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There is increasing information characterizing menstrual cycle length in women, but less information is available on the potential differences across lifestyle variables.
This study aimed to describe differences in menstrual cycle length, variability, and menstrual phase across women of different ages and BMI among a global cohort of Flo app users. We have also reported on demographic and lifestyle characteristics across median cycle lengths.
The analysis was run based on the aggregated anonymized dataset from a menstrual cycle tracker and ovulation calendar that covers all phases of the reproductive cycle. Self-reported information is documented, including demographics, menstrual flow and cycle length, ovulation information, and reproductive health and diseases. Data from women aged ≥18 years and who had logged at least three cycles (ie, 2 completed cycles and 1 current cycle) in the Flo app were included (1,579,819 women).
Of the 1.5 million users, approximately half (638,683/1,579,819, 40.42%) were aged between 18 and 24 years. Just over half of those reporting BMIs were in the normal range (18.5-24.9 kg/m2; 202,420/356,598, 56.76%) and one-third were overweight or obese (>25 kg/m2; 120,983/356,598, 33.93%). A total of 16.32% (257,889/1,579,819) of women had a 28-day median cycle length. There was a higher percentage of women aged ≥40 years who had a 27-day median cycle length than those aged between 18 and 24 years (22,294/120,612, 18.48% vs 60,870/637,601, 9.55%), but a lower percentage with a 29-day median cycle length (10,572/120,612, 8.77% vs 79,626/637,601, 12.49%). There were a higher number of cycles with short luteal phases in younger women, whereas women aged ≥40 years had a higher number of cycles with longer luteal phases. Median menstrual cycle length and the length of the follicular and luteal phases were not remarkably different with increasing BMI, except for the heaviest women at a BMI of ≥50 kg/m2.
On a global scale, we have provided extensive evidence on the characteristics of women and their menstrual cycle length and patterns across different age and BMI groups. This information is necessary to support updates of current clinical guidelines around menstrual cycle length and patterns for clinical use in fertility programs.
For more than 30 years, the notion has been that the average woman is potentially fertile between days 10 and 17 of her 28-day menstrual cycle. However, this assumes that ovulation occurs exactly 14 days before the onset of the next menstrual period and that the fertile window extends before and after ovulation [
Landmark longitudinal [
For the past 10 years, hundreds of smartphone apps have been developed for women to track their menstrual cycles, ovulation and fertile days, and health information [
This study aimed to describe differences in menstrual cycle length, variability, and menstrual phase across women of different ages and BMIs. We also reported on demographic and lifestyle characteristics across the median cycle length. The study analyses will provide extensive worldwide evidence on the characteristics of menstrual cycle length and patterns among a global cohort of Flo app users. This information is necessary to support recommendations within current obstetric clinical guidelines around menstrual cycle length and patterns for clinical use in fertility programs.
The data were collected through the mobile period tracking and ovulation calendar called Flo, which was launched in October 2015. Users of the Flo app are found in over 200 countries, but the vast majority of them are located in Europe and North America. Flo’s privacy policy and terms of use permit the use of aggregated and anonymized data for research purposes. Data collection for this study started in December 2018 and extracted from 2 million users aged ≥18 years. Women were not included if they had logged a pregnancy, oral contraceptive reminders, and had recorded less than 3 menstrual cycles, which was the minimum number needed to obtain median cycle data. This resulted in a cohort of 1,579,819 women.
The participants' ages were collected through the mandatory sign-up questionnaire, and BMI was calculated for women who reported their weight (the latest input was used) and height. Additional information was collected from the user in 2 ways: (1) by tracking the symptoms that users log themselves and (2) by survey answer questions. For example, the user can log information on cycle length, period length and intensity, and days of the luteal phase. The survey information that users can report includes a range of questions regarding diet, lifestyle (general well-being, sleep, sexual activity, physical activity, stress, alcohol), menstrual cycle symptoms, and reproductive health information. Manually logged information reported in the current analyses included information on weight (in kilogram, logged manually), menstrual flow (light, medium, heavy), smoking status (regularly, sometimes, do not smoke), alcohol consumption (≥3 times a week, 1-2 times a week, <2-3 times a month, none), frequency of high stress (≥3 times a week, 1-2 times a week, <3 times a month, none), frequency of physical activity (≥3 times a week, 1-2 times a week, <3 times a month, none), relationship status (married or stable partner, single, no partner), months trying to conceive (<1 month, 1-3 months, 3-6 months, >6 months to 1 year, >1 year), number of children (0, 1, or 2, ≥3), and any reproductive disorders (yes, no, I don't know).
Women manually logged information about their menstrual cycles (days of menstruation), including the intensity of menstrual flow (light, medium, heavy). The start and end dates of menstrual cycles were defined by the logged first day of menstruation. To estimate mean and median cycle lengths, we computed intrawomen inputs and then calculated the mean and median for population groups.
The data from over 1.5 million nonpregnant women who were not using oral contraceptives and who had logged at least 3 cycles (N=1,579,819) were included in the study (
Description of the study population.
Characteristics | Values, n (%) | |
|
||
|
18-24 | 638,683 (40.43) |
|
25-29 | 383,179 (24.25) |
|
30-34 | 275,039 (17.41) |
|
35-39 | 162,156 (10.26) |
|
40-55 | 120,762 (7.64) |
|
||
|
≤18.4 | 33,195 (9.31) |
|
18.5-24.9 | 202,420 (56.76) |
|
25.0-29.9 | 70,707 (19.83) |
|
30.0-34.9 | 30,144 (8.45) |
|
35.0-50.0 | 19,540 (5.48) |
|
≥50+ | 592 (0.17) |
|
Light | 44,171 (22.36) |
|
Medium | 148,236 (75.03) |
|
Heavy | 5172 (2.62) |
|
||
|
Regularly | 104,612 (14.01) |
|
Sometimes | 87,506 (11.72) |
|
Do not smoke | 554,278 (74.26) |
|
||
|
≥3 times a week | 42,115 (5.67) |
|
1-2 times a week | 144,263 (19.42) |
|
<2-3 times a month | 310,597 (41.82) |
|
None | 245,640 (33.08) |
|
||
|
≥3 times a week | 252,894 (32.90) |
|
1-2 times a week | 248,630 (32.35) |
|
<3 times a month | 218,490 (28.43) |
|
None | 48,557 (6.32) |
|
||
|
≥3 times a week | 140,287 (17.52) |
|
1-2 times a week | 176,124 (22.00) |
|
<3 times a month | 121,145 (15.13) |
|
None | 363,314 (45.36) |
|
||
|
Married or stable partner | 531,360 (70.98) |
|
Single | 73,194 (9.78) |
|
No partner | 144,058 (19.24) |
|
||
|
<1 month | 36,510 (26.46) |
|
1-3 months | 27,383 (19.85) |
|
3-6 months | 17,108 (12.40) |
|
>6 months to 1 year | 15,088 (10.94) |
|
>1 year | 41,884 (30.36) |
|
||
|
0 | 501,976 (70.80) |
|
1 or 2 | 178,303 (25.15) |
|
≥3 | 28,758 (4.06) |
|
||
|
Yes | 76,722 (11.16) |
|
No | 443,597 (64.54) |
|
I don’t know | 166,971 (24.29) |
In all, 91.13% (1,439,613/1,579,819) of women had a median cycle length of 21 to 35 days, whereas 89.04% (1,406,643/1,579,819) had an average cycle length of 21 to 35 days. A total of 0.17% (2614/1,579,819) had a short cycle length (<21 days), and 8.60% (135,824/1,579,819) had a long cycle length (>35 days). The percentage of women with a median 27-day, 28-day, and 29-day cycle length was 12.05% (190,373/1,579,819), 16.32% (257,889/1,579,819), and 12.11% (191,351/1,579,819), respectively.
Demographic and lifestyle characteristics across median cycle length.
Characteristics | Short cycle (≤20 days), n (%) | Normal cycle (21-35 days), n (%) | Long cycle (≥36 days), n (%) | |
|
||||
|
18-24 | 1255 (48.01) | 556,541 (39.57) | 80,887 (47.42) |
|
25-29 | 634 (24.25) | 334,817 (23.80) | 47,728 (27.98) |
|
30-34 | 330 (12.62) | 248,280 (17.65) | 26,429 (15.50) |
|
35-39 | 170 (6.50) | 151,867 (10.80) | 10,119 (5.93) |
|
40-55 | 225 (8.61) | 115,138 (8.19) | 5399 (3.17) |
|
||||
|
≤18.4 | 31 (8.1) | 29,309 (9.21) | 3855 (10.16) |
|
18.5-24.9 | 182 (47.6) | 182,511 (57.35) | 19,727 (51.98) |
|
25.0-29.9 | 85 (22.3) | 63,183 (19.85) | 7439 (19.60) |
|
30.0-34.9 | 40 (10.5) | 26,253 (8.25) | 3851 (10.15) |
|
35.0-50.0 | 42 (11.0) | 16,515 (5.19) | 2983 (7.86) |
|
≥50.0 | 2 (0.5) | 494 (0.16) | 96 (0.25) |
|
||||
|
Light | 240 (50.4) | 37,469 (21.78) | 6462 (25.77) |
|
Medium | 222 (46.6) | 130,178 (75.67) | 17,836 (71.12) |
|
Heavy | 14 (2.94) | 4378 (2.54) | 780 (3.11) |
|
||||
|
Smoke regularly | 160 (14.6) | 94,649 (14.18) | 9803 (12.56) |
|
Smoke sometimes | 155 (14.1) | 78,205 (11.72) | 9146 (11.72) |
|
Do not smoke | 782 (71.3) | 494,381 (74.09) | 59,115 (75.73) |
|
||||
|
≥3 times a week | 60 (5.5) | 38,455 (5.79) | 3600 (4.64) |
|
1-2 times a week | 213 (19.5) | 130,651 (19.68) | 13,399 (17.25) |
|
<2-3 times a month | 444 (40.7) | 277,731 (41.84) | 32,422 (41.75) |
|
None | 373 (34.2) | 217,031 (32.69) | 28,236 (36.36) |
|
||||
|
≥3 times a week | 448 (40.1) | 224,951 (32.75) | 27,495 (34.13) |
|
1-2 times a week | 359 (32.1) | 221,845 (32.30) | 26,426 (32.80) |
|
<3 times a month | 235 (21.0) | 196,573 (28.62) | 21,682 (26.92) |
|
None | 75 (6.7) | 43,528 (6.34) | 4954 (6.15) |
|
||||
|
≥3 times a week | 191 (16.5) | 127,088 (17.76) | 13,008 (15.49) |
|
1-2 times a week | 190 (16.4) | 158,190 (22.10) | 17,744 (21.13) |
|
<3 times a month | 155 (13.4) | 107,620 (15.04) | 13,370 (15.92) |
|
None | 622 (53.7) | 322,839 (45.11) | 39,853 (47.46) |
|
||||
|
<1 month | 63 (27.8) | 32,361 (26.82) | 4086 (23.93) |
|
1-3 months | 49 (1.6) | 23,828 (19.75) | 3506 (20.53) |
|
3-6 months | 35 (15.4) | 14,902 (12.35) | 2171 (12.71) |
|
>6 months to 1 year | 18 (7.9) | 13,096 (10.85) | 1974 (11.56) |
|
>1 year | 62 (27.3) | 36,484 (30.23) | 5338 (31.26) |
|
||||
|
0 | 650 (63.22) | 444,711 (70.14) | 56,615 (76.55) |
|
1 or 2 | 324 (31.52) | 162,663 (25.65) | 15,316 (20.71) |
|
≥3 | 54 (5.25) | 26,679 (4.21) | 2025 (2.74) |
|
||||
|
Yes | 164 (16.7) | 64,376 (10.47) | 12,182 (17.01) |
|
No | 563 (57.2) | 403,419 (65.63) | 39,615 (55.32) |
|
I don't know | 257 (26.1) | 146,896 (23.90) | 19,818 (27.67) |
aShort cycle (N=2614), normal cycle (N=1,406,643), and long cycle (N=170,562).
bShort cycle (N=382), normal cycle (N=318,265), and long cycle (N=37,951).
cShort cycle (N=476), normal cycle (N=172,025), and long cycle (N=25,078).
dShort cycle (N=1097), normal cycle (N=667,235), and long cycle (N=78,064).
eShort cycle (N=1090), normal cycle (N=663,868), and long cycle (N=77,657).
fShort cycle (N=1117), normal cycle (N=686,897), and long cycle (N=80,557).
gShort cycle (N=1158), normal cycle (N=715,737), and long cycle (N=83,975).
hShort cycle (N=227), normal cycle (N=120,671), and long cycle (N=17,075).
iShort cycle (N=1028), normal cycle (N=634,053), and long cycle (N=73,956).
jShort cycle (N=984), normal cycle (N=614,691), and long cycle (N=71,615).
Median cycle length distribution by age groups.
Median cycle length distribution by BMI categories.
Variation in cycle length across age group.
Variation in cycle length across BMI categories.
There were 18,761 cycles with positive LH ovulation tests, signifying the end of the follicular phase, and the following day to be the day of estimated ovulation. The highest percentage of cycles was at an estimated ovulation day 14 (13.08%, 2509 cycles;
The length of the luteal phase was highest at day 15, with 16.96% (3696/21,788) of the cycles, followed by a 14-day luteal phase, with 16.17% (3523/21,788) of the cycles (
Estimated ovulation day based on positive luteinizing hormone test (N=18,761 cycles).
Estimated day of ovulation | Cycles, n (%) |
11 | 1668 (8.89) |
12 | 1877 (10.00) |
13 | 2248 (11.98) |
14 | 2509 (13.37) |
15 | 2267 (12.08) |
16 | 1905 (10.15) |
17 | 1518 (8.09) |
18 | 1154 (6.15) |
19 | 822 (4.38) |
20 | 636 (3.39) |
21 | 458 (2.44) |
22 | 321 (1.71) |
23 | 304 (1.62) |
24 | 266 (1.41) |
25 | 189 (1.00) |
26 | 184 (0.98) |
27 | 149 (0.79) |
28 | 160 (0.85) |
29 | 126 (0.67) |
Estimated luteal phase length based on positive luteinizing hormone test (N=18,761).
Length of luteal phase (days) | Cycles, n (%) |
5 | 142 (0.75) |
6 | 172 (0.91) |
7 | 206 (1.09) |
8 | 227 (1.20) |
9 | 344 (1.83) |
10 | 543 (2.89) |
11 | 946 (5.04) |
12 | 1565 (8.34) |
13 | 2645 (14.09) |
14 | 3523 (18.77) |
15 | 3696 (19.70) |
16 | 2765 (14.73) |
17 | 1819 (9.69) |
18 | 1380 (7.35) |
19 | 1006 (5.36) |
20 | 809 (4.31) |
We have reported recent and comprehensive data characterizing over 1.5 million women and their menstrual cycle patterns. Approximately two-thirds of women using the app were aged <30 years and one-third were overweight or obese based on their BMI. The majority of women (1,439,613/1,579,819, 1.13%) had a usual median cycle length of 21 to 35 days, of whom 16.32% (257,889/1,579,819) had a median cycle length of 28 days. Shorter cycles with less variation were more common for women ≥40 years. Among women who reported short cycles, a higher percentage reported higher stress levels, no physical activity, and a lighter menstrual flow in comparison with women with normal or long cycles. There were only subtle differences in length and variability across BMIs; however, women with the lowest BMI tended to have the highest variation in cycle length and more women with a BMI >35 kg/m2 had a median cycle of 36 days and longer.
The reporting of menstrual cycle length and patterns was estimated from mobile phone data collected from women using the app. Although this app has a global reach of 100 million women using the app, and 30 million active users monthly, not all women reported on their BMI or other lifestyle characteristics. This means these findings cannot be generalized to all women using the app. Recently, a review of pregnancy apps and their use in culturally and linguistically diverse women found that engagement with apps may be lower in areas of higher social disadvantage, cultural and language barriers, and health literacy [
The strengths of this study include the very large cohort of women providing fertility information, along with data on a high number of ovulatory cycles. The Flo app uses artificial intelligence–based algorithms, and when additional data, such as basal body temperature and ovulation data, are entered, the predictive ability improves. Comparatively, calendar-based apps may only use simulated 28-day cycles to estimate ovulation, or predictive methods may be used; for example, the standard days method, where users avoid unprotected intercourse during cycle days 8 through 19 [
Imperative to our study is that we assessed
Our results are consistent with previous studies reporting on shorter cycle lengths with increasing age [
Epidemiological evidence has demonstrated the adverse effects of obesity on female reproduction, including anovulation and menstrual cycle irregularities [
This is the largest analysis to report on physical activity, stress, and menstrual flow across short, normal, and long menstrual cycle lengths. Interestingly, shorter cycles were associated with a higher frequency of high stress, no physical activity, and lighter menstrual flow. There is limited information on stress and physical activity, but research to date suggests that professional and high-frequency training impairs ovarian activity, which may manifest as luteal phase defects, irregular menstruation, or amenorrhea [
The current findings have clinical implications for women who are trying to conceive but also for women with different lifestyle characteristics. First, current estimations for conceiving are based on the premise of a 28-day cycle with ovulation on day 14. We demonstrated that only 16% of women had a median 28-day cycle. Our results invoke a fundamental change in the assessment of cycle lengths of individual women and that the population mean cycle length may no longer be an applicable form of its measurement. Second, few menstrual cycle differences were seen in women with different BMIs. Finally, lifestyle factors such as physical activity and stress may relate to cycle length and therefore the potential day of ovulation. Prediction models, including menstrual cycle data as well as age and lifestyle factors, could be developed to predict the likelihood of pregnancy success. The use of such models would be helpful in the clinic setting to optimize conception, particularly in those who do not have regular cycles.
On a global scale, we have provided extensive evidence on the characteristics of women and their menstrual cycle length and patterns. We demonstrate that the typical average 28-day cycle length is not common for a high percentage of women, and only 13.08% of cycles had an estimated ovulation on day 14. Age appeared to be a more important factor than BMI in terms of menstrual cycle length and variability. Our data provide important information on the necessity for an individualized approach to support reproductive health and fertility, and modifiable factors such as physical activity and stress should additionally be considered when planning a pregnancy. Future work could extend these findings by addressing cultural and ethnic diversities in relation to menstrual cycle patterns.
Estimated length of the follicular phase.
Estimated ovulation day based on positive luteinizing hormone test across age groups (N=18,761 cycles).
Estimated ovulation day based on positive luteinizing hormone test across BMI group (N=18,235 cycles).
Number of cycles and the luteal length, according to age.
Number of cycles and the luteal length, according to BMI.
heavy
light
luteinizing hormone
medium
metabolic equivalent
The authors gratefully acknowledge the members of the Flo team, Anna Targonskaya, Natalia Kukharchyk, Anna Klepchukova, and Andrei Zhabinsk, who generated the results and allowed the authors to make use of the data. Without them, this paper would not have been possible. The authors appreciate their guidance and assistance with the results and the overall paper.
JG and RN contributed substantially to the conception and design of the study. JG wrote the first draft of the manuscript. All authors read the final draft of the manuscript and revised it critically for its intellectual content. All authors read and approved the final manuscript.
None declared.