BRIEF REPORT
Lifestyle modification intervention among infertile overweight and obese women with polycystic ovary syndrome Diane Mahoney, FNP-BC, WHNP-BC, DNP (Infertility Coordinator) School of Nursing, University of Missouri-Kansas City, Olathe, Kansas
Keywords Polycystic ovary syndrome; infertile women; dietary intake; lifestyle; obesity; physical activity. Correspondence Diane Mahoney, FNP-BC, WHNP-BC, DNP, Infertility Coordinator, Reproductive Resource Center, 12200 West 106th Street, Suite 120, Overland Park, Kansas 66215. Tel: (913)894-2323, Fax: (913)894-0841; E-mail: [email protected] Received: June 2012; accepted: August 2012 doi: 10.1002/2327-6924.12073
Abstract Purpose: To implement an evidence-based lifestyle modification intervention, guided by motivational interviewing, among a sample of infertile overweight and obese women with polycystic ovary syndrome to increase chances of conception while improving overall health. Data sources: A prospective quantitative design was utilized (n = 12). Infertile overweight and obese women with polycystic ovary syndrome at an infertility practice completed questionnaires to assess diet and exercise practices at study onset and completion. Body mass index and weight measurements were obtained on participants at study onset and completion of intervention. Menstrual history was assessed by interview. Conclusions: There was a mean weight loss (p = .005) of 7(±5) pounds although a 5% weight reduction did not occur. Mean daily calorie (p = .005), fat (p = .006), and carbohydrate intake (p = .014) were significantly reduced. Frequency in brisk walking exercise significantly increased (p = .024). Frequency in home or gym exercise increased (p = .050). Menstrual cyclicity improved by 50% among prior amenorrheic subjects. Implications for practice: An evidence-based lifestyle modification guideline could prove to be a cost effective intervention for infertile women with polycystic ovary syndrome (PCOS) who desire pregnancy. This intervention could be integrated into the primary care and reproductive medicine visits as sole therapy or in conjunction with infertility treatment.
Introduction Infertility is a growing healthcare problem for women. Infertility is defined as an inability to conceive after a year of trying for women 35 years or younger and after 6 months for women over the age of 35 (American Society of Reproductive Medicine, 2003). A large proportion of infertile women have polycystic ovary syndrome (PCOS). It is the most common endocrine disorder affecting approximately 5%–10% of reproductive aged women (Palomba et al., 2008). In fact, there is no significant difference in the prevalence of PCOS between White and Black females in the United States (Azziz et al., 2004). Thus, infertility issues associated with PCOS have generated broad concern. There has been an association between obesity, hyperandrogenism, and insulin resistance as causative factors of menstrual dysfunction, anovulation, and infertil-
ity in women diagnosed with PCOS (March, Steinbeck, Atkinson, Petocz, & Brand-Miller, 2010; Norman et al., 2004). In addition to reproductive problems, women with PCOS are at increased risk for the development of type II diabetes mellitus, hypertension, dsylipidemia, and cardiovascular disease (Douglas et al., 2006; Humphreys & Costarelli, 2008; Moran, Brinkworth, Noakes, & Norman, 2006). Although not all women with PCOS have weight issues, it has been estimated that 40%–60% of women with PCOS are overweight or obese (Moran, Pasquali, Teede, Hoeger, & Norman, 2009). This population of women is commonly seen by infertility and primary care providers (PCPs) for an array of health services. However, evidence reveals minimal support from healthcare professionals in advising them on lifestyle modification that could improve chances of conception and overall health status (Humphreys & Costarellil, 2008).
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Experts agree that diet and exercise management should be implemented with overweight and obese women with PCOS following the initial assessment of infertility (Moran, et al., 2009; Thessaloniki European Society of Human Reproduction and Embryology and the American Society for Reproductive Medicine PCOS Consensus Workshop Group, 2007). With the estimated cost of treating PCOS-related menstrual dysfunction to be $1.35 billion, infertility care to be $533 million, and diabetes to be $1.77 billion annually in the United States alone, an evidence-based lifestyle modification guideline could prove to be a cost effective intervention for treating these clients (Azziz, Marin, Hoq, Badamgarav, & Song, 2005). Therefore, the author hypothesized that an evidencebased lifestyle modification intervention among a group of infertile overweight and obese women with PCOS could accomplish (a) a 5% weight reduction (b) an improvement in diet and physical activity practices, and (c) an improvement in menstrual cyclicity during a 12-week pilot study.
Literature review Lifestyle modification is defined as a structured diet and/or exercise intervention (Moran, Hutchison, Norman, & Teede, 2011). Lifestyle modification interventions have been efficacious in reducing the risk for diabetes, cardiovascular disease, and cancer among the general population (Aldana et al., 2005). Dietary patterns can influence fertility within the general population of healthy women (Chavarro, Rich-Edwards, Rosner, & Willett, 2009, 2007). The Foresight (1995) study affirmed the important role of lifestyle modification in optimizing chances of pregnancy and improving pregnancy outcomes for women with and without a prior history of infertility. Because women with PCOS have an increased risk for the development of infertility, diabetes, hypertension, and cardiovascular disease, the effects of lifestyle modification on reducing such risks have warranted further investigation (Moran et al., 2006). The first and only meta-analysis on lifestyle changes in women with PCOS reported evidence of improved body composition, insulin resistance, and hyperandrogenism (Moran et al., 2011). However, none of the studies in the meta-analysis assessed fertility as the primary outcome. In addition, there was no data to analyze menstrual regularity or ovulation (Moran et al., 2011). Randomized controlled studies have been carried out to compare the effects of lifestyle modification and/or metformin treatment on ovulation and androgen concentrations in overweight women with PCOS. There is evidence that ovulation rates do not differ significantly between groups when a mod302
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est weight loss was present (Hoeger et al., 2004). Weight reduction could be the most pivotal factor for restoring reproductive function. Menstrual regularity, ovulatory patterns, and pregnancy rates have improved in women with PCOS after a modest 5% weight reduction (Crosignani et al., 2003). Lifestyle modification targeted at slower weight loss has been shown more effective for improving insulin sensitivity that restores ovulation in infertile obese women with PCOS (Huber-Buchholz, Carey, & Norman, 1999). On the other hand, rapid weight reduction over as little as 4 weeks has also improved PCOS presentation in obese women with PCOS (Moran et al., 2006). Researchers have compared the impact of a specific diet and/or exercise program when implementing a lifestyle modification intervention. Thomson et al. (2008) found exercise to have no superior effect on reproductive functioning and cardiometabolic risk compared to a hypocaloric diet in obese women with PCOS. On the contrary, others have reported that structured exercise training yields higher occurrences of menstrual regularities and cumulative pregnancy rates over lower caloric diets (Palomba et al., 2008). There is evidence that combined nutritional and exercise counseling yields the greatest benefit to obese women with PCOS (Bruner, Chad, & Chizen, 2006). Women with PCOS have been found to consume greater dietary consumption of foods with a higher glycemic index (GI) compared to women who do not have PCOS (Douglas et al., 2006). With the complexities of insulin resistance and hyperinsulinemia characterized by PCOS, a greater intake of high GI foods could generate additional insult. In fact, women with PCOS who consume the lower GI diet have demonstrated improvements in menstrual cyclicity over women on the healthy diet (March et al., 2010). Further, women with PCOS tend to have a higher body mass index (BMI) and consume greater amounts of saturated fats (Colombo et al., 2009). Thus, advisement on dietary and exercise modification could be crucial for improving cardiovascular health in women with PCOS.
Motivational interviewing In this study, motivational interviewing (MI) was used to activate and empower each study participant’s own motivations, values, and resources at counseling sessions. MI originated from the counseling discipline to assist clients in overcoming alcohol and drug dependencies (Rollnick, Miller, & Butler, 2008). Today, usage of MI interventions has expanded to obese populations for weight loss achievement particularly in diabetic women (West, DiLillo, Bursac, Gore, & Greene, 2007). Through MI, the
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Table 1 Examples of change talk Desire Ability Reasons Need Commitment Taking steps
“I wish to exercise more to be healthy” “I could eat healthier to lose weight and get pregnant” “I need to change my lifestyle to lose weight and get pregnant” “I have to eat better to be healthy” “I will change my lifestyle to lose weight and get pregnant” “Last week I exercised 4 days for 30 minutes”
Note. Adapted from Rollnick et al. (2008, p. 37).
healthcare provider subtly reinforces positive change talk and addresses challenging barriers to change. Change talk consists of statements that signal a client’s likelihood of making a behavioral change (see Table 1). There are six different themes of change talk, which are based on desire, ability, reason, need, commitment, and steps taken to change behaviors (Rollnick et al., 2008).
Method Design A prospective quantitative design was used to address the research hypothesis. Institutional Review Board approval was obtained.
Participants Clients from an infertility practice, located in the suburb of a large Midwestern city in the United States, were recruited through a convenience sampling process. Eligibility for study inclusion were (a) a diagnosis of PCOS as defined by Rotterdam ESHRE/ARSM-sponsored PCOS consensus workshop group (2004) criteria, (b) a desire to conceive, (c) a BMI greater than 27, (d) age range of 18–44, (e) female gender, and (f) the ability to read and write. Infertility practice healthcare providers informed possible participants that a study was being conducted and provided contact information with the investigator. Women who were interested in participation met with the investigator.
Instruments A digital scale was used for measuring weight, and BMI was calculated by the individual’s body weight in kilograms divided by the square of her height in meters. The Block Brief Food Frequency Questionnaire (FFQ) was the predictor for dietary intake. The Block Brief FFQ estimated intake of a wide variety of nutrients and food groups over the past 3 months. Individual portion size
was assessed for each food with pictures provided to enhance accuracy of quantification. Individual average daily caloric intake was quantified. The Block Brief FFQ was developed by assessing three 4-day dietary records among a group of middle-age females and two 7-day dietary records among a group of older males. Nutrient count correlations between full and brief version of the questionnaire ranged from 0.60 to 0.80 (Block, Hartman, & Naughton, 1990). Permission was obtained to use this questionnaire. The Block Adult Physical Activity (PA) Screener was the predictor for physical activity. This tool assessed frequency and duration of job-related, daily life, and leisure activities. It was developed using data from a large United States representative sample of men and women. Observed and predicted percent body fat correlated at r = .73 for men and r = .82 for women (Block et al., 2009). Permission was obtained to use this questionnaire. Menstrual history (presence of amenorrhea, regular menses, or irregular menses) was assessed by interview and recorded on a menstrual log. Amenorrhea was defined as the absence of menstrual bleeding for greater than 3 months. Regular menses was defined as having menstrual bleeding every 21–35 days apart for greater than 3 months. Irregular menses was defined as having menstrual bleeding more than 35 days apart for greater than 3 months. Age, race, marital status, employment status, years of infertility, and presence of metformin or/and ovulation induction (OI) therapy was assessed by interview and recorded on an intake form.
Procedures Informed consent was obtained from recruited subjects during an office visit. Baseline height, weight, and BMI were gathered and each participant completed a dietary questionnaire (Block Brief FFQ) and exercise questionnaire (Block Adult PA Screener). In addition, participants were interviewed regarding age, race, weight, marital status, employment status, years of infertility, menstrual history, and presence of metformin or/and OI therapy. Study participants were scheduled for individualized counseling sessions with the PI. Participants were advised on (a) calorie reduction, (b) food categories, (c) portion and serving sizes, (d) United States Department of Agriculture (USDA) ChooseMyPlate (2011) guide to healthy eating, (e) incorporating foods with a lower GI, (f) minimizing saturated fats, (g) shopping tips and menu planning, and (h) food preparations. The women were also counseled on alcohol reduction and smoking cessation if applicable (see Figure 1). Based on Moran et al. (2006) recommendations, participants were advised to engage in low impact physical 303
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Recruited (n = 54)
Declined (n = 20) No response (n = 10)
Enrollment
Assessed for eligibility (n = 24)
Diet and exercise counseling
Withdrew before study (n = 3) Pregnant (n = 2) Moved out of town (n = 3) Other (n = 3)
Consented to participate (n = 12)
Completed lifestyle modification intervention (n = 9)
Dropouts Lost to follow-up (n = 2) Personal issues (n = 1)
End of study
Figure 1 Study flow diagram.
activity for a minimum of 3–5 days/week for at least 30– 60 min. The investigator encouraged participants to first establish a regular exercise habit before advancing frequency. Low impact physical activities were advised such as brisk walking, cycling, and aerobics. Resistance training was encouraged two to three times per week utilizing a variety of exercises to work the major muscle groups. The investigator advised participants to engage in daily activities, such as walking longer distances, using stairs instead of the elevator, parking further distances away, and walking during lunchtime hours. Study participants were provided dietary and exercise logs to complete and return at every counseling visit. Participants were scheduled for counseling sessions every 2 weeks for a total of six sessions. Weights were obtained at each session. Counseling topics included (a) ways of cooking with vegetables, (b) lower fat recipes, (c) 304
healthy snacks, (d) budget shopping, (e) dining out, and (f) preparing for holiday eating. Twelve weeks later, at study completion, a final weight and BMI was obtained. The Block Brief FFQ and the Block PA Screener were readministered to participants. Participants were reinterviewed regarding menstrual history.
Data analysis Statistical analysis was performed with Statistics Package for Social Sciences Base 19.0 software (SPSS, 2010). The paired samples t-test was used to compare weight, BMI, nutritional intake, and physical activity before and after lifestyle modification intervention. Descriptive statistics were used to analyze sample characteristics of age, race, weight, marital status, employment status,
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Table 2 Sample characteristics (N = 12) Characteristic
n
%
Mean
SD
Range
Age 32 years 5.33 24–42 years Weight 256 pounds 37.28 202–326 pounds BMI 44 kg/m2 5.75 34–53 kg/m2 Race Caucasian 8 66.6 African American 2 16.6 Hispanic or Latino 2 16.6 Marital status Married 11 91.6 Single 1 8.3 Employment status Employed 11 91.6 Unemployed 1 8.3 Years of infertility Less than 2 years 2 16.6 Greater than 2 years 10 83.3 Menstrual historya No cyclesb 4 Irregular cyclesc 4 Regular cyclesd 4 On metformin Yes 7 58.3 No 5 41.6 On OI therapy Yes 3 25.0 No 9 75.0 Note. OI, ovulation induction; BMI, body mass index; a , occurrence of menstrual cycles without medical intervention; b , amenorrhea; c , menstrual bleeding greater than 35 days apart; d , menstrual bleeding ranging 21– 35 days apart.
years of infertility, menstrual history, and presence of metformin or/and OI therapy.
Results Participant characteristics Twelve women voluntarily consented to participate in the lifestyle intervention study. All 12 were included in sample characteristic data analysis. Three became lost to follow-up prior to study completion. Nine were included in the weight, BMI, physical activity, and menstrual history data analysis. Seven were included in the dietary data analysis. Two were unable to complete poststudy dietary questionnaire. Demographic information and additional characteristics are presented in Table 2.
Weight and BMI Preintervention, the mean weight in pounds was 256(±37) and mean BMI was 44(±6) kg/m2 . There was a significant (p = .013) mean weight reduction
of 7(±5) pounds postlifestyle modification intervention, which represented an overall mean loss of 2.6%. The mean BMI index reduced to 43 kg/m2 , which represented a 1.7% reduction.
Diet modification Energy intakes were calculated from data provided by participant responses on the FFQs. The mean daily caloric intake decreased from 2430 (±1151) kcal preintervention to 1078 (±453) kcal postintervention. This represents a significant (p = .005) reduction of 1352 kcal. Total daily fat intake reduced significantly (p = 0.006) to 44(±22) grams postintervention compared from 96(±39) grams preintervention. Daily carbohydrate intake significantly (p = .014) reduced from 210 (±69) grams to 135(±67) grams. There was also a significant reduction in protein (p = .017) intake. Cholesterol intake decreased significantly (p = .014) from 259 mg (±105) to 133 (±67) mg/day. Saturated fat consumption decreased significantly (p = .004) from 32 (±12) g to 12(±7) g daily. There were also significant reductions in daily bread servings (p = .001), meat servings (p = .033), and fatty food servings (p = .026). Yet, there were no significant changes in the number of daily vegetables, fruit, or dairy food servings (see Table 3).
Physical activity modification Physical activity was calculated based on data collected from the PA screener responses. Prior to lifestyle modification, participants reported a mean participation in brisk walking activity to be “a few times a month.” After undergoing the lifestyle modification intervention, the mean participation in brisk walking increased significantly (p = .024) to “three to four times per week.” There was no significant (p = .139) change in duration of brisk walking activity. There was also a significant (p = .050) mean increase in frequency of exercising at a gym or at home from “rarely” to “a few times per month” participation after the lifestyle intervention. There was no significant (p = 0.139) change in the duration time.
Menstrual cyclicity Amenorrhea was defined as having no cycles. Fifty percent (n = 2) of the four amenorrheic participants reported having two spontaneous menstrual cycles. An additional 50% (n = 2) reported at least one episode of feeling bloated and having menstrual cramps although menstrual bleeding did not result. There were no reported improvements in menstrual regularity among subjects with a prior history of irregular cycles. 305
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Table 3 Pre- and postlifestyle intervention comparisons Variable Weight (pounds) Preintervention Postintervention BMI (kg/m2 ) Preintervention Postintervention Energy intake (kcal/day) Preintervention Postintervention Fat (g/d) Preintervention Postintervention Saturated fat (g/d) Preintervention Postintervention Carbohydrates (g/d) Preintervention Postintervention Protein (g/d) Preintervention Postintervention Fat (%) Preintervention Postintervention Carbohydrate (%) Preintervention Postintervention Protein (%) Preintervention Postintervention
n
Mean
SD
t
df
p
9 9
261.1 254.4
41.2 37.0
3.49
6
.13
9 9
44.0 43.3
5.6 4.7
1.88
6
NS
7 7
2429.9 1077.7
1150.8 453.2
4.30
6
.005
7 7
95.6 43.7
39.2 21.9
4.13
6
.006
7 7
31.7 14.0
12.0 6.8
4.63
6
.004
7 7
210.8 121.6
68.5 54.7
3.40
6
.014
7 7
74.8 43.3
26.7 9.7
3.28
6
.017
7 7
42.4 36.7
4.9 7.9
3.70
6
.052
7 7
42.3 47.2
5.9 7.2
− 1.44
6
NS
7 7
15.1 17.5
3.2 2.7
− 1.65
6
NS
Note. BMI, body mass index; kcal/day, kilocalories per day; g/d, grams per day; NS, not significant.
Discussion The results of this study revealed significant achievement of weight loss and lifestyle improvement among participants although a 5% weight reduction did not occur. If the sample size had been larger, a 5% weight loss may well have been attained. This study demonstrates the importance of providing dietary and exercise advisement for improving reproductive and overall health outcomes. These findings are consistent with the literature. Metabolic outcomes were not assessed in the present study. Nonetheless, achieving a 5% weight loss and improvement in lifestyle practices was believed to positively impact such outcomes. Weight loss through dietary and/or exercise modifications have been proven beneficial in significantly improving body composition, reproductive function, and anthropometric measurements (Crosignani et al., 2003). The literature has identified a trend toward a 5% weight loss being effective for improving PCOS presen306
tation (Crosignani et al., 2003; Thomson et al., 2008). Improvements in insulin resistance have been identified after as little as a 1% BMI reduction (Bruner et al., 2006). Large changes in weight loss may not be necessary to restore reproductive functioning (Norman et al., 2004). Perhaps any modest weight reduction could provide some reproductive and metabolic benefit to these women. During the current study, participants demonstrated a significant increase in frequency of physical activity. Participants also reported intent to further increase frequency and duration of activities. The addition of exercise has been shown to improve reproductive function and body composition in anovulatory woman with PCOS (Thomson et al., 2008). Menstrual regulation and insulin sensitivity have improved in women with PCOS after a 3-month course of structured exercise (Vigorito et al., 2007). Therefore, in the present study, it is likely that greater physical activity participation could have yielded increased weight loss and greater menstrual regularity improvement. In fact, women with PCOS that engage in regular exercise have been found to experience higher ovulation rates (Palomba et al., 2008). Participant motivation and compliance to the lifestyle intervention remained a concern throughout the current study. As a result, MI strategies were integrated into the counseling sessions to enhance participant motivation in the present study. It was believed the MI process would activate participants to engage in selfactualization behaviors to improve health. Nonetheless, participants reported reencountering struggles with compliance to diet and exercise regimen irrespective of knowing the associated general and reproductive health benefits. Participants identified awareness of making better eating choices although a behavioral change may not have automatically resulted. However, as the PI gained greater trust with subjects, MI sessions generated “change talk” occurrences supporting the significant drop in caloric intake that occurred by study termination. Although the present findings revealed significant improvements in weight and lifestyle practices, there are study limitations to consider. Anthropometric measures (waist or hip circumference) were not used to evaluate central adiposity in participants. The pilot study was small, nonrandomized, and uncontrolled, limiting the ability to generalize from it. For study replication, larger randomized controlled trials would be beneficial in further examining the role of lifestyle changes in women with PCOS. In addition, long-term follow-up studies are essential to evaluate pregnancy outcomes resulting from lifestyle modification.
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Conclusions and implications Overweight and obese women with PCOS demonstrate menstrual irregularities, chronic anovulation, and insulin resistance causing infertility issues. This pilot study has provided evidence that support from healthcare providers significantly impacts client success with diet and exercise improvement. This intervention would be feasible in the primary care or infertility specialty setting. Healthcare providers could integrate diet and exercise counseling during a medical visit. Additional counseling visits could be added as needed. This will require collaboration between nurses, PCPs, gynecologists, reproductive endocrinologists, and dieticians in determining the best strategy to maximize outreach to the greatest volume of women affected by PCOS. Such an intervention could prove cost effective for both those who cannot afford infertility treatment and those currently receiving treatment. Most importantly, it could give infertile women with PCOS the gift they so earnestly wait for and alleviate further suffering far too many women endure.
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Crosignani, R. G., Colombo, M., Vegetti, W., Somigliana, E., Gessati, A., & Ragni, G. (2003). Overweight and obese anovulatory patients with polycystic ovaries: Parallel improvements in anthropometric indices, ovarian physiology and fertility rate by diet. Human Reproduction, 18(9), 1928–1932. Douglas, C. C., Norris, L. E., Oster, R. A., Darnell, B. E., Azziz, R., & Gower, B. A., (2006). Difference in dietary intake between women with polycystic ovary syndrome and healthy controls. Fertility and Sterility, 86(2), 411–417. Foresight (1995). The Foresight program: Improving reproduction and infant health through preconception care. Journal of the Australian College of Nutritional and Environmental Medicine, 14(2), 16. Hoeger, K. M., Kochman, L., Wixom, N., Craig, K., Miller, R. K., & Guzick, D. S. (2004). A randomized, 48-week, placebo-controlled trial of intensive lifestyle modification and/or metformin therapy in overweight women with polycystic ovary syndrome: A pilot study. Fertility and Sterility, 82(2), 421–429. Huber-Buchholz, M. M., Carey, D. G., & Norman, R. J. (1999). Restoration of reproductive potential by lifestyle modification in obese polycystic ovary syndrome: Role of insulin sensitivity and luteinizing hormone. Journal of Clinical Endocrinology and Metabolism, 84(4), 1470–1474. Humphreys, L., & Costarelli, V. (2008). Implementation of dietary and general lifestyle advice among woman with polycystic ovarian syndrome. Journal of the Royal Society for the Promotion of Health, 128(4), 190–195. March, K. A., Steinbeck, K. S., Atkinson, F. S., Petocz, P., & Brand-Miller, J. C. (2010). Effect of a low glycemic index compared with a conventional healthy diet on polycystic ovary syndrome. American Journal of Clinical Nutrition, 92, 83–92. Moran, L., Brinkworth, G., Noakes, M., & Norman, R. J. (2006). Symposium: Diet, nutrition and exercise in reproduction; effects of lifestyle modification in polycystic ovarian syndrome. Reproductive BioMedicine Online, 12(5), 569–578. Moran, L. J., Hutchinson, S. K., Norman, R. J., & Teede, H. J. (2011). Lifestyle changes in women with polycystic ovary syndrome. The Cochrane Library (2), 1–57. Moran, L. J., Pasquali, R., Teede, H. J., Hoeger, K. M., & Norman, R. J. (2009). Treatment of obesity in polycystic ovary syndrome: A position statement of the androgen excess and polycystic ovary syndrome society, Fertility and Sterility, 92(6), 1966–1982. Norman, R. J., Noakes, M., Wu, R., Davies, M. J., Moran, L., & Wang, J. X. (2004). Improving reproductive performance in overweight/obese women with effective weight management. European Society of Human Reproduction and Embryology, 10(3), 267–280. Palomba, S., Giallauria, F., Falbo, A., Russo, T., Oppedisano, R., Tolino, A., . . . Orio, F. (2008). Structured exercise training program versus hypocaloric hyperproteic diet in obese polycystic ovary syndrome patients with anovulatory infertility: A 24-wk pilot study. Human Reproduction, 23(3), 642–650. Rollnick, S., Miller, W.R., & Butler, C. (2008). Motivational Interviewing in health care: Helping patients change behavior. New York: Guilford Press. Rotterdam ESHRE/ARSM-sponsored PCOS consensus workshop group (2004). Revised 2003 consensus on diagnostic criteria and long-term health risks related to polycystic ovary syndrome. Fertility and Sterility, 81(1), 19–25. SPSS. (2010). SPSS brief guide (version 16.0) [computer software]. Chicago, IL: SPSS Inc. Thessaloniki European Society of Human Reproduction and Embryology and the American Society for Reproductive Medicine PCOS Consensus Workshop Group. (2007). Consensus on infertility treatment related to polycystic ovary syndrome. Human Reproduction, 23(3), 462–477. Thomson, R. L., Buckley, J. D., Noakes, M., Clifton, P. M., Norman, R. J., & Brinkworth. (2008). The effect of a hypocaloric diet with and without exercise training on body composition, cardiometabolic risk profile, and reproductive function in overweight and obese women with polycystic
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Lifestyle modification intervention among infertile overweight and obese women with polycystic ovary syndrome Diane Mahoney, FNP-BC, WHNP-BC, DNP (Infertility Coordinator) School of Nursing, University of Missouri-Kansas City, Olathe, Kansas
Keywords Polycystic ovary syndrome; infertile women; dietary intake; lifestyle; obesity; physical activity. Correspondence Diane Mahoney, FNP-BC, WHNP-BC, DNP, Infertility Coordinator, Reproductive Resource Center, 12200 West 106th Street, Suite 120, Overland Park, Kansas 66215. Tel: (913)894-2323, Fax: (913)894-0841; E-mail: [email protected] Received: June 2012; accepted: August 2012 doi: 10.1002/2327-6924.12073
Abstract Purpose: To implement an evidence-based lifestyle modification intervention, guided by motivational interviewing, among a sample of infertile overweight and obese women with polycystic ovary syndrome to increase chances of conception while improving overall health. Data sources: A prospective quantitative design was utilized (n = 12). Infertile overweight and obese women with polycystic ovary syndrome at an infertility practice completed questionnaires to assess diet and exercise practices at study onset and completion. Body mass index and weight measurements were obtained on participants at study onset and completion of intervention. Menstrual history was assessed by interview. Conclusions: There was a mean weight loss (p = .005) of 7(±5) pounds although a 5% weight reduction did not occur. Mean daily calorie (p = .005), fat (p = .006), and carbohydrate intake (p = .014) were significantly reduced. Frequency in brisk walking exercise significantly increased (p = .024). Frequency in home or gym exercise increased (p = .050). Menstrual cyclicity improved by 50% among prior amenorrheic subjects. Implications for practice: An evidence-based lifestyle modification guideline could prove to be a cost effective intervention for infertile women with polycystic ovary syndrome (PCOS) who desire pregnancy. This intervention could be integrated into the primary care and reproductive medicine visits as sole therapy or in conjunction with infertility treatment.
Introduction Infertility is a growing healthcare problem for women. Infertility is defined as an inability to conceive after a year of trying for women 35 years or younger and after 6 months for women over the age of 35 (American Society of Reproductive Medicine, 2003). A large proportion of infertile women have polycystic ovary syndrome (PCOS). It is the most common endocrine disorder affecting approximately 5%–10% of reproductive aged women (Palomba et al., 2008). In fact, there is no significant difference in the prevalence of PCOS between White and Black females in the United States (Azziz et al., 2004). Thus, infertility issues associated with PCOS have generated broad concern. There has been an association between obesity, hyperandrogenism, and insulin resistance as causative factors of menstrual dysfunction, anovulation, and infertil-
ity in women diagnosed with PCOS (March, Steinbeck, Atkinson, Petocz, & Brand-Miller, 2010; Norman et al., 2004). In addition to reproductive problems, women with PCOS are at increased risk for the development of type II diabetes mellitus, hypertension, dsylipidemia, and cardiovascular disease (Douglas et al., 2006; Humphreys & Costarelli, 2008; Moran, Brinkworth, Noakes, & Norman, 2006). Although not all women with PCOS have weight issues, it has been estimated that 40%–60% of women with PCOS are overweight or obese (Moran, Pasquali, Teede, Hoeger, & Norman, 2009). This population of women is commonly seen by infertility and primary care providers (PCPs) for an array of health services. However, evidence reveals minimal support from healthcare professionals in advising them on lifestyle modification that could improve chances of conception and overall health status (Humphreys & Costarellil, 2008).
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Experts agree that diet and exercise management should be implemented with overweight and obese women with PCOS following the initial assessment of infertility (Moran, et al., 2009; Thessaloniki European Society of Human Reproduction and Embryology and the American Society for Reproductive Medicine PCOS Consensus Workshop Group, 2007). With the estimated cost of treating PCOS-related menstrual dysfunction to be $1.35 billion, infertility care to be $533 million, and diabetes to be $1.77 billion annually in the United States alone, an evidence-based lifestyle modification guideline could prove to be a cost effective intervention for treating these clients (Azziz, Marin, Hoq, Badamgarav, & Song, 2005). Therefore, the author hypothesized that an evidencebased lifestyle modification intervention among a group of infertile overweight and obese women with PCOS could accomplish (a) a 5% weight reduction (b) an improvement in diet and physical activity practices, and (c) an improvement in menstrual cyclicity during a 12-week pilot study.
Literature review Lifestyle modification is defined as a structured diet and/or exercise intervention (Moran, Hutchison, Norman, & Teede, 2011). Lifestyle modification interventions have been efficacious in reducing the risk for diabetes, cardiovascular disease, and cancer among the general population (Aldana et al., 2005). Dietary patterns can influence fertility within the general population of healthy women (Chavarro, Rich-Edwards, Rosner, & Willett, 2009, 2007). The Foresight (1995) study affirmed the important role of lifestyle modification in optimizing chances of pregnancy and improving pregnancy outcomes for women with and without a prior history of infertility. Because women with PCOS have an increased risk for the development of infertility, diabetes, hypertension, and cardiovascular disease, the effects of lifestyle modification on reducing such risks have warranted further investigation (Moran et al., 2006). The first and only meta-analysis on lifestyle changes in women with PCOS reported evidence of improved body composition, insulin resistance, and hyperandrogenism (Moran et al., 2011). However, none of the studies in the meta-analysis assessed fertility as the primary outcome. In addition, there was no data to analyze menstrual regularity or ovulation (Moran et al., 2011). Randomized controlled studies have been carried out to compare the effects of lifestyle modification and/or metformin treatment on ovulation and androgen concentrations in overweight women with PCOS. There is evidence that ovulation rates do not differ significantly between groups when a mod302
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est weight loss was present (Hoeger et al., 2004). Weight reduction could be the most pivotal factor for restoring reproductive function. Menstrual regularity, ovulatory patterns, and pregnancy rates have improved in women with PCOS after a modest 5% weight reduction (Crosignani et al., 2003). Lifestyle modification targeted at slower weight loss has been shown more effective for improving insulin sensitivity that restores ovulation in infertile obese women with PCOS (Huber-Buchholz, Carey, & Norman, 1999). On the other hand, rapid weight reduction over as little as 4 weeks has also improved PCOS presentation in obese women with PCOS (Moran et al., 2006). Researchers have compared the impact of a specific diet and/or exercise program when implementing a lifestyle modification intervention. Thomson et al. (2008) found exercise to have no superior effect on reproductive functioning and cardiometabolic risk compared to a hypocaloric diet in obese women with PCOS. On the contrary, others have reported that structured exercise training yields higher occurrences of menstrual regularities and cumulative pregnancy rates over lower caloric diets (Palomba et al., 2008). There is evidence that combined nutritional and exercise counseling yields the greatest benefit to obese women with PCOS (Bruner, Chad, & Chizen, 2006). Women with PCOS have been found to consume greater dietary consumption of foods with a higher glycemic index (GI) compared to women who do not have PCOS (Douglas et al., 2006). With the complexities of insulin resistance and hyperinsulinemia characterized by PCOS, a greater intake of high GI foods could generate additional insult. In fact, women with PCOS who consume the lower GI diet have demonstrated improvements in menstrual cyclicity over women on the healthy diet (March et al., 2010). Further, women with PCOS tend to have a higher body mass index (BMI) and consume greater amounts of saturated fats (Colombo et al., 2009). Thus, advisement on dietary and exercise modification could be crucial for improving cardiovascular health in women with PCOS.
Motivational interviewing In this study, motivational interviewing (MI) was used to activate and empower each study participant’s own motivations, values, and resources at counseling sessions. MI originated from the counseling discipline to assist clients in overcoming alcohol and drug dependencies (Rollnick, Miller, & Butler, 2008). Today, usage of MI interventions has expanded to obese populations for weight loss achievement particularly in diabetic women (West, DiLillo, Bursac, Gore, & Greene, 2007). Through MI, the
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Table 1 Examples of change talk Desire Ability Reasons Need Commitment Taking steps
“I wish to exercise more to be healthy” “I could eat healthier to lose weight and get pregnant” “I need to change my lifestyle to lose weight and get pregnant” “I have to eat better to be healthy” “I will change my lifestyle to lose weight and get pregnant” “Last week I exercised 4 days for 30 minutes”
Note. Adapted from Rollnick et al. (2008, p. 37).
healthcare provider subtly reinforces positive change talk and addresses challenging barriers to change. Change talk consists of statements that signal a client’s likelihood of making a behavioral change (see Table 1). There are six different themes of change talk, which are based on desire, ability, reason, need, commitment, and steps taken to change behaviors (Rollnick et al., 2008).
Method Design A prospective quantitative design was used to address the research hypothesis. Institutional Review Board approval was obtained.
Participants Clients from an infertility practice, located in the suburb of a large Midwestern city in the United States, were recruited through a convenience sampling process. Eligibility for study inclusion were (a) a diagnosis of PCOS as defined by Rotterdam ESHRE/ARSM-sponsored PCOS consensus workshop group (2004) criteria, (b) a desire to conceive, (c) a BMI greater than 27, (d) age range of 18–44, (e) female gender, and (f) the ability to read and write. Infertility practice healthcare providers informed possible participants that a study was being conducted and provided contact information with the investigator. Women who were interested in participation met with the investigator.
Instruments A digital scale was used for measuring weight, and BMI was calculated by the individual’s body weight in kilograms divided by the square of her height in meters. The Block Brief Food Frequency Questionnaire (FFQ) was the predictor for dietary intake. The Block Brief FFQ estimated intake of a wide variety of nutrients and food groups over the past 3 months. Individual portion size
was assessed for each food with pictures provided to enhance accuracy of quantification. Individual average daily caloric intake was quantified. The Block Brief FFQ was developed by assessing three 4-day dietary records among a group of middle-age females and two 7-day dietary records among a group of older males. Nutrient count correlations between full and brief version of the questionnaire ranged from 0.60 to 0.80 (Block, Hartman, & Naughton, 1990). Permission was obtained to use this questionnaire. The Block Adult Physical Activity (PA) Screener was the predictor for physical activity. This tool assessed frequency and duration of job-related, daily life, and leisure activities. It was developed using data from a large United States representative sample of men and women. Observed and predicted percent body fat correlated at r = .73 for men and r = .82 for women (Block et al., 2009). Permission was obtained to use this questionnaire. Menstrual history (presence of amenorrhea, regular menses, or irregular menses) was assessed by interview and recorded on a menstrual log. Amenorrhea was defined as the absence of menstrual bleeding for greater than 3 months. Regular menses was defined as having menstrual bleeding every 21–35 days apart for greater than 3 months. Irregular menses was defined as having menstrual bleeding more than 35 days apart for greater than 3 months. Age, race, marital status, employment status, years of infertility, and presence of metformin or/and ovulation induction (OI) therapy was assessed by interview and recorded on an intake form.
Procedures Informed consent was obtained from recruited subjects during an office visit. Baseline height, weight, and BMI were gathered and each participant completed a dietary questionnaire (Block Brief FFQ) and exercise questionnaire (Block Adult PA Screener). In addition, participants were interviewed regarding age, race, weight, marital status, employment status, years of infertility, menstrual history, and presence of metformin or/and OI therapy. Study participants were scheduled for individualized counseling sessions with the PI. Participants were advised on (a) calorie reduction, (b) food categories, (c) portion and serving sizes, (d) United States Department of Agriculture (USDA) ChooseMyPlate (2011) guide to healthy eating, (e) incorporating foods with a lower GI, (f) minimizing saturated fats, (g) shopping tips and menu planning, and (h) food preparations. The women were also counseled on alcohol reduction and smoking cessation if applicable (see Figure 1). Based on Moran et al. (2006) recommendations, participants were advised to engage in low impact physical 303
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Recruited (n = 54)
Declined (n = 20) No response (n = 10)
Enrollment
Assessed for eligibility (n = 24)
Diet and exercise counseling
Withdrew before study (n = 3) Pregnant (n = 2) Moved out of town (n = 3) Other (n = 3)
Consented to participate (n = 12)
Completed lifestyle modification intervention (n = 9)
Dropouts Lost to follow-up (n = 2) Personal issues (n = 1)
End of study
Figure 1 Study flow diagram.
activity for a minimum of 3–5 days/week for at least 30– 60 min. The investigator encouraged participants to first establish a regular exercise habit before advancing frequency. Low impact physical activities were advised such as brisk walking, cycling, and aerobics. Resistance training was encouraged two to three times per week utilizing a variety of exercises to work the major muscle groups. The investigator advised participants to engage in daily activities, such as walking longer distances, using stairs instead of the elevator, parking further distances away, and walking during lunchtime hours. Study participants were provided dietary and exercise logs to complete and return at every counseling visit. Participants were scheduled for counseling sessions every 2 weeks for a total of six sessions. Weights were obtained at each session. Counseling topics included (a) ways of cooking with vegetables, (b) lower fat recipes, (c) 304
healthy snacks, (d) budget shopping, (e) dining out, and (f) preparing for holiday eating. Twelve weeks later, at study completion, a final weight and BMI was obtained. The Block Brief FFQ and the Block PA Screener were readministered to participants. Participants were reinterviewed regarding menstrual history.
Data analysis Statistical analysis was performed with Statistics Package for Social Sciences Base 19.0 software (SPSS, 2010). The paired samples t-test was used to compare weight, BMI, nutritional intake, and physical activity before and after lifestyle modification intervention. Descriptive statistics were used to analyze sample characteristics of age, race, weight, marital status, employment status,
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Table 2 Sample characteristics (N = 12) Characteristic
n
%
Mean
SD
Range
Age 32 years 5.33 24–42 years Weight 256 pounds 37.28 202–326 pounds BMI 44 kg/m2 5.75 34–53 kg/m2 Race Caucasian 8 66.6 African American 2 16.6 Hispanic or Latino 2 16.6 Marital status Married 11 91.6 Single 1 8.3 Employment status Employed 11 91.6 Unemployed 1 8.3 Years of infertility Less than 2 years 2 16.6 Greater than 2 years 10 83.3 Menstrual historya No cyclesb 4 Irregular cyclesc 4 Regular cyclesd 4 On metformin Yes 7 58.3 No 5 41.6 On OI therapy Yes 3 25.0 No 9 75.0 Note. OI, ovulation induction; BMI, body mass index; a , occurrence of menstrual cycles without medical intervention; b , amenorrhea; c , menstrual bleeding greater than 35 days apart; d , menstrual bleeding ranging 21– 35 days apart.
years of infertility, menstrual history, and presence of metformin or/and OI therapy.
Results Participant characteristics Twelve women voluntarily consented to participate in the lifestyle intervention study. All 12 were included in sample characteristic data analysis. Three became lost to follow-up prior to study completion. Nine were included in the weight, BMI, physical activity, and menstrual history data analysis. Seven were included in the dietary data analysis. Two were unable to complete poststudy dietary questionnaire. Demographic information and additional characteristics are presented in Table 2.
Weight and BMI Preintervention, the mean weight in pounds was 256(±37) and mean BMI was 44(±6) kg/m2 . There was a significant (p = .013) mean weight reduction
of 7(±5) pounds postlifestyle modification intervention, which represented an overall mean loss of 2.6%. The mean BMI index reduced to 43 kg/m2 , which represented a 1.7% reduction.
Diet modification Energy intakes were calculated from data provided by participant responses on the FFQs. The mean daily caloric intake decreased from 2430 (±1151) kcal preintervention to 1078 (±453) kcal postintervention. This represents a significant (p = .005) reduction of 1352 kcal. Total daily fat intake reduced significantly (p = 0.006) to 44(±22) grams postintervention compared from 96(±39) grams preintervention. Daily carbohydrate intake significantly (p = .014) reduced from 210 (±69) grams to 135(±67) grams. There was also a significant reduction in protein (p = .017) intake. Cholesterol intake decreased significantly (p = .014) from 259 mg (±105) to 133 (±67) mg/day. Saturated fat consumption decreased significantly (p = .004) from 32 (±12) g to 12(±7) g daily. There were also significant reductions in daily bread servings (p = .001), meat servings (p = .033), and fatty food servings (p = .026). Yet, there were no significant changes in the number of daily vegetables, fruit, or dairy food servings (see Table 3).
Physical activity modification Physical activity was calculated based on data collected from the PA screener responses. Prior to lifestyle modification, participants reported a mean participation in brisk walking activity to be “a few times a month.” After undergoing the lifestyle modification intervention, the mean participation in brisk walking increased significantly (p = .024) to “three to four times per week.” There was no significant (p = .139) change in duration of brisk walking activity. There was also a significant (p = .050) mean increase in frequency of exercising at a gym or at home from “rarely” to “a few times per month” participation after the lifestyle intervention. There was no significant (p = 0.139) change in the duration time.
Menstrual cyclicity Amenorrhea was defined as having no cycles. Fifty percent (n = 2) of the four amenorrheic participants reported having two spontaneous menstrual cycles. An additional 50% (n = 2) reported at least one episode of feeling bloated and having menstrual cramps although menstrual bleeding did not result. There were no reported improvements in menstrual regularity among subjects with a prior history of irregular cycles. 305
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Table 3 Pre- and postlifestyle intervention comparisons Variable Weight (pounds) Preintervention Postintervention BMI (kg/m2 ) Preintervention Postintervention Energy intake (kcal/day) Preintervention Postintervention Fat (g/d) Preintervention Postintervention Saturated fat (g/d) Preintervention Postintervention Carbohydrates (g/d) Preintervention Postintervention Protein (g/d) Preintervention Postintervention Fat (%) Preintervention Postintervention Carbohydrate (%) Preintervention Postintervention Protein (%) Preintervention Postintervention
n
Mean
SD
t
df
p
9 9
261.1 254.4
41.2 37.0
3.49
6
.13
9 9
44.0 43.3
5.6 4.7
1.88
6
NS
7 7
2429.9 1077.7
1150.8 453.2
4.30
6
.005
7 7
95.6 43.7
39.2 21.9
4.13
6
.006
7 7
31.7 14.0
12.0 6.8
4.63
6
.004
7 7
210.8 121.6
68.5 54.7
3.40
6
.014
7 7
74.8 43.3
26.7 9.7
3.28
6
.017
7 7
42.4 36.7
4.9 7.9
3.70
6
.052
7 7
42.3 47.2
5.9 7.2
− 1.44
6
NS
7 7
15.1 17.5
3.2 2.7
− 1.65
6
NS
Note. BMI, body mass index; kcal/day, kilocalories per day; g/d, grams per day; NS, not significant.
Discussion The results of this study revealed significant achievement of weight loss and lifestyle improvement among participants although a 5% weight reduction did not occur. If the sample size had been larger, a 5% weight loss may well have been attained. This study demonstrates the importance of providing dietary and exercise advisement for improving reproductive and overall health outcomes. These findings are consistent with the literature. Metabolic outcomes were not assessed in the present study. Nonetheless, achieving a 5% weight loss and improvement in lifestyle practices was believed to positively impact such outcomes. Weight loss through dietary and/or exercise modifications have been proven beneficial in significantly improving body composition, reproductive function, and anthropometric measurements (Crosignani et al., 2003). The literature has identified a trend toward a 5% weight loss being effective for improving PCOS presen306
tation (Crosignani et al., 2003; Thomson et al., 2008). Improvements in insulin resistance have been identified after as little as a 1% BMI reduction (Bruner et al., 2006). Large changes in weight loss may not be necessary to restore reproductive functioning (Norman et al., 2004). Perhaps any modest weight reduction could provide some reproductive and metabolic benefit to these women. During the current study, participants demonstrated a significant increase in frequency of physical activity. Participants also reported intent to further increase frequency and duration of activities. The addition of exercise has been shown to improve reproductive function and body composition in anovulatory woman with PCOS (Thomson et al., 2008). Menstrual regulation and insulin sensitivity have improved in women with PCOS after a 3-month course of structured exercise (Vigorito et al., 2007). Therefore, in the present study, it is likely that greater physical activity participation could have yielded increased weight loss and greater menstrual regularity improvement. In fact, women with PCOS that engage in regular exercise have been found to experience higher ovulation rates (Palomba et al., 2008). Participant motivation and compliance to the lifestyle intervention remained a concern throughout the current study. As a result, MI strategies were integrated into the counseling sessions to enhance participant motivation in the present study. It was believed the MI process would activate participants to engage in selfactualization behaviors to improve health. Nonetheless, participants reported reencountering struggles with compliance to diet and exercise regimen irrespective of knowing the associated general and reproductive health benefits. Participants identified awareness of making better eating choices although a behavioral change may not have automatically resulted. However, as the PI gained greater trust with subjects, MI sessions generated “change talk” occurrences supporting the significant drop in caloric intake that occurred by study termination. Although the present findings revealed significant improvements in weight and lifestyle practices, there are study limitations to consider. Anthropometric measures (waist or hip circumference) were not used to evaluate central adiposity in participants. The pilot study was small, nonrandomized, and uncontrolled, limiting the ability to generalize from it. For study replication, larger randomized controlled trials would be beneficial in further examining the role of lifestyle changes in women with PCOS. In addition, long-term follow-up studies are essential to evaluate pregnancy outcomes resulting from lifestyle modification.
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Conclusions and implications Overweight and obese women with PCOS demonstrate menstrual irregularities, chronic anovulation, and insulin resistance causing infertility issues. This pilot study has provided evidence that support from healthcare providers significantly impacts client success with diet and exercise improvement. This intervention would be feasible in the primary care or infertility specialty setting. Healthcare providers could integrate diet and exercise counseling during a medical visit. Additional counseling visits could be added as needed. This will require collaboration between nurses, PCPs, gynecologists, reproductive endocrinologists, and dieticians in determining the best strategy to maximize outreach to the greatest volume of women affected by PCOS. Such an intervention could prove cost effective for both those who cannot afford infertility treatment and those currently receiving treatment. Most importantly, it could give infertile women with PCOS the gift they so earnestly wait for and alleviate further suffering far too many women endure.
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