Your BMI Could Affect Your Menstrual Cycle - Researchers Explain How

Your BMI Could Affect Your Menstrual Cycle - Researchers Explain How

New data from 8,700 women shows how being underweight and obesity disrupts cycles - and why hitting a BMI sweet spot of 20 could boost fertility and ovulation.

In a study recently published in the journalNPJ Women's HealthResearchers examined the relationship between body mass index (BMI) and menstrual irregularities.

The characteristics of the menstrual cycle are among the most accessible indicators for assessing women's health. Regular menstruation depends on a functional hypothalamic-pituitary-ovarian (HPO) axis, disruption of which could lead to abnormalities such as anovulation, amenorrhea and irregular menstrual cycles. Research suggests that individuals with extreme BMI are at higher risk of menstrual irregularities.

In addition, high BMI and obesity are often associated with infertility, mainly due to hormonal and metabolic disorders that affect ovulation. Additionally, underweight individuals are reported to be at higher risk of ovulatory infertility, although studies have been limited to specific populations, such as: B. Female athletes and those with anorexia nervosa. Furthermore, existing studies on menstrual irregularities and BMI extremities are inconsistent.

About the study

The study used real-world data from over 8,700 participants and 191,000 menstrual cycles, making it the largest BMI and menstrual health study.

The present study examined the relationship between menstrual cycle irregularities and BMI. The study used a mobile time tracking (mobile application (Lunaluna) in Japan. Menstrual data were collected from January 2019 to March 2021 from app users who agreed to participate. Participants completed bimonthly questionnaires collecting information on health conditions, lifestyle, education, and employment.

The first questionnaire (Wave 1) was administered from January 23 to March 25, 2020 and the second (Wave 2) was administered from June 14 to June 14, 2020. Respondents with data from both waves were included in the analyses. Participants were excluded if they had a BMI <15 kg/m² or >35 kg/m², were pregnant, underwent infertility treatment using hormonal contraceptives or IUD/ius, or logged fewer than three menstrual cycles. Additionally, extreme outlier cycles (>4 standard deviations from the mean cycle length) were removed to ensure data quality.

The primary outcomes were cycle length (CL), proportion of subjects with menstrual irregularities, and proportion of biphasic cycles.

Menstrual irregularity indicators were infrequent menstrual bleeding (IMB, defined as CL ≥ 39 days but <90 days) and absent menstrual bleeding (AMB, defined as CL ≥ 90 days, according to Figo guidelines). For basal body temperature (BBT) analysis, the luteal phase was defined as the 10 days before the next menstruation, while the follicular phase was defined as the first 10 days from the start of the menstrual cycle.

A cycle was considered bivalent if the difference in the mid-luteal phase -BBT from the follicular phase BBT was greater than 0.3 °C, an indicator of ovulatory function. The relationship between BMI and outcomes was assessed using a restricted cubic spline model with linear regression for continuous outcomes, logistic regression for binary outcomes, and Poisson regression for proportions (of biphasic cycles).

Results

Women with a BMI below 19 or above 26 were more likely to experience missed menstrual periods (ABB), highlighting how weight cycles regularly affect the cycle.

A total of 10,465 people completed both questionnaires (waves 1 and 2). Each subject logged an average of 21 cycles. They were excluded if they had a BMI <15 kg/m , were pregnant for fewer than three cycles, or were on infertility treatment or on hormonal contraceptives. After exclusions, 8,745 participants with 191,426 menstrual cycles were included. BBT data were collected from 3,221 participants with 15,883 cycles.

Overall, participants were in their late 20s or early 30s and were unmarried, employed, and non-smokers. Using Asian-specific BMI categories, approximately 14% of participants were underweight (15-18.4 kg/m2), 59% were normal BMI (18.5-22.9 kg/m2), 13% were overweight (23-24.9 kg/m2), and 14% were fat (25-35 kg/m2). The average CL was 31.5 days. In addition, 7% of subjects had IMB and 4% had Amb. Participants with a BMI of 20 kg/m² had the lowest mean, while those with a BMI of ≤ 16 kg/m² or ≥ 30 kg/m² had significantly longer cycles (+1.03 and +1.06 days, respectively).

Overweight and obese individuals had a higher risk of IMB than those with normal BMI (overweight: or 1.56; obese: or 2.63). In addition, underweight and obese individuals showed greater AMB risks than those with normal BMI (underweight: or 1.78; obese: or 1.94). A J-shaped relationship between BMI with IMB and AMB showed that higher and lower BMIs increased the prevalence of IMB and Amb.

Additionally, individuals with a BMI ≤ 18 kg/m² or ≥21 kg/m² had a higher risk of IMB than those with a BMI 20 kg/m². Similarly, the risk of Amb was significantly higher in individuals with a BMI ≤ 19 kg/m² or ≥26 kg/m².

Furthermore, there was an inverted J-shaped relationship between BMI and the proportion of biphasic cycles, suggesting that ovulatory function was optimal at BMI 20 kg/m² but decreased at both higher and lower BMI values. This finding highlights that both overweight and underweight individuals are at increased risk of anovulation.

Conclusions

The results suggest that even small changes in BMI outside the normal range could increase the likelihood of longer, unpredictable menstrual cycles.

The results illustrate a nonlinear relationship between BMI and menstrual cycle characteristics. People with a low or high BMI showed increased risks of longer, irregular menstrual cycles. Furthermore, an inverted J-shaped relationship with the proportion of biphasic cycles confirmed that both high and low BMI increased the risk of non-ovulatory cycles and possibly led to ovulatory infertility.

Overall, individuals with normal BMI (particularly around 20 kg/m²) had the lowest risk of irregular, non-ovulatory menstrual cycles, highlighting the reproductive health benefits of maintaining a normal BMI.

However, the study was conducted exclusively in Japan, and the authors note that BMI-obesity relationships differ between ethnic groups. These results may not be directly generalizable to non-Asian populations. Additionally, potential selection bias should be considered as app users may not fully represent the general population. Reliance on self-reported BMI data is another limitation that should be acknowledged.

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