Time to Resumption of Menses, Spatial Distribution, and Predictors Among  Post-partum Period Women in Ethiopia, Evidence From Ethiopian Demographic and  Health Survey 2016 Data: Gompertz Inverse Gaussian Shared Frailty Model

Belay DG, Asratie MH

doi:10.3389/frph.2022.862693

Frontiers in Reproductive Health, 4, 862693, 2022

Time to Resumption of Menses, Spatial Distribution, and Predictors Among Post-partum Period Women in Ethiopia, Evidence From Ethiopian Demographic and Health Survey 2016 Data: Gompertz Inverse Gaussian Shared Frailty Model

Daniel Gashaneh Belay , Melaku Hunie Asratie

Author affiliations

University of Gondar ROR

DOI10.3389/frph.2022.862693 PMID36303667

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Abstract

Background

The timing of the resumption of post-partum menses is important for a woman who intends to avoid subsequent unintended pregnancy, and it has key implications on maternal, neonatal, and child health outcomes. Despite this, information is scant about the time to resumption of post-partum menses and predictors in Ethiopia. Therefore, this study aimed to determine the time it takes to start menses and spatial distribution among post-partum period women in Ethiopia and identify its predictors.

Methods

A secondary data analysis was conducted based on 2016 Ethiopian Demographic and Health Survey (EDHS). A total weighted sample of 6,489 post-partum women was included in the analysis. STATA 14 was used to weigh, clean, and analyze the data. The shared frailty model was applied since the EDHS data have a hierarchical nature. For checking the proportional hazard assumption, the Schenefold residual test, Log-Log plot, Kaplan-Meier, and predicted survival plot were applied. Akakie Information Criteria (AIC), Cox-Snell residual test, and deviance were used for checking model adequacy and for model comparison. Based on these, the Gompertz inverse Gaussian shared frailty model was the best-fitted model for this data. Variables with a p < 0.2 were considered for the multivariable Gompertz inverse Gaussian shared frailty model. Finally, the adjusted hazard ratio (AHR) with a 95% confidence interval (CI), and a p < 0.05 was reported to identify the significant predictors of time to the resumption of post-partum menses.

Results

The median survival time to post-partum menses resumption was 14.6 months. In this study, 51.90% [95% CI: 50.03, 53.76] of post-partum period women had resumed, and the risk of menses resumption was 1.17 times [AHR: 1.17; 95% CI: 1.03-1.33] higher among urban resident, 1.14 times [AHR: 1.14; 95% CI: 1.0-1.24] in women who had attended formal education, and 1.63 times [AHR: 1.63; 95% CI: 1.4-1.7] higher among women who used hormonal contraceptives. However, the risk of post-partum menses resumption was lower among 7-24 months breastfeeding women by 36% [AHR: 0.64; 95% CI: 0.5-0.76], women with child alive by 26% [AHR: 0.74; 95% CI: 0.6-0.85], and multiparous women by 27% [AHR: 0.73; 95% CI: 0.6-0.80].

Conclusion

Almost half of the participants had resumed post-partum menses, with the median survival timing of menses resumption at 14.5 months. Women residing in urban areas, who attended formal education, and using hormonal contraceptives have a shorter time to resume post-partum menses, whereas a woman with an alive child, breastfeeding practice, and multiple parity has a longer time to resume post-partum menses. Therefore, the healthcare providers and program managers should act on the resumption of post-partum menses through health education and promotion to cultivate the 14 months lag period identified by considering the significant factors.

Topics

postpartum/return-of-fertility/breastfeeding-and-ovulation menstrual-cycle/cycle-across-the-lifespan/cycle-and-general-health

postpartum menses resumption, return to fertility postpartum, breastfeeding menstruation return, postpartum amenorrhea duration, lactational amenorrhea Ethiopia, demographic health survey postpartum, menstrual resumption predictors, postpartum contraception timing, Gompertz frailty model, postpartum fertility return predictors

PMID 36303667 36303667 DOI 10.3389/frph.2022.862693 10.3389/frph.2022.862693 Belay et al. 2022, Belay 2022

Cite this article

Belay, D. G., & Asratie, M. H. (2022). Time to Resumption of Menses, Spatial Distribution, and Predictors Among Post-partum Period Women in Ethiopia, Evidence From Ethiopian Demographic and Health Survey 2016 Data: Gompertz Inverse Gaussian Shared Frailty Model. Frontiers in reproductive health, 4, 862693. https://doi.org/10.3389/frph.2022.862693

postpartum/return-of-fertility/breastfeeding-and-ovulation menstrual-cycle/cycle-across-the-lifespan/cycle-and-general-healthreproductive-endocrinology/luteal-phase/luteal-phase-deficiency

Late infertile days in early postpartum cycles

Hatherley LI, 1985 Clin Reprod Fertil

Luteal phase abnormalities in early menstrual cycles after pregnancy have been shown to cause confusion in the practice of natural family planning (NFP) for some patients and to restrict severely the number of late infertile days available to others. The cause of the abnormalities is uncertain but appears to be related to the nursing status of the patient.

menstrual-cycle/cycle-across-the-lifespan/cycle-and-general-health reproductive-endocrinology/ovarian-hormones/estrogendiagnostics/hormone-testing/urinary-metabolites Open Access

Modeling fertile window differences across the reproductive lifespan with quantitative urine hormone monitoring of the menstrual cycle

Bouchard TP et al., 2026 Journal of ovarian research

Reproductive hormones of the fertile window are often referenced to women in regular cycles, but this may not be representative of the hormonal profiles of women in different circumstances like polycystic ovarian syndrome, the postpartum period, and the perimenopause transition. This observational cohort study sought to identify the variability in the reproductive hormones in various clinical circumstances and to establish potential thresholds for each category based on hormone measurements with the Mira urinary hormone monitor. A total of 57 women (ages 22-51) in various circumstances (regular cycles, polycystic ovarian syndrome, postpartum and perimenopause) tracked Mira urine hormone measurements (estrone-3-glucuronide, luteinizing hormone, pregnanediol glucuronide), contributing 444 cycles of data. Using additive mixed models, hormone values were stratified by the four different reproductive categories. The perimenopause and polycystic ovarian syndrome groups demonstrated relative hypoestrogenic states, while the perimenopause group showed low luteal pregnanediol glucuronide and the polycystic ovarian syndrome/polyendocrine metabolic ovarian syndrome (PCOS/PMOS) group showed high luteal pregnanediol glucuronide. The perimenopause group had significantly higher luteinizing hormone values throughout the whole cycle. The fertile window hormone thresholds vary depending on a woman's specific reproductive category. Women in different circumstances should not necessarily use the same hormonal thresholds for the fertile window and ovulation. A larger dataset with ultrasound correlation to ovulation is required to delineate the fertile window with more precision. Hormone differences across the menstrual cycle could be used for targeted treatments in polycystic ovarian syndrome and perimenopause women.

menstrual-cycle/cycle-across-the-lifespan/cycle-and-general-health reproductive-endocrinology/ovarian-hormones/estrogenfertility-awareness/biomarkers/urinary-hormone-monitoring Open Access

Modeling Fertile Window Differences Across the Reproductive Lifespan with Quantitative Urine Hormone Monitoring of the Menstrual Cycle

Bouchard TP et al., 2025

Background Reproductive hormones of the fertile window are often referenced to women in regular cycles, but this may not be representative of the hormonal profiles of women in different circumstances like polycystic ovarian syndrome, the postpartum period, and the perimenopause transition. This observational cohort study sought to identify the variability in the hormones of the fertile window in various reproductive categories and to establish potential thresholds for each category based on hormone measurements with the Mira urinary hormone monitor. Results A total of 57 women (ages 22–51) in various circumstances (regular cycles, polycystic ovarian syndrome, postpartum and perimenopause) tracked Mira urine hormone measurements (estrone-3-glucuronide, luteinizing hormone, pregnanediol glucuronide), contributing 444 cycles of data. Using additive mixed models, hormone values were stratified by the four different reproductive categories. The perimenopause and polycystic ovararian syndrome groups demonstrated relative hypoestrogenic states, while the perimenopause group showed low luteal pregnanediol glucuronide and the polycystic ovarian syndrome group showed high luteal pregnanediol glucuronide. The perimenopause group had higher luteinizing hormone values throughout the whole cycle. Conclusion The fertile window hormone thresholds vary depending on a woman’s specific reproductive category. Women in different circumstances should not necessarily use the same hormonal thresholds for the fertile window and ovulation. A larger dataset with ultrasound correlation to ovulation is required to delineate the fertile window with more precision. Hormone differences across the menstrual cycle could be used for targeted treatments in polycystic ovarian syndrome and perimenopause women.

reproductive-endocrinology/ovarian-hormones/estrogen fertility-awareness/biomarkers/urinary-hormone-monitoringmenstrual-cycle/cycle-across-the-lifespan/cycle-and-general-health Open Access

Case Reports from Women Using a Quantitative Hormone Monitor to Track the Perimenopause Transition

Meyers M et al., 2023 Medicina (Kaunas)

The fertility tracking of menstrual cycles during perimenopause with a quantitative hormone monitor is a novel undertaking. Women in regular menstrual cycles have been tracking their fertility using different biomarkers since the 1960's. Presently, there are newer electronic hormonal devices used to track fertility that provide more exact and objective data to help delineate the fertile time frame of a woman's cycle. These devices measure quantitative levels of estrogen, the luteinizing hormone, progesterone, and follicle-stimulating hormone, all of which occur at varying levels during the menstrual cycle. As women advance toward menopause, their cycles vary in length, and their hormones fluctuate. In this retrospective analysis, forty-two women aged 40 to 50 tracked their cycles over time, and eight of these forty-two women used the quantitative hormonal device. With the use of this device, the perimenopausal period has revealed distinct hormonal cycle characteristics that are unique to this group of women. It is the purpose of this paper to discuss these cycle's characteristics during perimenopause, which were found with the use of the quantitative hormonal device.