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The effect of health-promoting lifestyle education on the treatment of unexplained female infertility
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Contents lists available at ScienceDirect
European Journal of Obstetrics & Gynecology and Reproductive Biology journal homepage: www.elsevier.com/locate/ejogrb
The effect of health-promoting lifestyle education on the treatment of unexplained female infertility
1 2
3 Q1
Yeliz Kayaa,* , Nezihe Kizilkaya Bejib , Yunus Aydinc , Hikmet Hassac
4 5 6
a b c
Q2
Eskişehir Osmangazi University, Faculty of Health Sciences, Department of Nursing, Eskişehir, Turkey Biruni University, Faculty of Health Sciences, Department of Nursing, Istanbul, Turkey Eskişehir Osmangazi University, Faculty of Medicine, Department of Gynecology and Obstetrics, Reproductive Endocrinology and Infertility, Eskişehir, Turkey
A R T I C L E I N F O
A B S T R A C T
Article history: Received 14 May 2016 Received in revised form 23 July 2016 Accepted 24 October 2016 Available online xxx
Objective: This study aimed to reveal the 1) awareness, 2) improvements of a health-promoting lifestyle on women with unexplained infertility having at least one of the risk factors that have been indicated to negatively affect fertility (smoking, body mass index lower than 18.5 kg/m2 and more than 25 kg/m2, over-exercising or not exercising at all, alcohol consumption, caffeine consumption of more than 300 mg/day, and high levels of stress) by means of health-promoting lifestyle education, 3) the effect of this improvement on the result of assisted-reproduction treatment in terms of clinical pregnancy. Study design: 64 women diagnosed with unexplained infertility were divided into a group receiving Health-Promoting Lifestyle (HPL) education and a control group. 1) Risk Factors Questionnaire (BMI, Smoking, Alcohol, Stress, Exercise, Caffeine), 2) Depression, Anxiety and Stress Scale, 3) HealthPromoting Lifestyle Profile II. The health promoting lifestyle was given to the education group. The Risk Factors Questionnaire; Depression, Anxiety, Stress Scale and Healthcare-Promoting Lifestyle Profile II were also administered after the first-second-third month of education but before ART treatment. Results: A statistically significant decrease was found in the average levels of four variables as; BMI (p < 0.001)-stress (p < 0.001)-caffeine consumption (p < 0.001)-lower exercise levels (p < 0.001). Moreover, the total number of risk factors that females had between the first and third interview decreased significantly. Clinical pregnancy rate after ART was 12 (46.15%) and 5 (19.24%) in education and control group consequently (p = 0.02). Conclusion: Health-promoting lifestyle education was found to be effective in reducing the lifestyle risk factors for infertility and increasing the success rates of assisted reproduction treatment by correcting these risk factors. ã 2016 Elsevier Ireland Ltd. All rights reserved.
Keywords: Lifestyle Infertility Assisted reproduction
7 8 9 10 11 12 13 14 15
Introduction Patients should always try to manage the lifestyle factors that can contribute to infertility, and the effectiveness of infertility treatment, despite technical developments in the treatment of infertility. The most frequently observed risk factors for infertility are smoking, body mass index (BMI) lower than 18.5 kg/m2 and higher than 25 kg/m2, over-exercising or not exercising at all, alcohol consumption, caffeine consumption of more than 300 mg/ day, and stress. It seems that smoking negatively affects follicle
lık Bilimleri Fakültesi, * Corresponding author at: ESOGÜ Meşelik Yerleşkesi Sag 26480 Eskişehir, Turkey. Fax: +90 222 229 26 95. E-mail address: [email protected] (Y. Kaya).
development, ovulation and fertilization [1–5]. BMI > 25 kg/m2 and BMI < 20 kg/m2 were found to cause infertility in both females and males [6,7]. In addition, treatment of fertility was observed to be less successful in overweight and obese individuals [1,8–11]. Caffeine consumption of more than 300 mg/day is considered to be a risk factor in females in their reproductive years [1,5,11] and stress may affect the nervous and endocrine systems, and thereby Q3 fertility [5]. Additonally, information on reducing the negative effects of these factors on fertility by taking up a health-promoting lifestyle is gradually increasing [3,4,11]. Although evidence has been found of the positive effects of a health-promoting lifestyle on infertility, no randomised controlled studies were found in literature which analyzed the effect of these risk factors on the success of assistedreproduction treatment in cases of unexplained infertility [1,3,4].
http://dx.doi.org/10.1016/j.ejogrb.2016.10.050 0301-2115/ã 2016 Elsevier Ireland Ltd. All rights reserved.
Please cite this article in press as: Y. Kaya, et al., The effect of health-promoting lifestyle education on the treatment of unexplained female infertility, Eur J Obstet Gynecol (2016), http://dx.doi.org/10.1016/j.ejogrb.2016.10.050
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This study aimed to reveal the 1) awareness, 2) improvements of a health-promoting lifestyle on women with unexplained infertility having at least one of the risk factors that have been indicated to negatively affect fertility (smoking, body mass index lower than 18.5 kg/m2 and more than 25 kg/m2, over-exercising or not exercising at all, alcohol consumption, caffeine consumption of more than 300 mg/day, and high levels of stress) by means of health-promoting lifestyle education, 3) the effect of this improvement onthe result of assisted-reproduction treatment in terms of clinical pregnancy.
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Materials and method
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Following the Local Ethics Committee approval, the study was conducted between July 1st 2014 and June 31st 2015 in the Reproductive Health Center of Eskişehir Osmangazi University’s Faculty of Medicine. The Risk Factors Questionnaire and Depression, Anxiety and Stress Scale were completed by the women who were diagnosed with unexplained infertility and had at least two unsuccessful intra-uterine inseminations. Of 109 females; 13 could not be reached again, 17 did not agree to participate in the study, and 6 did not attend their scheduled interview despite agreeing to participate; therefore 73 females having at least one risk factor were included in the study. The file numbers of the females were divided into two groups, with file numbers ending with an odd number being assigned to the education group to ensure randomness. A power analysis was made to determine the number of participants for each groups. This analysis was based on the “ongoing pregnancy rate” in the study of Lledo et al., and the power analysis result obtained by comparing two independent rates in the Fischer-Exact Test showed that there should be at least 26 participants in both groups for a power of 80% to increase the pregnancy rate by more than 10% [12]. The education group and control group included 33 and 40 females respectively. 1) A Risk Factors Questionnaire 2) Depression, Anxiety and Stress Scale, 3) Health-Promoting Lifestyle Profile II were given to all study participants. The health promoting lifestyle education was given to the education group. The Risk Factors Questionnaire and Depression, Anxiety, Stress Scale were also administered after the first, second and third month of education and HealthPromoting Lifestyle Profile II was administered after the third month of education but before ART treatment.
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Risk Factors Questionnaire
73
84
This questionnaire was prepared by the researchers in line with literature and included open and closed questions. The participants’ height and weight were measured and recorded to determine their BMIs. The BMI value was obtained by dividing the weight value (kilogram) by the height value (meters) [13]. A BMI of lower than 18.5 kg/m2 and more than 25 kg/ m2 was accepted as a risk factor [1,6–10,14]. The following factors were accepted as risk factors: Daily smoking or passive smoking [1–5], consumption of one glass of alcohol or more per week [15,16], caffeine consumption of more than 300 mg daily [1,5,11], Not exercising at all, or doing heavy exercise for more than four hours per week [17] and stress [5].
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The Depression, Anxiety and Stress Scale
43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70
74 75 76 77 78 79 80 81 82 83
86 87 88 89 90
The Depression, Anxiety and Stress Scale (DASS) developed by Lovibond and Lovibond in 1995 consists of 42 questions: 14 questions on depression, 14 questions on anxiety, and 14 questions on stress [18]. High scores on each of the depression, anxiety and stress subscales of this indicate that the individual has the said
problem. Scores of 14 and above on the subscale were accepted as a stress risk factor [5].
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Health-Promoting Lifestyle Profile II
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The Health-Promoting Lifestyle Profile (HPLP) was developed by Walker et al. and originally had 48 questions [19]. Four questions were added later by Walker and Hill-Polerecky. The 52 questions measure the health-promoting behaviors of individuals [20]. There are six subscales: self-actualization, health responsibility, exercise, nutrition, interpersonal support and stress management. Each subscale can be used independently. The total score of the subscales is the total score of the HPLP. The lowest and highest scores of the scale are 52 and 216, respectively. Higher scores indicate that the individual shows the said health behaviors at a high level. The education group was given Health-Promoting Lifestyle Education (HPLE) by the researcher (Y.K.) who is a specialist in infertility nursing and healthy lifestyle programmes. This education was prepared by the researchers in line with literature, and included information on the effects of the six behaviors most found to prevent pregnancy and successful IVF/ICSI and suggestions as to how to change these behaviors to a healthpromoting lifestyle, based on the 2010 Cochrane Database [3,4]. Verbal narration, written and visual education materials were used during this education process. Within the scope of this education, face-to-face interviews were conducted in a separate room in the reproductive health center for approximately 15– 20 min at a time. Afterwards, the content was gathered in a booklet and distributed to the participants to ensure continuity of the education. A telephone interview was conducted monthly over three months with each participant to provide support and to help them recognize the empowering results of positive health behaviors, to develop a positive point of view on the behaviors, and to improve self-monitoring. The barriers to these behaviors were discussed. At the end of each interview, objectives were determined to successfully continue the health-promoting behavior until the next interview. After the third monthly follow-up, three females in the education group and six females in the control group were excluded from the study because they could not be reached again by telephone. Additionally, as a result of the evaluation before embryo transfer, IVF/ICSI procedures, four females in the education group and eight females in the control group were canceled due to problems with the embryos. In conclusion, embryo transfer was made for 26 females in both groups. The b HcG values and fetal heartbeats of all females were analyzed on the 15th day and 4th week, respectively (Fig. 1).
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Statistical analysis
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The continuous data were given as average standard deviation, and the categorical data were given as percentage (%). The Shapiro Wilk test was used to analyze the appropriateness of the data to normal distribution. The Kruskal–Wallis H test was used to compare three and more groups not appropriate to normal distribution. The Wilcoxon test was used to compare the values of two groups in different measurement times. Two-way repeated measures ANOVA (One Factor Repetition) was used for repeated measures. The direction and size of the correlation was determined using the Pearson correlation analysis for the variables showing a normal distribution and the Spearman correlation coefficient for the variables showing an abnormal distribution. The analysis of the cross tables were made using Pearson Chi-Square. The analyses were made using IBM SPSS Statistics 21.0. p < 0.05 was considered to be the threshold for statistical significance
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3
UNEXPLAINED INFERTILE FEMALES (n=109)
RISK FACTORS QUESTIONNAIRE; DEPRESSION, ANXIETY AND STRESS SCALE
THE FEMALES WITH AT LEAST 1 RISK FACTOR (n=73)
SOCIODEMOGRAPHIC CHARACTERISTICS QUESTIONNAIRE HEALTH-PROMOTING LIFESTYLE PROFILE II
EDUCATION GROUP (n=33)
CONTROL GROUP (n=40)
EDUCATED NOT EDUCATED
FOLLOW-UP IVF/ICSI PRACTICE (n=34)
(Determinaon of the changes in the risk factors through phone interviews each month for 3 months)
β HcG evaluaon aer 15 days (n=26)
Fetal heartbeat (FH) evaluaon aer 4 weeks IVF/ICSI PRACTICE (n=30)
SUCCESS EVALUATION AFTER IVF/ICSI β HcG evaluaon aer 15 days (n=26)
Fetal heartbeat (FH) evaluaon aer 4 weeks
SUCCESS EVALUATION AFTER IVF/ICSI Fig. 1. Study flow chart. 153 154 155 156 157 158 159 160 161
Results No statistical difference was found between the sociodemographic characteristics of the two groups according to age, infertility period, education level, rate of working women and source of infertility information (Table 1). The characteristics of all participants related to the factors that affect fertility are shown in Table 2 and no statistically significant difference was found between the two groups in terms of the total number of risk factors and of each risk factor.
The education group was re-evaluated in the first, second and third months after the first interview in terms of risk factors. Despite the decrease in the risk factors of BMI and smoking by the third month, this difference was not statistically significant. However, a statistically significant decrease was found in the average levels of four variables; average BMI-stresscaffeine consumption and lower exercise levels (all p < 0.001). Moreover, the total number of risk factors that females had in the first and third interview decreased significantly (p < 0.001) (Table 3).
Please cite this article in press as: Y. Kaya, et al., The effect of health-promoting lifestyle education on the treatment of unexplained female infertility, Eur J Obstet Gynecol (2016), http://dx.doi.org/10.1016/j.ejogrb.2016.10.050
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Table 1 Comparison of the sociodemographic characteristics of the participants.
Age of women Age of man Period of infertility Education of women
Rate of working women Treatments for infertility
a b c
Q4
Ave. Sd Ave. Sd Ave. Sd None Elementary High school Associate degree University Intra-uterine insemination IVF/ICSI
Education group
Control group
Total
p
30 31.2 34.9 4.5 5.9 3.4 2 (6.7%) 15 (50%) 9 (30%) 3 (10%) 1 (3.3%) 7 (23.3%) 2.4 0.7 1.3 0.5
34 31.0 33.5 3.5 5.7 3.0 0 (0%) 17 (50%) 11 (32.4%) 5 (14.7%) 1 (2.9%) 5 (14.7%) 1.9 0.7 1.6 0.5
31.1 4.2 34.0 4.1 5.8 3.2 2 (3.1%) 32 (50%) 20 (31.3%) 8 (12.5%) 2 (3.1%) 12 (18.7%) 2.1 0.8 1.5 0.5
0.8a 0.08a 0.9b 0.7c
0.6c 0.09b 0.7b
Student T test. Mann–Whitney U test. Chi square test.
Table 2 Comparison of the risk factors of the participants.
BMI
Ave. Sd Risk factor (n)
Education group
Control group
Total
p
no yes
25.7 5.3 15 (50%) 15 (50%)
25.3 4.7 15 (44.1%) 19 (55.9%)
25.5 4.9 30 (46.9%) 34 (53.1%)
0.9a 0.8b
Smoking
Risk factor (n)
no yes
19 (63.3%) 11 (36.7%)
17 (50%) 17 (50%)
36 (43.7%) 28 (56.3%)
0.4b
Alcohol
Risk factor (n)
no yes
30 (100%) 0 (0%)
33 (97.1%) 1 (2.9%)
63 (98.4%) 1 (1.6%)
1.000b
Stress (DASS score)
Risk factor (n)
no yes
11 (36.7%) 19 (63.3%)
11 (32.3%) 23 (67.7%)
22 (32.4%) 42 (67.6%)
0.9b
Exercise
Risk factor (n)
no yes
4 (13.3%) 26 (86.7%)
6 (17.6%) 28 (82.4%)
10 (84.4%) 54 (15.6%)
0.7b
Caffeine (daily consumption (mg))
Risk factor (n)
no yes
11 (36.7%) 19 (63.3%)
15 (38.2%) 19 (55.9%)
24 (37.5%) 40 (62.5%)
1.000b
The number of existing risk factors
Ave. Sd
2.8 1.0
3.2 1.0
3.0 1.0
0.052a
a b
Mann–Whitney U test. Chi square test.
Table 3 Changes in the risk factors determined in the education group (n = 30) between the first interview and monthly follow-ups after education.
Risk factor that affect fertility
First month
Second month
Third month
Ave. Sd
Ave. Sd
Ave. Sd
Ave. Sd
25.3 4.6 n (%) 18 (60.0%) 12 (40.0%)
24.9 4.9 n (%) 19 (63.3%) 11 (36.6%)
24.8 4.8 n (%) 20 (66.6%) 10 (33.3%)
<0.001b
Risk factor
No Yes
25.7 5.3 n (%) 15 (50.0%) 15 (50.0%)
Smoking
Risk factor
No Yes
18 (60.0%) 12 (40.0%)
23 (76.7%) 7 (23.3%)
24 (80.0%) 6 (20.0%)
25 (83.3%) 5 (16.6%)
0.2c
Alcohol
Risk factor
No Yes
30 (100%) 0 (0%)
30 (100%) 0 (0%)
30 (100%) 0 (0%)
30 (100%) 0 (0%)
–
Stress (DASS score)
Risk factor
No Yes
11 (36.7%) 19 (63.3%)
13 (43.3%) 17 (56.6%)
27 (90.0%) 3 (10.0%)
27 (90.0%) 3 (10.0%)
<0.001c
Exercise
Risk factor (n)
No Yes
1 (3.33%) 29 (96.7%)
21 (70.0%) 9 (30.0%)
25 (83.3%) 5 (16.6%)
25 (83.3%) 5 (16.6%)
<0.001c
Caffeine (daily consumption (mg))
Risk factor
No Yes
11 (36.7%) 19 (63.3%)
23 (76.6%) 7 (23.3%)
25 (83.3%) 5 (16.6%)
28 (93.4%) 2 (6.6%)
<0.001c
The number of existing risk factors
Ave. Sd
2.8 1.0
1.3 1.0
0.8 0.8
0.6 0.8
<0.001d
BMI
a b c d
Ave. Sd
Pa
First interview
0.5c
Comparison of the findings of the first interview and the interview three months later. Two-way variance analysis test. Chi square test. Kruskal Wallis H test.
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Q5
Table 4 Comparison of the HPLP scores of all participants. HPLP subscales Health responsibility Exercise Nutrition Self-actualization Interpersonal support Stress management Total a b
Education Ave. Sd 19.2 4.1 12.4 4.4 21.1 5.8 24.1 4.7 24.3 4.7 17.1 4.5 118.0 22.5
Control
Total
18.4 3.0 13.7 5.4 22.7 2.7 24.1 2.8 23.5 2.9 15.2 2.8 118.0 16.5
18.7 3.6 13.1 5.0 22.0 4.5 24.1 3.8 23.9 3.9 16.1 3.8 118.0 19.4
p a
0.4 0.4b 0.1a 0.8b 0.9b 0.06a 0.9a
Student T test. Mann–Whitney U test.
Table 5 Comparison of the HPLP scores of the education group before and after education. HPLP subscales
Before education Ave. Sd
After education Ave. Sd
Pa
Health responsibility Exercise Nutrition Self-actualization Interpersonal support Stress management Total
19.2 4.1 12.4 4.4 21.1 5.8 24.1 4.7 24.3 4.7 17.1 4.5 118.0 22.5
20.9 3.3 19.4 3.2 23.3 4.5 25.0 3.8 24.8 4.0 18.7 3.2 132.5 18.2
<0.001 <0.001 <0.001 0.011 0.1 0.002 <0.001
a
172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190
Wilcoxon Signed Rank Test.
No statistically significant difference was found between the scores of the education and control groups on the HPLP and its subscales (Table 4). The HPLP was re-applied to the participants in the education group after the three-month follow-ups, and a statistically significant increase was seen in all subscale scores and the total score of the scale, except for the “interpersonal support” subscale (p < 0.05) (Table 5). Oocytes were collected from 30 of the infertile females in the education group and 34 of the infertile females in the control group. Due to problems with the embryos, transfers were made in 26 females in both groups. No statistically significant difference at baseline was found between the total number of oocytes, MII oocyte number, fertilization rate and the number of transferred embryos. The b HcG value of the embryo-transferred females was analyzed on the 15th day and all was found to be positive. Then, their fetal heartbeats were evaluated in the 4th week. Fetal heartbeat was found in 12 (46.15%) females in the education group and 5 (19.24%) females in the control group, which is a statistically significant difference (p = 0.02) (Table 6).
5
Comment
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In the present study we found that with a 3-month HPLE; the awareness of women of the risk factors for infertility and HPLP total score increased. While the total number of risk factors that females had in the first and third interview decreased significantly; especially the decrease of average BMI, caffeine consumption, stress levels and increase in exercise level were remarkable. Moreover, the clinical pregnancy rate after ART was significantly higher in women who had the 3-month HPLE compared to the control group. In terms of natural conception; obesity, smoking, and alcohol significantly affect fertility. There is also sufficient evidence that these lifestyle variables also have a negative influence on IVF outcome. ESHRE recommended that health-care providers should inform their patients about the importance of these problems and provide support in order to achieve the intended results for the target lifestyle changes [21]. It was shown that psychological stress is another variable that may also affect the outcome of IVF treatment [22]. Although the effect of an unhealthy lifestyle on infertility is clearly known and information is obtained from various sources, couples may still continue to demonstrate non-health-promoting behaviors [23–26]. Having the knowledge of the negative effect of these lifestyle variables seems insufficient; the major aims of health-care providers should be to increase the awareness of women about the risks of lifestyle variables on infertility and to support their patients in achieving the intended results. Homan et al. and Hammice et al. showed that health-promoting lifestyle education may increase the healthy lifestyle in infertile couples and in copules planning pregnancy [2,27]. According to our results; the awareness of women about risk factors and also changing in lifestyle habits in a healthier direction with HPLE increased in unexplained infertile women before ART. Infertility centers may become important practice centers to develop a health-promoting lifestyle for a community starved of information and ready to accept education [28]. However, there is a limited number of studies on changing the unhealthy lifestyles of women who are trying to become pregnant into health-promoting lifestyles and the effects of this change on the results of assisted reproduction [29]. In this present study, all risk factors improved in the education group and the clinical pregnancy rate was found to be 46.15% in the education group and 19.24% in the control group and in the fourth week, which is a statistically significant difference. The decrease in the risk factors, the significant increase in the HPL score, and the statistically high clinical pregnancy rate
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Table 6 Findings on the results of IVF/ICSI treatment of infertile females. Education group
Control group
Total
P
Number of collected oocytes
Ave. Sd
9.7 8.2 9.3 7.7
11.3 5.7 10.1 5.9
10.5 7.0 9.7 6.8
0.6a 0.2b
Number of MIII oocytes
Ave. Sd
6.3 5.9 6.1 5.1
6.0 3.0 5.6 3.1
6.1 4.6 5.8 4.4
1.000a 0.9b
Fertilization rate
Ave. Sd
81.0 22.5 69.8 35.2
84.2 19.8 64.4 40.1
82.6 21.0 66.9 37.7
0.5a 0.8b
Number of transferred embryos
Ave. Sd
1.3 0.4 1.1 0.6
1.1 0.3 0.8 0.5
1.2 0.4 0.9 0.6
0.09a 0.06b
12/26c (46.1%) 12/30d (40%)
5/26c (19.2%) 5/34d (14.8%)
17/52c (32.6%) 17/64d (26.5%)
0.02c,d
Clinical pregnancy n (%)
a b c d
Mann–Whitney U test. Intend to treat analysis (Mann–Whitnney U test). Chi square test. Intend to treat analysis (Chi square test).
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suggest that the education and monitoring of women with unexplained infertilility in developing a health-promoting lifestyle prior to assisted reproduction had positive effects on the treatment. However, we cannot be sure about the longterm probable positive effects of education and the decrease in pregnancy complications and longterm health. Termination of follow up with pregnancy is one of the most important limitations of our study but new trials with this aim will resolve this issue. Nurses could have a very important role in behavior-changing programs. Confidence in the nurses helps to provide the best support to the participants, to get them to monitor themselves, and to have attitudes that offer positive reinforcement for beneficial changes [30]. The behavior-changing programs organized by nurses in eight community health centers in England which aim to help the participants lose weight showed successful results [31]. The pre-conceptional counseling services can be structured and provided by midwives or nurses in reproductive health centers. As a conclusion, couples applying for assisted reproduction treatment should be educated and made aware of HPL, and the prenatal period is appropriate for developing HPL. Appropriate environments should be created to provide HPL-developing programs for individuals in reproductive health centers. Health staff should be informed about HPL through in-service and comprehensive education, and supported to create the opportunity to provide this service. The short-term and long-term effectiveness of the education practiced in this study should be evaluated. Conflict of interest The authors declared that there was no conflict of interest.
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Funding
265
None.
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Acknowledgment
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Thanks are given to Muzaffer Bilgin, Eskisehir Osmangazi University, Medical Faculty, Department of Bioistatistics, for analyzing the data statistically.
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References
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[6] Ramlau-Hansen CH, Thulstrup AM, Nohr EA, Bonde JP, Sorensen TI, Olsen J. Subfecundity in overweight and obese couples. Hum Reprod 2007;22: 1634–7. [7] Hassan M, Killick SR. Negative lifestyle is associated with a significant reduction in fecundity. Fertil Steril 2004;81:384–92. [8] Erel CT, Senturk LM. The impact of body mass index on assisted reproduction. Curr Opin Obstet Gynecol 2009;21(3):228–35. [9] Maheshwari A, Stofberg L, Bhattacharya S. Effect of overweightand obesity on assisted reproductive technology—a systematic review. Hum Reprod Update 2007;13:433–44. [10] Fedorcsak P, Dale PO, Storeng R, et al. Impact of overweight and underweight on assisted reproduction treatment. Hum Reprod 2004;19:2523–8. [11] Klonoff-Cohen H. Female and male lifestyle habits and IVF: what is known and unknown. Hum Reprod Update 2005;11:179–203. [12] Lledo B, Turienzo A, Ortiz JA, et al. Negative effect of P72 polymorphism on p53 gene in IVF outcome in patients with repeated implantation failure and pregnancy loss. J Assist Reprod Genet 2014;31:169–72. [13] WHO. Obesity. Preventing and managing the global epidemic. Geneva, Switzerland, Technical Report Series 200;894:1–253. Available at: http:// www.who.int/nutrition/publications/obesity/WHO_TRS_894/en/. [Accessed 14 July 2012]. [14] Lintsen AM, Pasker-de Jong PC, de Boer EJ, et al. Effects of subfertility cause, smoking and body weight on the success rate of IVF. Hum Reprod 2005;20:1867–75. [15] Guerrini I, Jackson S, Keaney F. Pregnancy and alcohol misuse. Br Med J 2009;338:845. [16] Gilmore IT. Excessive drinking in young women: not just a “lifestyle disease”. Br Med J 2008;336:952–3. [17] Morris SN, Missmer SA, Cramer DW, et al. Effects of lifetime exercise on the outcome of in vitro fertilization. Obstet Gynecol 2006;108:938–45. [18] Lovibond PF, Lovibond SH. The structure of negative emotionalstates: comparison of the Depression Anxiety Stress Scale (DASS) with the Beck Depression and Anxiety Inventories. Behav Res Ther 1995;33:335–43. [19] Walker SN, Sechrist KR, Pender NJ. The Health Promoting Lifestyle Profile development and psychometric characteristics. Nurs Res 1987;36:76–80. [20] Walker SN, Hill-Polerecky DM. Psychometric evaluation of the Health Promoting Lifestyle Profile II. Unpublished manuscript. University of Nebraska Medical Center; 1996. [21] Dondorp W, de Wert G, Pennings G, et al. Lifestyle-related factors and access to medically assisted reproduction. Hum Reprod 2010;25(3):578–83. [22] Csemiczky G, Landgren BM, Collins A. The influence of stress and state anxiety on the outcome of IVF-treatment: psychological and endocrinological assessment of Swedish women entering IVF-treatment. Acta Obstet Gynecol Scand 2000;79(2):113–8. [23] Domar A, Conboy L, Denardo-Roney J, Rooney K. Lifestyle behaviors in women undergoing in vitro fertilization: a prospective study. Fertil Steril 2012; 97:697–701. [24] Domar AD, Rooney KL, Milstein M, Conboy L. Lifestyle habits of 12,800 IVF patients: prevalence of negative lifestyle behaviors, and impact of region and insurance coverage. Hum Fertil (Camb Engl) 2015;18(4):253–7. [25] Ferreira RC, Halpern G, Figueira Rde C, et al. Physical activity, obesity and eating habits can influence assisted reproduction outcomes. Women’s Health (Lond Engl) 2010;6:517–24. [26] Schilling K, Toth B, Rösner S, Strowitzki T, Wischmann T. Prevalence of behaviour-related fertility disorders in a clinical sample: results of a pilot study. Arch Gynecol Obstet 2012;286(5):1307–14. [27] Homan G, Litt J, Norman RJ. The FAST study: fertility assessment and advice targeting lifestyle choices and behaviours: a pilot study. Hum Reprod 2012;27:2396–404. [28] Inskip HM, Crozier SR, Godfrey KM, Borland SE, Cooper C, Robinson SM. Women’s compliance with nutrition and lifestyle recommendations before pregnancy: general population cohort study. Br Med J 2009;338–481. [29] Rooney L, Domar D. The impact of lifestyle behaviors on infertility treatment outcome. Curr Opin Obstet Gynecol 2014;26:181–5. [30] McCabe S. What does it take to make a nurse? Considerations of the CNL and DNP role development. Perspect Psychiatr Care 2006;42:252–5. [31] Nanchahal K, Townsend J, Letley L, Haslam D, Wellings K, Haines A. Weightmanagement interventions in primary care: a pilot randomised controlled trial. Br J Gen Pract 2009;59:157–66.
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Contents lists available at ScienceDirect
European Journal of Obstetrics & Gynecology and Reproductive Biology journal homepage: www.elsevier.com/locate/ejogrb
The effect of health-promoting lifestyle education on the treatment of unexplained female infertility
1 2
3 Q1
Yeliz Kayaa,* , Nezihe Kizilkaya Bejib , Yunus Aydinc , Hikmet Hassac
4 5 6
a b c
Q2
Eskişehir Osmangazi University, Faculty of Health Sciences, Department of Nursing, Eskişehir, Turkey Biruni University, Faculty of Health Sciences, Department of Nursing, Istanbul, Turkey Eskişehir Osmangazi University, Faculty of Medicine, Department of Gynecology and Obstetrics, Reproductive Endocrinology and Infertility, Eskişehir, Turkey
A R T I C L E I N F O
A B S T R A C T
Article history: Received 14 May 2016 Received in revised form 23 July 2016 Accepted 24 October 2016 Available online xxx
Objective: This study aimed to reveal the 1) awareness, 2) improvements of a health-promoting lifestyle on women with unexplained infertility having at least one of the risk factors that have been indicated to negatively affect fertility (smoking, body mass index lower than 18.5 kg/m2 and more than 25 kg/m2, over-exercising or not exercising at all, alcohol consumption, caffeine consumption of more than 300 mg/day, and high levels of stress) by means of health-promoting lifestyle education, 3) the effect of this improvement on the result of assisted-reproduction treatment in terms of clinical pregnancy. Study design: 64 women diagnosed with unexplained infertility were divided into a group receiving Health-Promoting Lifestyle (HPL) education and a control group. 1) Risk Factors Questionnaire (BMI, Smoking, Alcohol, Stress, Exercise, Caffeine), 2) Depression, Anxiety and Stress Scale, 3) HealthPromoting Lifestyle Profile II. The health promoting lifestyle was given to the education group. The Risk Factors Questionnaire; Depression, Anxiety, Stress Scale and Healthcare-Promoting Lifestyle Profile II were also administered after the first-second-third month of education but before ART treatment. Results: A statistically significant decrease was found in the average levels of four variables as; BMI (p < 0.001)-stress (p < 0.001)-caffeine consumption (p < 0.001)-lower exercise levels (p < 0.001). Moreover, the total number of risk factors that females had between the first and third interview decreased significantly. Clinical pregnancy rate after ART was 12 (46.15%) and 5 (19.24%) in education and control group consequently (p = 0.02). Conclusion: Health-promoting lifestyle education was found to be effective in reducing the lifestyle risk factors for infertility and increasing the success rates of assisted reproduction treatment by correcting these risk factors. ã 2016 Elsevier Ireland Ltd. All rights reserved.
Keywords: Lifestyle Infertility Assisted reproduction
7 8 9 10 11 12 13 14 15
Introduction Patients should always try to manage the lifestyle factors that can contribute to infertility, and the effectiveness of infertility treatment, despite technical developments in the treatment of infertility. The most frequently observed risk factors for infertility are smoking, body mass index (BMI) lower than 18.5 kg/m2 and higher than 25 kg/m2, over-exercising or not exercising at all, alcohol consumption, caffeine consumption of more than 300 mg/ day, and stress. It seems that smoking negatively affects follicle
lık Bilimleri Fakültesi, * Corresponding author at: ESOGÜ Meşelik Yerleşkesi Sag 26480 Eskişehir, Turkey. Fax: +90 222 229 26 95. E-mail address: [email protected] (Y. Kaya).
development, ovulation and fertilization [1–5]. BMI > 25 kg/m2 and BMI < 20 kg/m2 were found to cause infertility in both females and males [6,7]. In addition, treatment of fertility was observed to be less successful in overweight and obese individuals [1,8–11]. Caffeine consumption of more than 300 mg/day is considered to be a risk factor in females in their reproductive years [1,5,11] and stress may affect the nervous and endocrine systems, and thereby Q3 fertility [5]. Additonally, information on reducing the negative effects of these factors on fertility by taking up a health-promoting lifestyle is gradually increasing [3,4,11]. Although evidence has been found of the positive effects of a health-promoting lifestyle on infertility, no randomised controlled studies were found in literature which analyzed the effect of these risk factors on the success of assistedreproduction treatment in cases of unexplained infertility [1,3,4].
http://dx.doi.org/10.1016/j.ejogrb.2016.10.050 0301-2115/ã 2016 Elsevier Ireland Ltd. All rights reserved.
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This study aimed to reveal the 1) awareness, 2) improvements of a health-promoting lifestyle on women with unexplained infertility having at least one of the risk factors that have been indicated to negatively affect fertility (smoking, body mass index lower than 18.5 kg/m2 and more than 25 kg/m2, over-exercising or not exercising at all, alcohol consumption, caffeine consumption of more than 300 mg/day, and high levels of stress) by means of health-promoting lifestyle education, 3) the effect of this improvement onthe result of assisted-reproduction treatment in terms of clinical pregnancy.
41
Materials and method
42
71
Following the Local Ethics Committee approval, the study was conducted between July 1st 2014 and June 31st 2015 in the Reproductive Health Center of Eskişehir Osmangazi University’s Faculty of Medicine. The Risk Factors Questionnaire and Depression, Anxiety and Stress Scale were completed by the women who were diagnosed with unexplained infertility and had at least two unsuccessful intra-uterine inseminations. Of 109 females; 13 could not be reached again, 17 did not agree to participate in the study, and 6 did not attend their scheduled interview despite agreeing to participate; therefore 73 females having at least one risk factor were included in the study. The file numbers of the females were divided into two groups, with file numbers ending with an odd number being assigned to the education group to ensure randomness. A power analysis was made to determine the number of participants for each groups. This analysis was based on the “ongoing pregnancy rate” in the study of Lledo et al., and the power analysis result obtained by comparing two independent rates in the Fischer-Exact Test showed that there should be at least 26 participants in both groups for a power of 80% to increase the pregnancy rate by more than 10% [12]. The education group and control group included 33 and 40 females respectively. 1) A Risk Factors Questionnaire 2) Depression, Anxiety and Stress Scale, 3) Health-Promoting Lifestyle Profile II were given to all study participants. The health promoting lifestyle education was given to the education group. The Risk Factors Questionnaire and Depression, Anxiety, Stress Scale were also administered after the first, second and third month of education and HealthPromoting Lifestyle Profile II was administered after the third month of education but before ART treatment.
72
Risk Factors Questionnaire
73
84
This questionnaire was prepared by the researchers in line with literature and included open and closed questions. The participants’ height and weight were measured and recorded to determine their BMIs. The BMI value was obtained by dividing the weight value (kilogram) by the height value (meters) [13]. A BMI of lower than 18.5 kg/m2 and more than 25 kg/ m2 was accepted as a risk factor [1,6–10,14]. The following factors were accepted as risk factors: Daily smoking or passive smoking [1–5], consumption of one glass of alcohol or more per week [15,16], caffeine consumption of more than 300 mg daily [1,5,11], Not exercising at all, or doing heavy exercise for more than four hours per week [17] and stress [5].
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The Depression, Anxiety and Stress Scale
43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70
74 75 76 77 78 79 80 81 82 83
86 87 88 89 90
The Depression, Anxiety and Stress Scale (DASS) developed by Lovibond and Lovibond in 1995 consists of 42 questions: 14 questions on depression, 14 questions on anxiety, and 14 questions on stress [18]. High scores on each of the depression, anxiety and stress subscales of this indicate that the individual has the said
problem. Scores of 14 and above on the subscale were accepted as a stress risk factor [5].
91
Health-Promoting Lifestyle Profile II
93
The Health-Promoting Lifestyle Profile (HPLP) was developed by Walker et al. and originally had 48 questions [19]. Four questions were added later by Walker and Hill-Polerecky. The 52 questions measure the health-promoting behaviors of individuals [20]. There are six subscales: self-actualization, health responsibility, exercise, nutrition, interpersonal support and stress management. Each subscale can be used independently. The total score of the subscales is the total score of the HPLP. The lowest and highest scores of the scale are 52 and 216, respectively. Higher scores indicate that the individual shows the said health behaviors at a high level. The education group was given Health-Promoting Lifestyle Education (HPLE) by the researcher (Y.K.) who is a specialist in infertility nursing and healthy lifestyle programmes. This education was prepared by the researchers in line with literature, and included information on the effects of the six behaviors most found to prevent pregnancy and successful IVF/ICSI and suggestions as to how to change these behaviors to a healthpromoting lifestyle, based on the 2010 Cochrane Database [3,4]. Verbal narration, written and visual education materials were used during this education process. Within the scope of this education, face-to-face interviews were conducted in a separate room in the reproductive health center for approximately 15– 20 min at a time. Afterwards, the content was gathered in a booklet and distributed to the participants to ensure continuity of the education. A telephone interview was conducted monthly over three months with each participant to provide support and to help them recognize the empowering results of positive health behaviors, to develop a positive point of view on the behaviors, and to improve self-monitoring. The barriers to these behaviors were discussed. At the end of each interview, objectives were determined to successfully continue the health-promoting behavior until the next interview. After the third monthly follow-up, three females in the education group and six females in the control group were excluded from the study because they could not be reached again by telephone. Additionally, as a result of the evaluation before embryo transfer, IVF/ICSI procedures, four females in the education group and eight females in the control group were canceled due to problems with the embryos. In conclusion, embryo transfer was made for 26 females in both groups. The b HcG values and fetal heartbeats of all females were analyzed on the 15th day and 4th week, respectively (Fig. 1).
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Statistical analysis
137
The continuous data were given as average standard deviation, and the categorical data were given as percentage (%). The Shapiro Wilk test was used to analyze the appropriateness of the data to normal distribution. The Kruskal–Wallis H test was used to compare three and more groups not appropriate to normal distribution. The Wilcoxon test was used to compare the values of two groups in different measurement times. Two-way repeated measures ANOVA (One Factor Repetition) was used for repeated measures. The direction and size of the correlation was determined using the Pearson correlation analysis for the variables showing a normal distribution and the Spearman correlation coefficient for the variables showing an abnormal distribution. The analysis of the cross tables were made using Pearson Chi-Square. The analyses were made using IBM SPSS Statistics 21.0. p < 0.05 was considered to be the threshold for statistical significance
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UNEXPLAINED INFERTILE FEMALES (n=109)
RISK FACTORS QUESTIONNAIRE; DEPRESSION, ANXIETY AND STRESS SCALE
THE FEMALES WITH AT LEAST 1 RISK FACTOR (n=73)
SOCIODEMOGRAPHIC CHARACTERISTICS QUESTIONNAIRE HEALTH-PROMOTING LIFESTYLE PROFILE II
EDUCATION GROUP (n=33)
CONTROL GROUP (n=40)
EDUCATED NOT EDUCATED
FOLLOW-UP IVF/ICSI PRACTICE (n=34)
(Determinaon of the changes in the risk factors through phone interviews each month for 3 months)
β HcG evaluaon aer 15 days (n=26)
Fetal heartbeat (FH) evaluaon aer 4 weeks IVF/ICSI PRACTICE (n=30)
SUCCESS EVALUATION AFTER IVF/ICSI β HcG evaluaon aer 15 days (n=26)
Fetal heartbeat (FH) evaluaon aer 4 weeks
SUCCESS EVALUATION AFTER IVF/ICSI Fig. 1. Study flow chart. 153 154 155 156 157 158 159 160 161
Results No statistical difference was found between the sociodemographic characteristics of the two groups according to age, infertility period, education level, rate of working women and source of infertility information (Table 1). The characteristics of all participants related to the factors that affect fertility are shown in Table 2 and no statistically significant difference was found between the two groups in terms of the total number of risk factors and of each risk factor.
The education group was re-evaluated in the first, second and third months after the first interview in terms of risk factors. Despite the decrease in the risk factors of BMI and smoking by the third month, this difference was not statistically significant. However, a statistically significant decrease was found in the average levels of four variables; average BMI-stresscaffeine consumption and lower exercise levels (all p < 0.001). Moreover, the total number of risk factors that females had in the first and third interview decreased significantly (p < 0.001) (Table 3).
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Table 1 Comparison of the sociodemographic characteristics of the participants.
Age of women Age of man Period of infertility Education of women
Rate of working women Treatments for infertility
a b c
Q4
Ave. Sd Ave. Sd Ave. Sd None Elementary High school Associate degree University Intra-uterine insemination IVF/ICSI
Education group
Control group
Total
p
30 31.2 34.9 4.5 5.9 3.4 2 (6.7%) 15 (50%) 9 (30%) 3 (10%) 1 (3.3%) 7 (23.3%) 2.4 0.7 1.3 0.5
34 31.0 33.5 3.5 5.7 3.0 0 (0%) 17 (50%) 11 (32.4%) 5 (14.7%) 1 (2.9%) 5 (14.7%) 1.9 0.7 1.6 0.5
31.1 4.2 34.0 4.1 5.8 3.2 2 (3.1%) 32 (50%) 20 (31.3%) 8 (12.5%) 2 (3.1%) 12 (18.7%) 2.1 0.8 1.5 0.5
0.8a 0.08a 0.9b 0.7c
0.6c 0.09b 0.7b
Student T test. Mann–Whitney U test. Chi square test.
Table 2 Comparison of the risk factors of the participants.
BMI
Ave. Sd Risk factor (n)
Education group
Control group
Total
p
no yes
25.7 5.3 15 (50%) 15 (50%)
25.3 4.7 15 (44.1%) 19 (55.9%)
25.5 4.9 30 (46.9%) 34 (53.1%)
0.9a 0.8b
Smoking
Risk factor (n)
no yes
19 (63.3%) 11 (36.7%)
17 (50%) 17 (50%)
36 (43.7%) 28 (56.3%)
0.4b
Alcohol
Risk factor (n)
no yes
30 (100%) 0 (0%)
33 (97.1%) 1 (2.9%)
63 (98.4%) 1 (1.6%)
1.000b
Stress (DASS score)
Risk factor (n)
no yes
11 (36.7%) 19 (63.3%)
11 (32.3%) 23 (67.7%)
22 (32.4%) 42 (67.6%)
0.9b
Exercise
Risk factor (n)
no yes
4 (13.3%) 26 (86.7%)
6 (17.6%) 28 (82.4%)
10 (84.4%) 54 (15.6%)
0.7b
Caffeine (daily consumption (mg))
Risk factor (n)
no yes
11 (36.7%) 19 (63.3%)
15 (38.2%) 19 (55.9%)
24 (37.5%) 40 (62.5%)
1.000b
The number of existing risk factors
Ave. Sd
2.8 1.0
3.2 1.0
3.0 1.0
0.052a
a b
Mann–Whitney U test. Chi square test.
Table 3 Changes in the risk factors determined in the education group (n = 30) between the first interview and monthly follow-ups after education.
Risk factor that affect fertility
First month
Second month
Third month
Ave. Sd
Ave. Sd
Ave. Sd
Ave. Sd
25.3 4.6 n (%) 18 (60.0%) 12 (40.0%)
24.9 4.9 n (%) 19 (63.3%) 11 (36.6%)
24.8 4.8 n (%) 20 (66.6%) 10 (33.3%)
<0.001b
Risk factor
No Yes
25.7 5.3 n (%) 15 (50.0%) 15 (50.0%)
Smoking
Risk factor
No Yes
18 (60.0%) 12 (40.0%)
23 (76.7%) 7 (23.3%)
24 (80.0%) 6 (20.0%)
25 (83.3%) 5 (16.6%)
0.2c
Alcohol
Risk factor
No Yes
30 (100%) 0 (0%)
30 (100%) 0 (0%)
30 (100%) 0 (0%)
30 (100%) 0 (0%)
–
Stress (DASS score)
Risk factor
No Yes
11 (36.7%) 19 (63.3%)
13 (43.3%) 17 (56.6%)
27 (90.0%) 3 (10.0%)
27 (90.0%) 3 (10.0%)
<0.001c
Exercise
Risk factor (n)
No Yes
1 (3.33%) 29 (96.7%)
21 (70.0%) 9 (30.0%)
25 (83.3%) 5 (16.6%)
25 (83.3%) 5 (16.6%)
<0.001c
Caffeine (daily consumption (mg))
Risk factor
No Yes
11 (36.7%) 19 (63.3%)
23 (76.6%) 7 (23.3%)
25 (83.3%) 5 (16.6%)
28 (93.4%) 2 (6.6%)
<0.001c
The number of existing risk factors
Ave. Sd
2.8 1.0
1.3 1.0
0.8 0.8
0.6 0.8
<0.001d
BMI
a b c d
Ave. Sd
Pa
First interview
0.5c
Comparison of the findings of the first interview and the interview three months later. Two-way variance analysis test. Chi square test. Kruskal Wallis H test.
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Q5
Table 4 Comparison of the HPLP scores of all participants. HPLP subscales Health responsibility Exercise Nutrition Self-actualization Interpersonal support Stress management Total a b
Education Ave. Sd 19.2 4.1 12.4 4.4 21.1 5.8 24.1 4.7 24.3 4.7 17.1 4.5 118.0 22.5
Control
Total
18.4 3.0 13.7 5.4 22.7 2.7 24.1 2.8 23.5 2.9 15.2 2.8 118.0 16.5
18.7 3.6 13.1 5.0 22.0 4.5 24.1 3.8 23.9 3.9 16.1 3.8 118.0 19.4
p a
0.4 0.4b 0.1a 0.8b 0.9b 0.06a 0.9a
Student T test. Mann–Whitney U test.
Table 5 Comparison of the HPLP scores of the education group before and after education. HPLP subscales
Before education Ave. Sd
After education Ave. Sd
Pa
Health responsibility Exercise Nutrition Self-actualization Interpersonal support Stress management Total
19.2 4.1 12.4 4.4 21.1 5.8 24.1 4.7 24.3 4.7 17.1 4.5 118.0 22.5
20.9 3.3 19.4 3.2 23.3 4.5 25.0 3.8 24.8 4.0 18.7 3.2 132.5 18.2
<0.001 <0.001 <0.001 0.011 0.1 0.002 <0.001
a
172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190
Wilcoxon Signed Rank Test.
No statistically significant difference was found between the scores of the education and control groups on the HPLP and its subscales (Table 4). The HPLP was re-applied to the participants in the education group after the three-month follow-ups, and a statistically significant increase was seen in all subscale scores and the total score of the scale, except for the “interpersonal support” subscale (p < 0.05) (Table 5). Oocytes were collected from 30 of the infertile females in the education group and 34 of the infertile females in the control group. Due to problems with the embryos, transfers were made in 26 females in both groups. No statistically significant difference at baseline was found between the total number of oocytes, MII oocyte number, fertilization rate and the number of transferred embryos. The b HcG value of the embryo-transferred females was analyzed on the 15th day and all was found to be positive. Then, their fetal heartbeats were evaluated in the 4th week. Fetal heartbeat was found in 12 (46.15%) females in the education group and 5 (19.24%) females in the control group, which is a statistically significant difference (p = 0.02) (Table 6).
5
Comment
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In the present study we found that with a 3-month HPLE; the awareness of women of the risk factors for infertility and HPLP total score increased. While the total number of risk factors that females had in the first and third interview decreased significantly; especially the decrease of average BMI, caffeine consumption, stress levels and increase in exercise level were remarkable. Moreover, the clinical pregnancy rate after ART was significantly higher in women who had the 3-month HPLE compared to the control group. In terms of natural conception; obesity, smoking, and alcohol significantly affect fertility. There is also sufficient evidence that these lifestyle variables also have a negative influence on IVF outcome. ESHRE recommended that health-care providers should inform their patients about the importance of these problems and provide support in order to achieve the intended results for the target lifestyle changes [21]. It was shown that psychological stress is another variable that may also affect the outcome of IVF treatment [22]. Although the effect of an unhealthy lifestyle on infertility is clearly known and information is obtained from various sources, couples may still continue to demonstrate non-health-promoting behaviors [23–26]. Having the knowledge of the negative effect of these lifestyle variables seems insufficient; the major aims of health-care providers should be to increase the awareness of women about the risks of lifestyle variables on infertility and to support their patients in achieving the intended results. Homan et al. and Hammice et al. showed that health-promoting lifestyle education may increase the healthy lifestyle in infertile couples and in copules planning pregnancy [2,27]. According to our results; the awareness of women about risk factors and also changing in lifestyle habits in a healthier direction with HPLE increased in unexplained infertile women before ART. Infertility centers may become important practice centers to develop a health-promoting lifestyle for a community starved of information and ready to accept education [28]. However, there is a limited number of studies on changing the unhealthy lifestyles of women who are trying to become pregnant into health-promoting lifestyles and the effects of this change on the results of assisted reproduction [29]. In this present study, all risk factors improved in the education group and the clinical pregnancy rate was found to be 46.15% in the education group and 19.24% in the control group and in the fourth week, which is a statistically significant difference. The decrease in the risk factors, the significant increase in the HPL score, and the statistically high clinical pregnancy rate
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Table 6 Findings on the results of IVF/ICSI treatment of infertile females. Education group
Control group
Total
P
Number of collected oocytes
Ave. Sd
9.7 8.2 9.3 7.7
11.3 5.7 10.1 5.9
10.5 7.0 9.7 6.8
0.6a 0.2b
Number of MIII oocytes
Ave. Sd
6.3 5.9 6.1 5.1
6.0 3.0 5.6 3.1
6.1 4.6 5.8 4.4
1.000a 0.9b
Fertilization rate
Ave. Sd
81.0 22.5 69.8 35.2
84.2 19.8 64.4 40.1
82.6 21.0 66.9 37.7
0.5a 0.8b
Number of transferred embryos
Ave. Sd
1.3 0.4 1.1 0.6
1.1 0.3 0.8 0.5
1.2 0.4 0.9 0.6
0.09a 0.06b
12/26c (46.1%) 12/30d (40%)
5/26c (19.2%) 5/34d (14.8%)
17/52c (32.6%) 17/64d (26.5%)
0.02c,d
Clinical pregnancy n (%)
a b c d
Mann–Whitney U test. Intend to treat analysis (Mann–Whitnney U test). Chi square test. Intend to treat analysis (Chi square test).
Please cite this article in press as: Y. Kaya, et al., The effect of health-promoting lifestyle education on the treatment of unexplained female infertility, Eur J Obstet Gynecol (2016), http://dx.doi.org/10.1016/j.ejogrb.2016.10.050
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suggest that the education and monitoring of women with unexplained infertilility in developing a health-promoting lifestyle prior to assisted reproduction had positive effects on the treatment. However, we cannot be sure about the longterm probable positive effects of education and the decrease in pregnancy complications and longterm health. Termination of follow up with pregnancy is one of the most important limitations of our study but new trials with this aim will resolve this issue. Nurses could have a very important role in behavior-changing programs. Confidence in the nurses helps to provide the best support to the participants, to get them to monitor themselves, and to have attitudes that offer positive reinforcement for beneficial changes [30]. The behavior-changing programs organized by nurses in eight community health centers in England which aim to help the participants lose weight showed successful results [31]. The pre-conceptional counseling services can be structured and provided by midwives or nurses in reproductive health centers. As a conclusion, couples applying for assisted reproduction treatment should be educated and made aware of HPL, and the prenatal period is appropriate for developing HPL. Appropriate environments should be created to provide HPL-developing programs for individuals in reproductive health centers. Health staff should be informed about HPL through in-service and comprehensive education, and supported to create the opportunity to provide this service. The short-term and long-term effectiveness of the education practiced in this study should be evaluated. Conflict of interest The authors declared that there was no conflict of interest.
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Funding
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None.
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Acknowledgment
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Thanks are given to Muzaffer Bilgin, Eskisehir Osmangazi University, Medical Faculty, Department of Bioistatistics, for analyzing the data statistically.
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References
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