival at stake: causes and Solutions. Reproductive BioMedicine Online. 17 (6), 866-880. Wiser, A., Shalom-Paz, E., Leigh Reinblatt, S., Son, W.Y., Das, M., Tulandi, T., Holzer, H., 2012. Ovarian stimulation and intrauterine insemination in women aged 40 years or more. Reproductive BioMedicine Online. 24, 170– 173. World

Health Organisation. http://www.euro.who.int/en/what-we-do/health-topics/noncommunicablediseases/obesity. Geraadpleegd op 09-01-2012.

Xueyan, Z., Jian, L., Yiqun, G., Yiming, Z., Zhongxu, W., Guang, J., 2011. A pilot study on environmental and behavioral factors related to missed abortion. Environ Health Prev Med. 16, 273–278. Zegers-Hochschild, F., Adamson, G.D., de Mouzon, J., Ishihara, O., Mansour, R., Nygren, K., Sullivan, E., Vanderpoel, S., 2009. International Committee for Monitoring Assisted Reproductive Technology (ICMART) and the World Health Organization (WHO) revised glossary of ART terminology. Fertility and Sterility. 92 (5).

24

APPENDIX I: LITERATURESEARCH FOR EXISTING QUESTIONNAIRES Author and year

Title

Topics in the questionnaire

Validity of the questionnaire

Ali et al., 2011

Knowledge, perceptions and myths regarding infertility among selected adult population in Pakistan: a crosssectional study

 Knowledge of infertility (menstrual cycle, definition of infertility, effect of lifestyle factors)  Attitude towards infertility  How infertility affects marital outcomes

 Face-validity (2 experts)  Developed by a team

Bretherick et al., 2010

Fertility and aging: do reproductive-aged Canadian women know what they need to know?

 Age  Pregnancy rates and chances  Menstrual cycle

 Face validity (other researchers)  Pilot-study (small number of reproductive-aged university women)


Knowledge about infertility risk factors, fertility myths and illusory benefits of healthy habits in young people

 Risk factors (age, overweight, alcohol, smoking, stress, marijuana, sexual transmitted disease)  Fertility myths (sexual habits, living in the countryside, adopting,.. )  Healthy habits (exercise, never smoking or drinking,..)


Development and preliminary validation of the fertility status awareness tool: FertiSTAT

 Demographic factors (age, ethnicity,..)  Reproductive factors (endometriosis, pelvic surgery,..)  Lifestyle factors (smoking, alcohol,..)  Non-reproductive medical factors (cancer, diabetes mellitus,..)

Useful? Because? No Questionnaire was developed for research in not western culture

No Nothing about the effect of lifestyle factors on fertility

Yes Both the knowledge about the effect of maternal age and lifestyle factors are examined. No Validity of the questionnaire is not discussed.  Face-validity (experts)

No Because it’s meant to describe women’s fertility status, not to test their knowledge.

25

Hashiloni-Dolev et al., 2011

The fertility myth: Israeli students’ knowledge regarding age-related fertility decline and late pregnancies in an era of assisted reproduction technology

 Age-related fertility  Age-related fertility with IVF  Medical procedures that enable very late pregnancies  Family status and attitudes regarding parenting

 Pre-tested by colleagues  Pilot-study (15 students)


Lampic et al., 2006

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

 Intention to have children  Importance of having children  Behavioral intention in case of infertility  Conditions of importance for the decision to become a parent  Perceived life changes in connection with becoming a parent  Awareness of fertility (age, pregnancy rates and chances, menstrual cycle)

 Developed by a team of 4  3 Pilot-studies (60 students)


Maheshwari et al., 2007

Women’s awareness and perceptions of delay in childbearing

 Decision to delay childbearing  Awareness of limitations of fertility treatment  Existing age limits for access to fertility treatment  Tests for prediction of fertility

 Developed by a team of 4  Pilot-study (in several study-groups)


Skoog Svanberg et al., 2006

Attitudes toward parenthood and awareness of fertility among postgraduate students in Sweden

 The same questionnaire as Lampic et al was used  Addition: Obstacles for having children during postgraduate studies

 3 Stages of pilot testing (university students)


26

APPENDIX II The pilot study In the first phase of the pilot study five patients filled in the questionnaire in the company of the researcher. They were asked to think out loud and tell the researcher which questions they found difficult to answer. After they completed the questionnaire the researcher randomly repeated some answers to find out whether the respondent agreed with the given answer. For example the researcher would ask “is it true that you think an extra 25 women will get pregnant if they live in the countryside?”. This way the researcher tested if the respondent was aware of how strong she estimated the effect. To test the face validity of the questionnaire the researcher asked questions about the interpretation of certain terms. For example the researcher would ask “what does the term ‘experiencing an event’ mean to you?”. The researcher also asked the respondent if she had any overall questions or comments. None of the five respondents correctly identified the number 50 on the scale as ‘no effect’. Four of the five respondents found it difficult to distinguish a positive from negative effect on the scale. Four of the five respondents filled in the questions in the component miscarriage incorrect, by marking a positive effect when they actually meant to mark a negative effect on the scale. Only two of the five respondents agreed with the estimated effect they had filled in when the answer was repeated afterwards. Two of the five respondents confessed they filled in the questions regarding their own lifestyle. For example a respondent said; ‘I’m a smoker so I can’t answer that smoking has a negative effect on fertility’. Another respondent said; ‘I don’t do sports, so I have to answer that sport has no effect’. Two of the five respondents didn’t understand the term ‘units of alcohol’. One respondent didn’t know what ‘chlamydia (sexually transmitted disease)’ was. All respondents understood that the questions containing the term ‘experiencing an event’ were about stress. After this first phase of the pilot study some adjustments were made. The scale was supplemented with arrows in order to clarify the direction of the effect. Texts were placed above the arrows that said ‘less chance of pregnancy’, ‘no effect’ and ‘more chance of pregnancy’. The term ‘units of alcohol’ was added with ‘(glasses)’. The new obtained questionnaire was then pilot tested on another five fertility patients. All five of these respondents correctly identified the number 50 on the scale as ‘no effect’. Only one respondent found it difficult to distinguish a positive from negative effect on the scale, and only one of the five respondents filled in the questions in the component miscarriage incorrect, by marking a positive effect when she actually meant to mark a negative effect on the scale. Still only two of the five respondents agreed with the estimated answers when those were repeated afterwards. One respondent confessed she filled in the questionnaire regarding her own lifestyle. She said; ‘I don’t do sports, so can’t answer that sport has a positive effect’. All respondents now understood the term ‘units (glasses) of alcohol’. All respondents understood that the questions containing the term ‘experiencing an event’ were about stress. The other part of the pilot study was a review of the questionnaire by an expert panel. Two professors who work as fertility doctors in the LUFC were asked to criticize the content of the questionnaire. The experts had to rate each question of the questionnaire for its relevance. Rating options were ‘not relevant’, ‘somewhat relevant’, ‘relevant’ and ‘very relevant’. Also comments were asked per component. In the components ‘fertility treatment’ and ‘miscarriage’ the questions on sexuality were left out because the researcher had not find any evidence of a connection between those. The experts had to indicate whether they agreed on leaving out these questions. The experts also had to name any missing risks, healthy habits or myths. And they were asked whether they had any overall comments on the questionnaire. No questions were rated ‘not relevant’ by the first expert. The second expert rated all the questions about sexuality ‘not relevant’. She believed these questions would cause patients to believe in these myths, rather than

27

that they would help them making a distinction between the risks and myths. The first expert found the question about the effect on fertility treatment of ‘having ever had chlamydia’ to unspecific, because the effect of chlamydia depends on the severity of the infection, the treatment, the complications and the type of fertility treatment. The second expert agreed on leaving out the questions about sexuality in the components ‘fertility treatment’ and ‘miscarriage’. The first expert however pointed out that there is some evidence that suggests sexuality has an effect on fertility treatment. For example lying down for 20 minutes after IUI (the questionnaire contains a question that asks whether lying down for 10 minutes after sex has an effect) would improve the pregnancy-rate as was demonstrated in a RCT, just as sexual intercourse after ET as was demonstrated in a study on animals. The first expert didn’t miss any risks in the questionnaire. As for the myths he missed a question about female orgasm and about position of the man and woman during sexual intercourse. The second expert pointed out that the woman’s profession as risk factor was missing. She more specific named the effects of anesthetic gasses, solvents, pesticides and paint. As for the myths she missed questions about frequency and timing of sexual intercourse. Other comments of the experts were unclear age categories, doubts about the distinction between smoking marijuana less and more than 4 times a week, the need for an example question per category and the need for more attention for the effect of stress in all three components of the questionnaire. Based on the second phase of the pilot study and the opinion of the experts, only one adjustment was made in the questionnaire. The example question was supplemented with two more example questions, one for each component in the questionnaire. If the researchers would have act on the other comments and suggestions, this would have implied changes in the questionnaire that would make it impossible to compare the results of this study with the study conducted by Bunting & Boivin. Therefore no questions were left out or supplemented to the questionnaire.

28

APPENDIX III

De kennis van fertiliteitspatiënten over het effect van leefstijlfactoren en leeftijd op de vruchtbaarheid, vruchtbaarheidsbehandeling en de kans op een miskraam.

Deze vragenlijst dient men in het fertiliteitscentrum in te vullen en direct daarna achter te laten in de groene doos die men in de wachtruimte aantreft, evenals het losse toestemmingsformulier.

De vragenlijst mag niet mee naar huis genomen worden.

Opdrachtgever:

Leuvens Universitair Fertiliteitscentrum

Onderzoekers:

Fieke van Asseldonk Eline Dancet Prof. Dr. T. D’Hooghe

29

Patiënteninformatie De kennis van fertiliteitspatiënten over het effect van leefstijlfactoren en leeftijd op de vruchtbaarheid, vruchtbaarheidsbehandeling en de kans op een miskraam. Opdrachtgever: Centrum voor Ziekenhuis- en Verplegingswetenschap van de Katholieke Universiteit Leuven Algemeen U wordt uitgenodigd om anoniem deel te nemen aan een wetenschappelijk onderzoek dat als doel heeft om de kennis te testen van fertiliteitspatiënten over het effect van leefstijlfactoren en leeftijd op de vruchtbaarheid, vruchtbaarheidsbehandeling en de kans op een miskraam. In de tekst hieronder en tijdens een toelichting wordt u uitgelegd wat de bedoeling van deze studie is en wat een eventuele deelname voor u betekent. Vooraleer te beslissen al dan niet deel te nemen aan dit onderzoek, vragen we u deze informatie aandachtig te lezen. Indien u bereid bent om aan deze studie deel te nemen, vragen we u op de losse bladzijde (het toestemmingsformulier) uw naam, de datum en uw handtekening te plaatsen. Deze studie werd beoordeeld en goedgekeurd door de Commissie voor Medische Ethiek van de UZ/K.U.Leuven. U dient deze goedkeuring niet te beschouwen als een aansporing tot deelname aan deze studie. Wel heeft deze commissie als taak te waken over uw rechten als patiënt conform de wet van 7 mei 2004 aangaande experimenten op de menselijke persoon en volgens de code van Good Clinical Practice ( ICH/GCP) en de verklaring van Helsinki (laatste versie). Praktische uitvoering van het onderzoek: U dient (anoniem) een vragenlijst in te vullen waarin zowel demografische- als kennisvragen worden gesteld. De vragenlijst zal worden ingevuld terwijl u in het fertiliteitscentrum aanwezig bent. Mogelijke voor- en nadelen: Dit onderzoek brengt voor u geen risico’s met zich mee. Dit onderzoek levert u daarnaast ook geen voordeel op. Wij zijn ons ervan bewust dat we toch een inspanning van u vragen. Door deel te nemen maakt u onderdeel uit van een wetenschappelijk onderzoek. Wij hopen op de lange termijn de fertiliteitszorg te kunnen optimaliseren door gebruik te maken van de resultaten die deze studie op zal leveren. Kosten en vergoeding: Deelname aan dit onderzoek zal geen kosten met zich meebrengen, noch voor u, noch voor de ziekteverzekering.

30

Verzekering: Indien u schade oploopt ten gevolge van deelname aan deze studie zal de schade vergoed worden conform de Belgische wet aangaande experimenten op de menselijke persoon van 7 mei 2004. Volgens deze wet is de opdrachtgever van het onderzoek, (Centrum voor Ziekenhuis- en Verplegingswetenschap van de Katholieke Universiteit Leuven), zelfs foutloos aansprakelijk voor alle schade die de deelnemer en/of zijn rechthebbenden oplopen en die rechtstreeks dan wel onrechtstreeks verband houdt met de proef. De opdrachtgever heeft een verzekering afgesloten die deze aansprakelijkheid dekt. Vrijwillige deelname: U bent volledig vrij om te beslissen al dan niet aan dit onderzoek deel te nemen. Indien u beslist om niet deel te nemen zal u hierdoor op geen enkele manier nadeel ondervinden. Bovendien heeft u het recht om op ieder ogenblik de deelname aan de studie stop te zetten, zonder hiervoor een verklaring te moeten geven. Vertrouwelijkheid: De Belgische Wet van 11 december 1998 betreffende de bescherming van het privéleven en de Belgische Wet van 22 augustus 2002 met betrekking tot de patiëntenrechten worden gerespecteerd bij het uitvoeren van dit onderzoek. Alle persoonlijke informatie die tijdens deze studie wordt verzameld is bijgevolg strikt vertrouwelijk. Zij wordt enkel aangewend voor het doeleinde van deze studie. Alle persoonlijke informatie wordt gecodeerd. Uw identiteit wordt op geen enkele manier kenbaar gemaakt aan onbevoegde derden. Bij eventuele publicatie van de gegevens over deze studie zal nooit enige informatie bekend gemaakt worden die uw identiteit kan kenbaar maken. Opmerkingen: Bij eventuele vragen in verband met deze studie kan u zich steeds richten tot uw onderzoeker: Eline Dancet [email protected] 016 341836 Dit onderzoek wordt uitgevoerd onder supervisie van Prof. Dr. T. D’Hooghe. Bij eventuele vragen in verband met uw rechten als deelnemer aan deze studie kan u zich richten tot de ombudsdienst van uw ziekenhuis (016 34 48 18).

31

Beste Mevrouw, Met behulp van onderstaande anonieme vragenlijst trachten wij de kennis van fertiliteitspatiënten te testen over het effect van leefstijlfactoren en leeftijd op de vruchtbaarheid, vruchtbaarheids-behandelingen en de kans op een miskraam. Deel 1 van de vragenlijst bevat 14 demografische en medische vragen. Deze vragen zijn opgenomen zodat de onderzoeker de uitkomsten van de kennistest mogelijks kan relateren aan bepaalde demografische en medische omstandigheden. Deze gegevens zullen gebruikt worden om op anonieme wijze de deelnemers van het onderzoek te beschrijven. Deel 2 van de vragenlijst bevat 84 kennisvragen. Hieronder vindt u instructies voor het invullen van deze vragen. Instructies We zijn geïnteresseerd in de factoren die mogelijkerwijs een effect op de vruchtbaarheid hebben. Met vruchtbaarheid bedoelen we de mogelijkheid voor u en uw partner om zwanger te raken. We willen van u weten of u denkt dat deze factoren uw kans op een zwangerschap beïnvloeden. Bij iedere factor staat een schaalverdeling die gaat van 0 vrouwen tot 100 vrouwen (zie voorbeeld op de volgende pagina). Stel voor dat 100 vrouwen proberen om zwanger te raken, en gemiddeld zouden 50 vrouwen dit doel bereiken binnen 3 maanden. Nu willen we van u weten of u denkt dat de leefstijlfactor het aantal vrouwen dat zwanger raakt beïnvloedt. U antwoordt door een kruisje op de schaal te tekenen op een van de aangeduide getallen. Als u denkt dat de factor de kans op een zwangerschap verlaagt duidt u uw antwoord aan links van 50 vrouwen. Als u denkt dat de factor de kans op een zwangerschap verhoogt duidt u uw antwoord aan rechts van 50 vrouwen. Hoeveel u het kruisje naar links of rechts plaatst, hangt af van hoe sterk u het verhogende of verlagende effect inschat. Als u denkt dat een factor geen effect heeft op de vruchtbaarheid, dan duidt u ‘50 vrouwen’ aan op de schaalverdeling door een kruisje in de pijl te plaatsen. Overweeg iedere factor apart. Daarnaast zijn wij geïnteresseerd in de factoren die mogelijkerwijs een effect hebben op de slaagkans van een vruchtbaarheidsbehandeling. U antwoordt wederom door een kruisje op de schaalverdeling te tekenen. Als u denkt dat de slaagkans van een vruchtbaarheidsbehandeling verlaagd is door de factor dan plaatst u het kruisje links van 50 vrouwen, en bij een verhoogde kans rechts van 50 vrouwen. Als u denkt dat een factor geen effect heeft dan duidt u dat aan door een kruisje in de pijl te plaatsen. Overweeg iedere factor apart. Ten slotte zijn wij geïnteresseerd in de factoren die mogelijkerwijs de kans op een miskraam verhogen of verlagen. Met miskraam bedoelen we een spontane afbreking van de zwangerschap tot 20 weken. U antwoordt wederom door een kruisje op de schaalverdeling te tekenen. Als u denkt dat de factor de kans op een miskraam verlaagt dan plaatst u het kruisje links van 50 vrouwen, en bij een verhoogde kans op miskraam rechts van 50 vrouwen. Als u denkt dat een factor geen effect heeft dan duidt u dat aan door een kruisje in de pijl te plaatsen. Overweeg iedere factor apart. Het invullen van de vragenlijst neemt ongeveer 25 minuten van uw tijd in beslag. U mag geen hulpmiddelen gebruiken bij het invullen van de vragenlijst, noch informatie inwinnen bij derden. De vragenlijst mag niet mee naar huis worden genomen en later alsnog worden ingediend. Bij eventuele vragen in verband met deze studie kan u zich steeds richten tot uw onderzoeker: Eline Dancet, [email protected], 016 341836

Voorbeeld Geef aan welk effect ‘dagelijks 10 aardbeien eten’ zal hebben op de vruchtbaarheid van de vrouw. Als u bij deze vraag 85 aanduidt, betekent dit dat u denkt dat naast het gemiddelde van 50 vrouwen nog eens 35 extra vrouwen zwanger zullen raken binnen 3 maanden. Dit betekent een toename van 70% in het aantal vrouwen dat zwanger raakt, doordat zij dagelijks 10 aarbeien eten.

35 extra vrouwen zullen zwanger raken. Dit is een toename van 70% in het aantal zwangerschappen, veroorzaakt door de factor.

Als u daarentegen 15 aanduidt, betekent dit dat u denkt dat door het eten van aardbeien 35 vrouwen minder zwanger zullen raken dan de 50 die normaal gesproken zwanger raken binnen 3 maanden. Dit betekent een afname van 70% in het aantal vrouwen dat zwanger raakt, doordat zij dagelijks 10 aarbeien eten.

Er zullen 35 vrouwen minder zwanger raken. Dit is een afname van 70% in het aantal zwangerschappen, veroorzaakt door de factor.

Als u ‘geen effect’ aanduidt, betekent dit dat u denkt dat het eten van aardbeien geen effect heeft op de kans op zwangerschap. Er zullen binnen 3 maanden niet meer, maar ook niet minder vrouwen zwanger raken door het eten van 10 aardbeien per dag.

Het gemiddelde van 50 vrouwen zal zwanger raken, niet meer en niet minder. Het eten van dagelijks 10 aardbeien heeft dus geen effect.

33

DEEL 1. DEMOGRAFISCHE EN MEDISCHE VRAGEN 1. Wat is uw leeftijd?

jaar

2. Wat is uw hoogst voltooide opleiding?

o

Middelbaar onderwijs BSO

o

Middelbaar onderwijs TSO

o

Middelbaar onderwijs ASO

o

Hoger onderwijs

o

Universitair onderwijs

o

Anders namelijk:

3. Probeerde u reeds meer dan 12 maanden zwanger te worden door het hebben van regelmatige onbeschermde betrekkingen? o

Ja

o

Neen

4. Sinds wanneer tracht u zwanger te worden?

__

-____

(maand – jaar)

5. Wanneer bezocht u voor het eerst een fertiliteitskliniek voor uw huidige kinderwens?

__

-___

_ (maand – jaar)

6. Heeft u reeds kinderen?

o

Ja, aantal:

o

Neen

34

7. Indien u reeds kinderen heeft, werd minimaal 1 van deze kinderen verwekt als gevolg van een vruchtbaarheidsbehandeling?

o

Ja

o

Neen

o

Niet van toepassing

8. Heeft u ooit een miskraam gehad?

o

Ja

o

Neen

9. Heeft u reeds andere fertiliteitsklinieken dan uw huidige (Leuvens Universitair Fertiliteitscentrum, UZ Leuven Gasthuisberg) bezocht? o

Ja, namelijk:

o

Neen

10. Heeft u uw huisarts geraadpleegd in verband met uw kinderwens? o

Ja

o

Neen

11. Heeft u een gynaecoloog die niet verbonden is aan een fertiliteitskliniek geraadpleegd in verband met uw kinderwens? o

Ja

o

Neen

35

12. Welke behandelingen en hoeveel van deze behandelingen heeft u reeds volledig doorlopen (tot en met het vernemen van het zwangerschapsresultaat)? o

Opvolging van uw cyclus met advies over de vruchtbare periode zonder ovulatie-inductie (medicijnen die het rijpen van de eicel stimuleren) en zonder inseminatie Aantal behandelingen:

o

Opvolging van uw cyclus met advies over de vruchtbare periode met ovulatie-inductie (medicijnen die het rijpen van de eicel stimuleren) en zonder inseminatie Aantal behandelingen:

o

IUI (inseminatie) zonder ovulatie-inductie (medicijnen die het rijpen van de eicel stimuleren) Aantal behandelingen:

o

IUI (inseminatie) met ovulatie-inductie (medicijnen die het rijpen van de eicel stimuleren) Aantal behandelingen:

o

IVF (reageerbuisbevruchting ofwel In Vitro Fertilisatie) Aantal behandelingen:

o

ICSI (reageerbuisbevruchting ofwel Intra Cytoplasmatische Sperma Injectie) Aantal behandelingen:

o

Andere: Aantal behandelingen:

o

Niet van toepassing, ik heb nog geen volledige behandeling (tot en met het vernemen van het zwangerschapsresultaat) doorlopen.

13. Wat is de oorzaak van uw vruchtbaarheidsproblemen? o

Mannelijke oorzaak

o

Vrouwelijke oorzaak

o

Mannelijke en vrouwelijke oorzaak

o

Geen duidelijke oorzaak

14. Hoe zou u over het algemeen uw gezondheid noemen? o

Slecht

o

Matig

o

Goed

o

Zeer goed

o

Uitstekend 36

DEEL 2. KENNISVRAGEN 2.1.

Het effect op de VRUCHTBAARHEID Duidt op de schaalverdeling het effect aan dat elk van de volgende factoren heeft op de vruchtbaarheid van de vrouw. U antwoordt door een kruisje op de schaal te plaatsen.

1.

Geef aan welk effect ‘24 jaar of jonger zijn’ zal hebben op de vruchtbaarheid van de vrouw.

2.

Geef aan welk effect ‘tussen de 25 en 34 jaar oud zijn’ zal hebben op de vruchtbaarheid van de vrouw.

3.

Geef aan welk effect ‘tussen 35 en 39 jaar oud zijn’ zal hebben op de vruchtbaarheid van de vrouw.

4.

Geef aan welk effect ‘tussen 40 en 44 jaar oud zijn’ zal hebben op de vruchtbaarheid van de vrouw.

5.

Geef aan welk effect ‘45 jaar of ouder zijn’ zal hebben op de vruchtbaarheid van de vrouw.

6.

Geen aan welk effect ‘een normaal gewicht hebben’ zal hebben op de vruchtbaarheid van de vrouw.

37

7.

Geef aan welk effect ‘overgewicht hebben’ zal hebben op de vruchtbaarheid van de vrouw.

8.

Geef aan welk effect ‘nooit roken’ zal hebben op de vruchtbaarheid van de vrouw.

9.

Geef aan welk effect ‘gemiddeld 1 – 9 sigaretten roken per dag’ zal hebben op de vruchtbaarheid van de vrouw.

10.

Geef aan welk effect ‘gemiddeld 10 -19 sigaretten roken per dag’ zal hebben op de vruchtbaarheid van de vrouw.

11.

Geef aan welk effect ‘gemiddeld meer dan 20 sigaretten roken per dag’ zal hebben op de vruchtbaarheid van de vrouw.

12.

Geef aan welk effect ‘nooit alcohol drinken’ zal hebben op de vruchtbaarheid van de vrouw.

38

13.

Geef aan welk effect ‘minder dan 14 eenheden (glazen) alcohol drinken per week’ zal hebben op de vruchtbaarheid van de vrouw.

14.

Geef aan welk effect ‘meer dan 14 eenheden (glazen) alcohol drinken per week’ zal hebben op de vruchtbaarheid van de vrouw.

15.

Geef aan welk effect ‘een gebeurtenis meemaken waar je mee om kunt gaan’ zal hebben op de vruchtbaarheid van de vrouw.

16.

Geef aan welk effect ‘een gebeurtenis meemaken waar je moeilijk mee om kunt gaan’ zal hebben op de vruchtbaarheid van de vrouw.

17.

Geef aan welk effect ‘een gebeurtenis meemaken waar je haast onmogelijk mee om kunt gaan’ zal hebben op de vruchtbaarheid van de vrouw.

18.

Geef aan welk effect ‘minder dan 7 minuten sporten per dag’ zal hebben op de vruchtbaarheid van de vrouw.

39

19.

Geef aan welk effect ‘tussen 7 en 59 minuten sporten per dag’ zal hebben op de vruchtbaarheid van de vrouw.

20.

Geef aan welk effect ‘ooit chlamydia (seksueel overdraagbare aandoening) gehad hebben’ zal hebben op de vruchtbaarheid van de vrouw.

21.

Geef aan welk effect ‘nooit marihuana gebruikt hebben’ zal hebben op de vruchtbaarheid van de vrouw.

22.

Geef aan welk effect ‘minder dan 4 keer per week marihuana roken’ zal hebben op de vruchtbaarheid van de vrouw.

23.

Geef aan welk effect ‘meer dan 4 keer per week marihuana roken’ zal hebben op de vruchtbaarheid van de vrouw.

24.

Geef aan welk effect ‘5 porties fruit en groenten per dag eten’ zal hebben op de vruchtbaarheid van de vrouw.

40

25.

Geef aan welk effect ‘niet urineren na seks’ zal hebben op de vruchtbaarheid van de vrouw.

26.

Geef aan welk effect ‘een kussen onder de heupen van de vrouw plaatsen tijdens en na seks’ zal hebben op de vruchtbaarheid van de vrouw.

27.

Geef aan welk effect ‘10 minuten gaan liggen na seks’ zal hebben op de vruchtbaarheid van de vrouw.

28.

Geef aan welk effect ‘op het platteland wonen’ zal hebben op de vruchtbaarheid van de vrouw.

29.

Geef aan welk effect ‘in de stad wonen’ zal hebben op de vruchtbaarheid van de vrouw.

30.

Geef aan welk effect ‘een baby adopteren’ zal hebben op de vruchtbaarheid van de vrouw.

41

2.2. Het effect op VRUCHTBAARHEIDSBEHANDELINGEN Duidt op de schaalverdeling het effect aan dat elk van de volgende factoren heeft op de slaagkans van een vruchtbaarheidsbehandeling. U antwoordt door een kruisje op de schaal te plaatsen. 31.

Geef aan welk effect ‘24 jaar of jonger zijn’ zal hebben op de slaagkans van een vruchtbaarheidsbehandeling.

32.

Geef aan welk effect ‘tussen de 25 en 34 jaar oud zijn’ zal hebben op de slaagkans van een vruchtbaarheidsbehandeling.

33.

Geef aan welk effect ‘tussen 35 en 39 jaar oud zijn’ zal hebben op de slaagkans van een vruchtbaarheidsbehandeling.

34.

Geef aan welk effect ‘tussen 40 en 44 jaar oud zijn’ zal hebben op de slaagkans van een vruchtbaarheidsbehandeling.

35.

Geef aan welk effect ‘45 jaar of ouder zijn’ zal hebben op de slaagkans van een vruchtbaarheidsbehandeling.

42

36.

Geef aan welk effect ‘een normaal gewicht hebben’ zal hebben op de slaagkans van een vruchtbaarheidsbehandeling.

37.

Geef aan welk effect ‘overgewicht hebben’ zal hebben op de slaagkans van een vruchtbaarheidsbehandeling.

38.

Geef aan welk effect ‘nooit roken’ zal hebben op de slaagkans van een vruchtbaarheidsbehandeling.

39.

Geef aan welk effect ‘gemiddeld 1 – 9 sigaretten roken per dag’ zal hebben op de slaagkans van een vruchtbaarheidsbehandeling.

40.

Geef aan welk effect ‘gemiddeld 10 -19 sigaretten roken per dag’ zal hebben op de slaagkans van een vruchtbaarheidsbehandeling.

41.

Geef aan welk effect ‘gemiddeld meer dan 20 sigaretten roken per dag’ zal hebben op de slaagkans van een vruchtbaarheidsbehandeling.

43

42.

Geef aan welk effect ‘nooit alcohol drinken’ zal hebben op de slaagkans van een vruchtbaarheidsbehandeling.

43.

Geef aan welk effect ‘minder dan 14 eenheden (glazen) alcohol drinken per week’ zal hebben op de slaagkans van een vruchtbaarheidsbehandeling.

44.

Geef aan welk effect ‘meer dan 14 eenheden (glazen) alcohol drinken per week’ zal hebben op de slaagkans van een vruchtbaarheidsbehandeling.

45.

Geef aan welk effect ‘een gebeurtenis meemaken waar je mee om kunt gaan’ zal hebben op de slaagkans van een vruchtbaarheidsbehandeling.

46.

Geef aan welk effect ‘een gebeurtenis meemaken waar je moeilijk mee om kunt gaan’ zal hebben op de slaagkans van een vruchtbaarheidsbehandeling.

44

47.

Geef aan welk effect ‘een gebeurtenis meemaken waar je haast onmogelijk mee om kunt gaan’ zal hebben op de slaagkans van een vruchtbaarheidsbehandeling.

48.

Geef aan welk effect ‘minder dan 7 minuten sporten per dag’ zal hebben op de slaagkans van een vruchtbaarheidsbehandeling.

49.

Geef aan welk effect ‘tussen 7 en 59 minuten sporten per dag’ zal hebben op de slaagkans van een vruchtbaarheidsbehandeling.

50.

Geef aan welk effect ‘ooit chlamydia (seksueel overdraagbare aandoening) gehad hebben’ zal hebben op de slaagkans van een vruchtbaarheidsbehandeling.

51.

Geef aan welk effect ‘nooit marihuana gebruikt hebben’ zal hebben op de slaagkans van een vruchtbaarheidsbehandeling.

52.

Geef aan welk effect ‘minder dan 4 keer per week marihuana roken’ zal hebben op de slaagkans van een vruchtbaarheidsbehandeling.

45

53.

Geef aan welk effect ‘meer dan 4 keer per week marihuana roken’ zal hebben op de slaagkans van een vruchtbaarheidsbehandeling.

54.

Geef aan welk effect ‘5 porties fruit en groenten per dag eten’ zal hebben op de slaagkans van een vruchtbaarheidsbehandeling.

55.

Geef aan welk effect ‘op het platteland wonen’ zal hebben op de slaagkans van een vruchtbaarheidsbehandeling.

56.

Geef aan welk effect ‘in de stad wonen’ zal hebben op de slaagkans van een vruchtbaarheidsbehandeling.

57.

Geef aan welk effect ‘een baby adopteren’ zal hebben op de slaagkans van een vruchtbaarheidsbehandeling.

46

2.3. Het effect op de kans op een MISKRAAM Duidt op de schaalverdeling het effect aan dat elk van de volgende factoren heeft op de kans op een miskraam. U antwoordt door een kruisje op de schaal te plaatsen. Let op: in tegenstelling tot bij de vorige twee onderdelen zal u nu aan de linkerkant van de schaalverdeling een kruisje plaatsen bij een gevoelsmatig ‘positief’ effect. Het is immers positief wanneer minder vrouwen een miskraam krijgen. 58.

Geef aan welk effect ‘24 jaar of jonger zijn’ zal hebben op de kans op een miskraam.

59.

Geef aan welk effect ‘tussen de 25 en 34 jaar oud zijn’ zal hebben op de kans op een miskraam.

60.

Geef aan welk effect ‘tussen 35 en 39 jaar oud zijn’ zal hebben op de kans op een miskraam.

61.

Geef aan welk effect ‘tussen 40 en 44 jaar oud zijn’ zal hebben op de kans op een miskraam.

62.

Geef aan welk effect ‘45 jaar of ouder zijn’ zal hebben op de kans op een miskraam.

47

63.

Geef aan welk effect ‘een normaal gewicht hebben’ zal hebben op de kans op een miskraam.

64.

Geef aan welk effect ‘overgewicht hebben’ zal hebben op de kans op een miskraam.

65.

Geef aan welk effect ‘nooit roken’ zal hebben op de kans op een miskraam.

66.

Geef aan welk effect ‘gemiddeld 1 – 9 sigaretten roken per dag’ zal hebben op de kans op een miskraam.

67.

Geef aan welk effect ‘gemiddeld 10 -19 sigaretten roken per dag’ zal hebben op de kans op een miskraam.

68.

Geef aan welk effect ‘gemiddeld meer dan 20 sigaretten roken per dag’ zal hebben op de kans op een miskraam.

48

69.

Geef aan welk effect ‘nooit alcohol drinken’ zal hebben op de kans op een miskraam.

70.

Geef aan welk effect ‘minder dan 14 eenheden (glazen) alcohol drinken per week’ zal hebben op de kans op een miskraam.

71.

Geef aan welk effect ‘meer dan 14 eenheden (glazen) alcohol drinken per week’ zal hebben op de kans op een miskraam.

72.

Geef aan welk effect ‘een gebeurtenis meemaken waar je mee om kunt gaan’ zal hebben op de kans op een miskraam.

73.

Geef aan welk effect ‘een gebeurtenis meemaken waar je moeilijk mee om kunt gaan’ zal hebben op de kans op een miskraam.

74.

Geef aan welk effect ‘een gebeurtenis meemaken waar je haast onmogelijk mee om kunt gaan’ zal hebben op de kans op een miskraam.

49

75.

Geef aan welk effect ‘minder dan 7 minuten sporten per dag’ zal hebben op de kans op een miskraam.

76.

Geef aan welk effect ‘tussen 7 en 59 minuten sporten per dag’ zal hebben op de kans op een miskraam.

77.

Geef aan welk effect ‘ooit chlamydia (seksueel overdraagbare aandoening) gehad hebben’ zal hebben op de kans op een miskraam.

78.

Geef aan welk effect ‘nooit marihuana gebruikt hebben’ zal hebben op de kans op een miskraam.

79.

Geef aan welk effect ‘minder dan 4 keer per week marihuana roken’ zal hebben op de kans op een miskraam.

80.

Geef aan welk effect ‘meer dan 4 keer per week marihuana roken’ zal hebben op de kans op een miskraam.

50

81.

Geef aan welk effect ‘5 porties fruit en groenten per dag eten’ zal hebben op de kans op een miskraam.

82.

Geef aan welk effect ‘op het platteland wonen’ zal hebben op de kans op een miskraam.

83.

Geef aan welk effect ‘in de stad wonen’ zal hebben op de kans op een miskraam.

84.

Geef aan welk effect ‘een baby adopteren’ zal hebben op de kans op een miskraam.

Bedankt voor uw deelname aan deze studie! Aan de hand van de resultaten van deze studie zal een brochure ontwikkeld worden. In deze brochure zullen de onderwerpen uitgewerkt worden uit deze vragenlijst waarover kennis ontoereikend bleek bij de fertiliteitspatiënten die deelnamen aan de studie. De brochure zal rond januari 2013 beschikbaar zijn in het fertiliteitscentrum van UZ Leuven. 51

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

Recommend Documents