Menstrual Chart Patterns and Its Associated Clinical Profile, Fertility Changes and Outcomes Among Women with Hormonalrelated Infertility at Bugando Medical Centre, Mwanza, Tanzania.
- Mwanza, Tanzania | Catholic University of Health and Allied Sciences [CUHAS-Bugando] | 2024.
- 94 Pages Includes References
Abstract:
Background: Infertility is a global problem and one in six people have experienced infertility at some stage in their lives. In Tanzania, the prevalence of infertility is 16%. The menstrual cycle is a highly regulated physiological process that makes conception and pregnancy possible. Menstrual cycle patterns are indicators of fecundity. Ovulatory dysfunctions that result from dysfunction of the hypothalamic-pituitary-ovarian axis, peripheral endocrine/non-endocrine glands, and other metabolic disorders may result in both menstrual irregularities and ovulatory infertility. Globally about 25% of women with infertility have infrequent or absent ovulation. Fertility awareness is a valuable tool that enables women to recognize their health status. Many times the answers to infertility lie hidden within these patterns. There is 96% sensitivity of the cervical mucus symptoms in identifying the entire fertility window. Charting the menstrual patterns is a simple, noninvasive, inexpensive tool each woman should embrace. This study aimed to determine the menstrual chart patterns and its associated clinical profile among women with hormonal-related infertility at Bugando Medical Centre.
Methods: A prospective longitudinal study that involved 230 women with hormonal infertility aged 18 to 44 years, was carried out at Bugando Medical Centre from March 2023 to March 2024 with the aims of identifying the menstrual chart patterns, its associated clinical profile in women with hormonal related infertility and changes in cycle patterns and fertility outcomes. Women with hormonal infertility were explained about the purpose of the study. Those who voluntarily agreed to consent and met the eligibility criteria were enrolled in the study. A standardized, pretested data collection tool was used to collect the participant's information including; social demographic factors, menstrual cycle patterns, clinical and hormonal profiles. Mothers were taught how to chart their menstrual cycle biomarkers: menstrual bleeding, cervical mucus, and dryness every day for three months consecutively after downloading the fertility education and medical management application. Data from questionnaires were entered into a computer using Microsoft excel and then exported to STATA version 15 for summarization and analysis. Continuous data were summarized using mean with standard deviation or median with interquartile range depending on their normality in distribution. Categorically data were summarized using frequencies, proportion and percentages. We used Pearson’s Chi-Squared test or Fisher’s Exact test to determine the significant differences of the distribution of menstrual patterns and clinical profile. For numerical data, mean, and median with interquartile range was used. A p-value less than 0.05 was regarded to be statistically significant.
Results: The mean age of the participants was 32.2 ± 5.7 years. About, 56.9% (131/230) were aged between 26 and 35. Half of the participants were nulliparous 50.4% (116/230). The years of infertility ranged from 1 to 20 with a median age of 4 [IQR 2 – 7] years. Of the 230 participants, 56.5% participants had a normal cycle length, 16.5% had shorter cycles and 27% had long cycles. The cycle length was 20 – 90 days, with a median of 30 [IQR: 27 – 37] days. About 70.6% (161/230) of participants had anovulatory cycles. Moreover after managing these patients for two to three months, (56%) 14/25 women aged less than 25 years had higher conception rate compared to those aged 26-35 (p-value 0.001). Patients who had normal HbA1c had a higher conception rate than those with abnormal HbA1c, 34.8 % (41/118) versus 22.3 % (25/112), (p-value 0.0370). Those without signs of thyroid dysfunctions (31.1%) 61/196 conceived more compared to those with signs of thyroid dysfunction (14.7%) 5/34 (p-value 0.035). At the end of three months of follow up, most of the participants 93.9%, had normal bleeding patterns and 85.2% had stretchy, slippery clear cervical mucus. Among those who ovulated 28.7% conceived within three months.
Conclusion: Many times the answers to infertility are hidden within the patterns of a woman’s reproductive cycle. Menstrual patterns, basic hormonal profiles together with clinical characteristics are better ways to diagnose infertility. Weight reduction with a hypo-caloric diet is an important intervention in managing infertility. Treating the root cause of a woman’s hormonal imbalance is often a remarkably effective approach. Hence we recommend that menstrual cycle charting patterns and lifestyle changes to be incorporated as tools in managing women with infertility
Wurzburg Road 35, Premises, Post Code: 33102 | P. O. Box 1464 Mwanza, Tanzania | Phone: (255) 28-298-3384 | Fax: (255) 28-298-3386 | Email: vc@bugando.ac.tz | Website: www.bugando.ac.tz