Highlights
-
•
In 1025 previously pregnant participants, 6.1% had previously been diagnosed with relative energy deficiency in sport and 20.5% had a history of secondary amenorrhea.
-
•
Participants diagnosed with relative energy deficiency in sport prior to conception had 3.5 times higher odds of having premature labor and 2.6 times higher odds of preterm delivery compared to those who had never been diagnosed.
-
•
Participants with a history of secondary amenorrhea did not have increased odds of adverse pregnancy or delivery outcomes.
Keywords: Perinatal health, Energy availability, Exercise
Abstract
Background
Relative energy deficiency in sport (REDs) results from exposure to problematic low energy availability. It is a serious condition affecting the health and athletic performance of up to 80% of elite female athletes. REDs is established to have negative short-term effects on reproductive function, but the long-term impact of this condition is unknown. Therefore, we examined the impact of secondary amenorrhea with or without a concurrent diagnosis of REDs on perinatal health outcomes.
Methods
Postpartum individuals (≥18 years of age) completed an online questionnaire that covered demographics, reproductive history (including a diagnosis of REDs or secondary amenorrhea), and maternal/fetal health outcomes. Logistic regression was used to determine the relationship between previously diagnosed REDs or secondary amenorrhea with perinatal health outcomes.
Results
A total of 1025 previously pregnant participants completed the survey (33.1 ± 3.4 years, mean ± SD). Prior to pregnancy, 6.1% had been previously diagnosed with REDs and 20.5% had a history with secondary amenorrhea. Individuals diagnosed with REDs had 3.5-times higher odds of having premature labor (odds ratio, (OR) = 3.52, 95% confidence interval (95%CI): 1.26–9.81) and 2.6-times higher odds of preterm delivery (OR = 2.62, 95%CI: 1.05–6.58) compared to those who had not experienced REDs or secondary amenorrhea. However, in individuals who did not have a history of REDs, secondary amenorrhea did not increase the odds of adverse pregnancy or delivery outcomes.
Conclusion
A history of REDs, but not secondary amenorrhea, may increase the odds of premature labor and preterm delivery.
Graphical abstract
1. Introduction
More than half of female athletes will experience menstrual dysfunction during their athletic career.1,2 Despite the frequency of primary and secondary amenorrhea and oligomenorrhea, there is a striking lack of awareness and research surrounding their impact on future reproductive health in athletic populations. It is well established that a primary cause of menstrual dysfunction in athletes is low energy availability (LEA). LEA occurs when energy intake is insufficient to support the energy expended through exercise.3 While mild, short-term exposure to LEA (adaptable LEA) can have tolerable health impacts, more severe, prolonged exposure (problematic LEA) can adversely affect both health and athletic performance.4 Relative energy deficiency in sport (REDs) is a syndrome resulting from problematic LEA that affects up to 80% of female athletes.4 REDs (formerly known as the Female Athlete Triad) was first recognized by the International Olympic Committee in 2014, and awareness of the short-term health impacts of the condition have been growing ever since.5 Previous work has demonstrated that REDs leads to reduced levels of reproductive hormones, primary or secondary amenorrhea, and anovulatory cycles.4,6,7 However, the longer-term impact of these changes on reproductive function during pregnancy and postpartum has yet to be elucidated. While there is limited research looking directly at fertility outcomes in athletes with a history of REDs, the well-established link between LEA-related menstrual dysfunction and anovulation points to potential challenges with achieving pregnancy. Insights from animal studies and malnourished populations suggest that chronic LEA may reduce the body’s biological capacity to reproduce. This is believed to relate, at least in part, to inhibited gonadotropin-releasing hormone secretion.8, 9, 10 In countries with high levels of malnutrition, miscarriage rates may be higher than in other populations, although this is difficult to measure accurately.9 Anorexia nervosa in pregnancy, which is likely to coincide with LEA, is associated with higher rates of preterm labor, oligohydramnios, severe maternal morbidity, a small for gestational age or low-birthweight infant, and preterm birth between 32 and 36 weeks with spontaneous preterm labor.10,11
As the number of female athletes continues to grow, a greater understanding of the health implications of LEA and REDs on reproductive capacity and pregnancy outcomes is critical. The existing lack of awareness has led some athletes to believe that conditions such as amenorrhea, LEA, and REDs lead to future reproductive issues.12 However, these claims have yet to be substantiated. Therefore, we aim to explore the relationship between a history of REDs or the presence of secondary amenorrhea with pregnancy and postpartum health outcomes.
2. Methods
Between November 6, 2023 and September 16, 2024, we recruited 1025 participants through social media (e.g., Instagram), word of mouth, and the authors’ personal networks to participate in an exploratory online survey. To be eligible to participate, participants had to be at least 18 years of age and to have previously given birth at least 1 time. Electronic informed consent was provided before completing an online survey. This study was approved by the University of Alberta Health Research Ethics Board (Pro00135105) and was conducted in accordance with the Declaration of Helsinki, apart from registration in a publicly available database. Responses were collected through Research Electronic Data Capture (REDCap; https://project-redcap.org), a web-based software hosted by the Women and Children’s Health Research Institute, University of Alberta, Canada.13,14 We used a cross-sectional design and analyzed the survey results according to the checklist for reporting results of internet e-surveys (CHERRIES).15 There were no incentives offered for completing the survey.
2.1. Survey
The questionnaire was developed by pelvic health physiotherapists (SD and EB), exercise physiologists (MHD and PATJ), and a sports medicine physician (AH) from Canada and the UK. The public was not involved in the design of this study. The questionnaire covered maternal demographics, reproductive history (pregnancy loss, use of assisted reproductive technology, diagnosis of REDs, absence of menstrual cycle aside from pregnancy or contraceptive use), and perinatal (preconception to postpartum) health outcomes, and it took 15–20 min to complete. Participants were able to review and change their answers by use of a “Back” button throughout the survey. The usability and technical functionality of the questionnaire was piloted prior to public release.
2.2. Statistical analysis
Following closure of the survey, data were cleaned and verified for accuracy, and impossible (e.g., non-human body weight) data were removed. All exclusions were reviewed by PATJ and MHD and discarded following consensus. We collected 1075 survey responses, of which 1025 (95.3%) were used in the final analyses. Fifty participants were removed due to missing data on one of the key variables: location, maternal age at delivery, infant birth weight, experience with fertility treatments, and pregnancy loss. Participants with a past diagnosis of REDs were allocated to the “REDs” group. Those with a history of secondary amenorrhea but who had not been diagnosed with REDs were allocated to the “Secondary amenorrhea” group. All other participants were allocated to the “No amenorrhea” group. Participants were allocated to a single group. The mean ± SD was calculated for continuous variables, and frequency of responses (n (%)) were calculated for categorical variables. Categorical variables were as follows: binary (yes/no), or infant birth weight (low birthweight: less than 2500 g; normal: 2500–3999 g; macrosomia: 4000 g or more), or delivery mode (vaginal unassisted; vaginal assisted: vacuum; vaginal assisted: forceps; caesarean section: emergency; caesarean section: elective; vaginal: unknown; or caesarean section: unknown). For binary variables, logistic regression was used to calculate the odds (odds ratio, OR) and 95% confidence interval (95%CI) to determine the relationship between previously diagnosed REDs or secondary amenorrhea and pregnancy and postpartum health outcomes. Multinomial (polytomous) logistic regression (relative risk ratio; RRR) was used to evaluate the relationship between previously diagnosed REDs or secondary amenorrhea and the multinomial outcomes: delivery mode and birth weight. Beta coefficients of birth weight were calculated using linear regression based on previously diagnosed REDs or secondary amenorrhea. The regression predicting infant birth weight was adjusted for preterm delivery, and the interaction between preterm delivery and maternal energy status was reviewed for significance. All statistical analyses were completed in STATA release 18 (StataCorp LLC., College Station, TX, USA). Statistical significance was defined as p < 0.05.
3. Results
3.1. Participant characteristics
Participants (n = 1025) were 33.10 ± 3.43 years (mean ± SD) at the time of delivery and were from 33 different countries, primarily the UK (44.1%), Canada (20.1%), and the USA (17.9%) (Table 1). Additional subject characteristics can be found in Supplementary Table 1.
Table 1.
Participant demographics (n = 1,025).
| Subgroup | Data |
|---|---|
| Age at delivery (year) | 33.10 ± 3.43 |
| Gestational age at delivery (week) | 39.28 ± 1.86 |
| Location | |
| Australia | 73 (7.1) |
| Canada | 206 (20.1) |
| Germany | 10 (1.0) |
| Ireland | 44 (4.3) |
| New Zealand | 10 (1.0) |
| Norway | 7 (0.7) |
| Switzerland | 6 (0.6) |
| UK | 452 (44.1) |
| USA | 183 (17.9) |
| Other | 34 (3.3) |
| Pregnancy loss | |
| Yes | 309 (30.2) |
| No | 716 (69.8) |
| Preconception | |
| Mental health | |
| Anxiety | 192 (18.7) |
| Depression | 114 (11.1) |
| Post-traumatic stress disorder | 16 (1.6) |
| Obsessive compulsive disorder | 12 (1.2) |
| Premenstrual dysphoric disorder | 8 (0.8) |
| Other | 2 (0.2) |
| Gynecological | |
| Painful periods | 66 (6.4) |
| Polycystic ovary syndrome | 51 (5.0) |
| Heavy menstrual bleeding | 43 (4.2) |
| Endometriosis | 26 (2.5) |
| Other | 30 (2.9) |
| Symptoms of pelvic floor dysfunction | |
| Urinary incontinence | 68 (6.6) |
| Pelvic organ prolapse | 34 (3.3) |
| Fecal urgency | 11 (1.1) |
| Obstructive defecation | 6 (0.6) |
| Wind incontinence | 4 (0.4) |
| Anal incontinence | 3 (0.3) |
Notes: Data are presented as mean ± SD or n (%). Percentages for location might not add up to 100% due to rounding. The “Other” category in Location includes 3 participants from Greece; 2 participants from each of the following countries: Austria, Belgium, Denmark, France, Latvia, Qatar, South Africa, and Spain; and 1 participant from each of the following countries: Brazil, Brunei, Chile, China, Israel, Italy, Malaysia, Malta, Mauritius, Philippines, Portugal, Serbia, Singapore, Sweden, and United Arab Emirates.
3.2. Reproductive outcomes
The most common complaints during pregnancy were related to the musculoskeletal system (low back pain/pelvic girdle pain and diastasis recti abdominus). Gestational diabetes, preeclampsia, and gestational hypertension were reported by 4.8%, 3.0%, and 2.6% of the population, respectively (Table 2).
Table 2.
Pregnancy health outcomes.
| System | Condition | No amenorrhea (n = 752) |
Secondary amenorrhea (n = 210) | REDs (n = 63) | Total (n = 1025) | ||
|---|---|---|---|---|---|---|---|
| Mental health | |||||||
| Anxiety | 112 (14.9) | 29 (13.8) | 11 (17.5) | 152 (14.8) | |||
| Depression | 40 (5.3) | 14 (6.7) | 4 (6.4) | 58 (5.7) | |||
| Obstetric | |||||||
| Unexplained vaginal bleeding | 25 (3.3%) | 12 (5.7) | 6 (9.5) | 43 (4.2%) | |||
| Twin pregnancy | 11 (1.5) | 4 (1.9) | 1 (1.6) | 16 (1.6) | |||
| Placenta previa >28 weeks | 8 (1.1) | 0 (0) | 0 (0) | 8 (0.8) | |||
| Incompetent cervix | 2 (0.3) | 0 (0) | 0 (0) | 2 (0.2) | |||
| Metabolic | |||||||
| Hyperemesis gravidarum | 35 (4.7) | 14 (6.7) | 4(6.4) | 53 (5.2) | |||
| Gestational diabetes | 37 (4.9) | 12 (5.7) | 0 (0) | 49 (4.8) | |||
| Preeclampsia | 23 (3.1) | 7 (3.3) | 1 (1.6) | 31 (3.0) | |||
| Gestational hypertension | 21 (2.8) | 6 (2.9) | 0 (0) | 27 (2.6) | |||
| Thyroid disease | 20 (2.6) | 5 (2.4) | 1 (1.6) | 26 (2.5) | |||
| Obstetric cholestasis | 3 (0.4) | 4 (1.9) | 0 (0) | 7 (0.7) | |||
| Urogynecological | |||||||
| Stress urinary incontinence | 71 (9.4) | 29 (13.8) | 8 (12.7) | 108 (10.5) | |||
| Urgency urinary incontinence | 30 (4.0) | 7 (3.3) | 2 (3.2) | 39 (3.8) | |||
| Pelvic organ prolapse | 26 (3.5) | 9 (4.3) | 0 (0) | 35 (3.4) | |||
| Anal incontinence | 2 (0.3) | 0 (0) | 0 (0) | 2 (0.2) | |||
| Musculoskeletal | |||||||
| LBP/PGP | 279 (37.1) | 75 (35.7) | 23 (36.5) | 377 (36.8) | |||
| Diastasis recti abdominus | 146 (19.4) | 48 (22.9) | 10 (15.9) | 204 (19.9) | |||
| Umbilical hernia | 1 (11.5) | 2 (1.0) | 1 (1.6) | 4 (0.4) | |||
| Hematological | |||||||
| Iron deficiency | 113 (15.0) | 26 (12.4) | 10 (15.9) | 149 (14.5) | |||
| Anemia | 35 (4.7) | 22 (10.5) | 3 (4.8) | 60 (5.9) | |||
| Other | 18 (2.4) | 7 (3.3) | 4 (6.3) | 31 (3.0) | |||
| Delivery | |||||||
| Premature labor | 18 (2.3) | 18 (2.3) | 5 (7.9) | 41 (4.0) | |||
| Preterm delivery <37 weeks | 29 (3.9) | 29 (3.9) | 6 (9.5) | 64 (6.2) | |||
| Vaginal | |||||||
| Unassisted | 358 (47.7) | 96 (45.7) | 29 (46.0) | 483 (47.3) | |||
| Forceps | 47 (6.3) | 8 (3.8) | 3 (4.8) | 58 (5.7) | |||
| Vacuum | 37 (5.0) | 10 (4.8) | – | 47 (4.6) | |||
| Unspecified | 112 (15.0) | 32 (15.2) | 15 (23.8) | 159 (15.6) | |||
| C-section | |||||||
| Emergency | 84 (11.2) | 31 (14.8) | 10 (15.9) | 125 (12.2) | |||
| Elective | 93 (12.4) | 25 (11.9) | 6 (9.5) | 124 (12.1) | |||
| Unspecified | 17 (2.3) | 8 (3.8) | – | 25 (2.5) | |||
Notes: Data are presented as n (%). Percentages of mode of delivery might not add up to 100% due to rounding.
Abbreviations: LBP/PGP = low back pain/pelvic girdle pain; REDs = relative energy deficiency in sport.
3.3. Infant outcomes
Average infant birth weight was 3440.67 ± 561.65 g, with 42 infants being categorized as low birth weight and 141 with macrosomia (Table 3). Infants whose mother had a history of REDs were significantly lighter (p = 0.002) than those with no history of secondary amenorrhea or a history of secondary amenorrhea. Controlling for preterm delivery did not correct the difference. There was no difference between groups in the number of infants with low birth weight or macrosomia (Supplementary Table 2).
Table 3.
Infant health outcomes.
| System | No amenorrhea | Secondary amenorrhea | REDs | Total |
|---|---|---|---|---|
| Gestational age at delivery (week) | 39.28 ± 1.85 | 39.37 ± 1.93 | 39.02 ± 1.76 | 39.28 ± 1.86 |
| Birth weight (g) | 3459.88 ± 560.15 | 3432.94 ± 545.45 | 3237.08 ± 599.69 | 3440.67 ± 561.65 |
| Birth weight (g) | ||||
| Low birth weight (<2500) | 28 (3.7) | 8 (3.8) | 6 (9.5) | 42 (4.1) |
| Macrosomia (4000+) | 108 (14.4) | 29 (13.8) | 4 (6.4) | 141 (13.8) |
| Admitted to the NICU | ||||
| Yes | 62 (8.3) | 15 (7.1) | 2 (3.2) | 79 (7.7) |
| No | 687 (91.7) | 195 (92.9) | 61 (96.8) | 943 (92.3) |
Note: Data are presented as mean ± SD or n (%).
Abbreviations: NICU = neonatal intensive care unit; REDs = relative energy deficiency in sport.
3.4. Postpartum health outcomes
The most reported postpartum conditions were low back/pelvic girdle pain (23.3%) and diastasis recti abdominus (23.2%) (Table 4).
Table 4.
Postpartum health outcomes.
| System | Condition | No amenorrhea (n = 752) |
Secondary amenorrhea (n = 210) | REDs (n = 63) |
Total (n = 1025) |
|---|---|---|---|---|---|
| Mental health | |||||
| Postpartum anxiety | 149 (19.8) | 36 (17.1) | 12 (19.1) | 197 (19.2) | |
| Postpartum depression | 90 (12.0) | 27 (12.9) | 10 (15.9) | 127 (12.4) | |
| Obsessive compulsive disorder | 11 (1.5) | 4 (1.9) | 1 (1.6) | 16 (1.6) | |
| Postpartum psychosis | 2 (0.3) | 2 (1.0) | 0 (0) | 4 (0.4) | |
| Reproductive | |||||
| Pain with sex | 137 (18.2) | 42 (20.0) | 12 (19.1) | 191 (18.6) | |
| Breastfeeding complications | 93 (12.4) | 23 (11.0) | 4 (6.3) | 120 (11.7) | |
| Irregular menstrual cycle | 52 (6.9) | 36 (17.1) | 5 (7.9) | 93 (9.1) | |
| Perimenopause | 7 (0.9) | 5 (2.4) | 0 (0) | 12 (1.2) | |
| Metabolic | Postpartum thyroid dysfunction | 19 (2.5) | 5 (2.4) | 2 (3.2) | 26 (2.5) |
| Urogynecological | |||||
| Stress urinary incontinence | 145 (19.3) | 41 (19.5) | 13 (20.6) | 199 (19.4) | |
| Pelvic organ prolapse | 86 (11.4) | 31 (14.8) | 6 (9.5) | 123 (12.0) | |
| Urgency urinary incontinence | 72 (9.6) | 23 (11.0) | 5 (7.9) | 100 (9.8) | |
| Wind incontinence | 44 (5.9) | 12 (5.7) | 1 (1.6) | 57 (5.6) | |
| Fecal urgency | 28 (3.7) | 13 (6.2) | 2 (3.2) | 43 (4.2) | |
| Anal incontinence | 20 (2.7) | 6 (2.9) | 1 (1.6) | 27 (2.6) | |
| Obstructive defecation | 13 (1.7) | 6 (2.9) | 0 (0) | 19 (1.9) | |
| Musculoskeletal | |||||
| LBP/PGP | 177 (23.5) | 54 (25.7) | 8 (12.7) | 239 (23.3) | |
| Diastasis recti abdominus | 169 (22.5) | 54 (25.7) | 15 (23.8) | 238 (23.2) | |
| Umbilical hernia | 13 (1.7) | 4 (1.9%) | 1 (1.6) | 18 (1.8) | |
| Hematological | |||||
| Iron deficiency | 60 (8.0) | 19 (9.1) | 5 (7.9) | 84 (8.2) | |
| Anemia | 27 (3.6) | 15 (7.1) | 3 (4.8) | 45 (4.4) |
Note: Data are presented as n (%).
Abbreviations: LBP/PGP = low back pain/pelvic girdle pain; REDs = relative energy efficiency in sport.
3.5. Regressions analysis
Participants with a history of REDs had greater odds of premature labor (OR = 3.52, 95%CI: 1.26–9.81) and preterm delivery (OR = 2.62, 95%CI: 1.05–6.58) compared to participants with no history of secondary amenorrhea (Table 5). Additionally, those with a history of REDs were more likely to experience unexplained vaginal bleeding during pregnancy. We were underpowered to identify differences for events that occurred at low frequency in the REDs group (i.e., gestational diabetes, gestational hypertension, obstetric cholestasis) (Table 5). Participants with a history of secondary amenorrhea are more likely to experience anemia during their pregnancy. There was no difference in mode of delivery (p = 0.11) or infant outcomes between groups (Supplementary Tables 2 and 3). Postpartum health outcomes were not different between groups (Table 6).
Table 5.
Pregnancy health outcomes.
| System | Condition | Secondary amenorrhea (n = 210) |
REDs (n = 63) |
||
|---|---|---|---|---|---|
| OR (95%CI) | p | OR (95%CI) | p | ||
| History of pregnancy loss | 1.19 (0.85–1.65) | 0.31 | 1.63 (0.96–2.77) | 0.07 | |
| Fertility treatments used | 1.58 (0.84–2.94) | 0.15 | 1.39 (0.48–4.04) | 0.55 | |
| Mental health | |||||
| Anxiety | 0.92 (0.59–1.42) | 0.70 | 1.21 (0.61–2.39) | 0.59 | |
| Depression | 1.27 (0.68–2.38) | 0.45 | 1.21 (0.42–0.39) | 0.73 | |
| Obstetric | |||||
| Unexplained vaginal bleeding | 1.76 (0.87–3.57) | 0.12 | 3.06 (1.21–7.77) | 0.02 | |
| Twin pregnancy | 1.31 (0.41–4.15) | 0.65 | 1.09 (0.14–8.55) | 0.94 | |
| Placenta previa >28 weeks | – | – | – | – | |
| Incompetent cervix | – | – | – | – | |
| Metabolic | |||||
| Hyperemesis gravidarum | 1.46 (0.77–2.77) | 0.24 | 1.39 (0.48–4.04) | 0.55 | |
| Gestational diabetes | 1.17 (0.60–2.29) | 0.64 | – | – | |
| Preeclampsia | 1.09 (0.46–2.58) | 0.84 | 0.51 (0.07–3.85) | 0.52 | |
| Gestational hypertension | 1.02 (0.41–2.57) | 0.96 | – | – | |
| Thyroid disease | 0.89 (0.33–2.41) | 0.82 | 0.59 (0.08–4.47) | 0.61 | |
| Obstetric cholestasis | 4.85 (1.08–21.83) | 0.04 | – | – | |
| Urogynecological | |||||
| Stress urinary incontinence | 1.54 (0.97–2.43) | 0.07 | 1.40 (0.64–3.05) | 0.40 | |
| Urgency urinary incontinence | 0.83 (0.36–1.92) | 0.66 | 0.79 (0.18–3.38) | 0.75 | |
| Pelvic organ prolapse | 1.25 (0.58–2.71) | 0.57 | – | – | |
| Anal incontinence | – | – | – | – | |
| Musculoskeletal | |||||
| LBP/PGP | 0.94 (0.68–1.30) | 0.71 | 0.97 (0.57–1.66) | 0.93 | |
| Diastasis recti abdominus | 1.23 (0.85–1.78) | 0.27 | 0.78 (0.39–1.58) | 0.49 | |
| Umbilical hernia | 0.65 (0.14–2.95) | 0.57 | 1.09 (0.14–8.55) | 0.94 | |
| Hematological | |||||
| Iron deficiency | 0.80 (0.51–1.26) | 0.51 | 1.07 (0.53–2.16) | 0.86 | |
| Anemia | 2.40 (1.37–4.18) | 0.002 | 1.02 (0.31–3.43) | 0.97 | |
| Other | 1.33 (0.55–3.21) | 0.53 | 3.33 (1.20–9.23) | 0.02 | |
| Delivery | |||||
| Premature labor | 0.99 (0.36–2.71) | 0.99 | 3.52 (1.26–9.81) | 0.02 | |
| Preterm delivery | 1.38 (0.68–2.81) | 0.38 | 2.62 (1.05–6.58) | 0.04 | |
Notes: Data are presented as OR and 95%CI, with the “no amenorrhea” group used as the comparison. Bold values indicate statistical significance.
Abbreviations: 95%CI = 95% confidence interval; LBP/PGP = low back pain/pelvic girdle pain; OR = odds ratio; REDs = relative energy deficiency in sport.
Table 6.
Postpartum health outcomes.
| System | Condition | Secondary amenorrhea (n = 210) |
REDs (n = 63) |
||
|---|---|---|---|---|---|
| OR (95%CI) | p | OR (95%CI) | p | ||
| Mental health | |||||
| Postpartum anxiety | 0.84 (0.56–1.25) | 0.39 | 0.95 (0.50–1.83) | 0.88 | |
| Postpartum depression | 1.09 (0.68–1.72) | 0.73 | 1.39 (0.68–2.82) | 0.37 | |
| Obsessive compulsive disorder | 2.41 (0.67–8.64) | 0.18 | 4.08 (0.81–20.63) | 0.09 | |
| Postpartum psychosis | 3.61 (0.50–25.75) | 0.20 | – | – | |
| Reproductive | |||||
| Pain with sex | 1.12 (0.76–1.65) | 0.56 | 1.06 (0.55–2.03) | 0.87 | |
| Breastfeeding complications | 0.87 (0.54–1.41) | 0.58 | 0.48 (0.17–1.35) | 0.17 | |
| Irregular menstrual cycle | 2.79 (1.76–4.40) | 0.00 | 1.16 (0.45–3.02) | 0.76 | |
| Perimenopause | 2.60 (0.82–8.26) | 0.11 | – | – | |
| Metabolic | Postpartum thyroid dysfunction | 0.94 (0.35–2.55) | 0.91 | 1.26 (0.29–5.56) | 0.76 |
| Urogynecological | |||||
| Stress urinary incontinence | 1.02 (0.69–1.49) | 0.94 | 1.09 (0.58–2.06) | 0.79 | |
| Pelvic organ prolapse | 1.34 (0.86–2.09) | 0.19 | 0.82 (0.34–1.95) | 0.65 | |
| Urgency urinary incontinence | 1.16 (0.71–1.91) | 0.55 | 0.81 (0.32–2.10) | 0.67 | |
| Wind incontinence | 0.98 (0.51–1.88) | 0.94 | 0.26 (0.04–1.92) | 0.19 | |
| Fecal urgency | 1.71 (0.87–3.36) | 0.12 | 0.85 (0.20–3.64) | 0.82 | |
| Anal incontinence | 1.08 (0.43–2.72) | 0.88 | 0.59 (0.08–4.47) | 0.61 | |
| Obstructive defecation | 1.67 (0.63–4.45) | 0.30 | – | – | |
| Musculoskeletal | |||||
| LBP/PGP | 1.12 (0.79–1.60) | 0.51 | 0.47 (0.22–1.01) | 0.05 | |
| Diastasis recti abdominus | 1.19 (0.84–1.70) | 0.33 | 1.08 (0.59–1.97) | 0.81 | |
| Umbilical hernia | 1.10 (0.36–3.42) | 0.86 | 0.92 (0.12–7.12) | 0.93 | |
| Hematological | |||||
| Iron deficiency | 1.15 (0.67–1.97) | 0.62 | 0.99 (0.38–2.57) | 0.99 | |
| Anemia | 2.07 (1.08–3.96) | 0.03 | 1.34 (0.40–4.55) | 0.64 | |
Notes: Data presented as OR and 95%CI, with the “no amenorrhea” group used as the comparison.
Abbreviations: 95%CI = 95% confidence interval; LBP/PGP = low back pain/pelvic girdle pain; OR = odds ratio; REDs = relative energy deficiency in sport.
4. Discussion
These data are the first to link a history of REDs with an increased odds of adverse pregnancy outcomes (i.e., labor and/or delivery before 37 weeks of pregnancy) and unexpected vaginal bleeding compared to those without a history of secondary amenorrhea. These data further suggest that the severity of LEA plays an important role, as menstrual dysfunction without a clinical diagnosis of REDs was not associated with an increased risk of adverse pregnancy outcomes.
The present study demonstrated that those with a history of REDs were more than twice as likely to experience preterm delivery compared to those without a history of secondary amenorrhea. The average global frequency of delivery prior to 37 weeks of pregnancy is 9.9% (ranging from 4%–16% depending on the country in which the study was conducted), and this continues to be a leading cause of infant mortality globally.16, 17, 18 Adverse infant health outcomes resulting from preterm delivery include respiratory distress syndrome (OR = 40.1, 95%CI: 32.0–50.3), respiratory failure (OR = 10.5, 95%CI: 6.9–16.1), heart failure (Hazard ratio = 4.49, 95%CI: 3.86–5.22), and sudden infant death syndrome (RRR = 1.69, 95%CI: 1.61–1.79).19, 20, 21 Infants born prematurely may also experience health complications later in life, such as increased blood pressure mmHg (systolic blood pressure mean difference = 4.2 mmHg, 95%CI: 2.8–5.7; diastolic blood pressure mean difference = 2.6, 95%CI: 1.2–4.0) and kidney disease.22, 23, 24 Adverse maternal health outcomes associated with preterm delivery include cardiovascular disease (RRR = 1.43, 95%CI: 1.18–1.72), stroke (RRR = 1.65, 95%CI: 1.51–1.79), cardiovascular disease death (RRR = 1.78, 95%CI: 1.42–2.21), and postpartum depression (RRR = 1.20, 95%CI: 1.06–1.36).25, 26, 27 Notably, there is a dose–response relationship, with earlier deliveries resulting in more severe and frequent complications for both mother and infant.19,25,28 Given the severity of these conditions, it is critical to address the risk presented by a history of REDs and to assess the risk for each patient in order to reduce mortality and improve health outcomes. Adequate progesterone levels play a role in preventing preterm delivery, and evidence suggests that progesterone supplementation may reduce the risk of preterm delivery.29 REDs is known to acutely reduce progesterone levels, raising questions about whether REDs could increase the susceptibility to complications such as preterm delivery due to prolonged hormonal imbalances.4 This is the first study to suggest a risk of preterm delivery associated with REDs. However, previous studies suggest that preterm delivery may result from a variety of risk factors, including a history of an eating disorder or low body mass index, both of which are common traits in individuals with REDs.30,31 Notably, infants born to mothers with a history of REDs were not more likely to be admitted to the neonatal intensive care unit. Additionally, individuals with a history of REDs were over 3 times more likely to have premature labor compared to those with no amenorrhea. While premature labor does not necessarily lead to delivery, approximately 45% of preterm deliveries are preceded by premature labor, exposing the mother and infant to the risks outlined above.32 Further research to better understand the causal relationships between REDs and premature labor and delivery is essential to determine preventative measures for improving short- and long-term maternal and fetal health outcomes.
Individuals with a history of REDs were more likely to experience unexplained vaginal bleeding during pregnancy compared to those with no history of amenorrhea. While vaginal bleeding during pregnancy can be benign, it can also cause significant psychological stress as it can be a sign of miscarriage.33 A threatened miscarriage causes vaginal bleeding during pregnancy and results from inadequate secretion of progesterone during early pregnancy.34 Given that REDs is known to acutely reduce progesterone and other reproductive hormones, it is possible that there are lasting consequences on reproductive hormones that cause seemingly unexplained vaginal bleeding during pregnancy.4 Furthermore, studies have also shown a relationship between vaginal bleeding during early pregnancy and preterm delivery.35 The findings of the current study provide rationale to further investigate hormonal and other factors that may leave individuals vulnerable to threatened miscarriage and unable to sustain a full-term pregnancy.
Unlike participants with a history of REDs, participants with a history of secondary amenorrhea were not at an increased risk of preterm delivery, premature labor, or unexplained vaginal bleeding. However, they were over 2 times more likely to have anemia during pregnancy. Anemia is estimated to affect over 20% of pregnancies globally and can have significant negative maternal and fetal health outcomes, including preeclampsia (OR = 0.049, 95%CI: 0.006–0.379), preterm delivery (OR = 1.2, 95%CI: 1.1–1.2), and low birth weight (OR = 1.1, 95%CI: 1.1–1.2).36, 37, 38, 39, 40 Interestingly, the whole study population had a low prevalence of anemia (5.6%) compared to rates reported in developed countries.36
4.1. Clinical implications
Clinicians and pregnant people should be aware that those with a history of REDs may be at increased risk for premature labor and preterm delivery and should make decisions and monitor the pregnancy accordingly. Breast feeding is a modifiable factor that is especially critical for the health and development of premature infants.41 Feeding premature infants breastmilk may be able to mitigate some of the health risks resulting from preterm delivery and should be encouraged when possible.41 Further research is critical to understand how the severity and duration of REDs may play a role in adverse pregnancy outcomes. Additionally, research regarding the underlying mechanisms will be important to understand how outcomes such as preterm labor and delivery may be avoided in patients with a history of REDs. Given the findings from this study and existing literature regarding energy availability and fertility, future research should also aim to investigate the potential impact of menstrual dysfunction, LEA, and REDs on infertility and the use of assistive reproductive techniques.42,43
4.2. Strengths and limitations
This study is the first to provide data from an international cohort related to the impact of REDs and secondary amenorrhea on pregnancy and postpartum health outcomes. The questionnaire resulted in 95% of responses being useable. However, the questionnaire was only offered in English, meaning non-English speakers were unable to participate. Data were collected via an online survey, increasing the risk for sampling and recall bias.44,45 Additionally, volunteer bias may have resulted in individuals with a pre-existing interest in exercise and/or energy availability being more likely to participate.46 Presently, awareness and diagnosis of REDs are low, meaning many individuals are likely experiencing, or have experienced, the condition without a diagnosis.47 This makes examining potential effects of the condition difficult. Future research examining the influence of duration or severity of REDs, as well as medical conditions such as polycystic ovary syndrome, would provide a more robust understanding of the relationship between REDs and pregnancy outcomes. Future research should prioritize prospective data collection and assess the spectrum of energy availability, including REDs, LEA, and secondary amenorrhea from preconception to the postpartum period (including fertility and pregnancy loss).
5. Conclusion
These data suggest that a history of REDs increases the risks of premature labor and delivery and unexplained vaginal bleeding during pregnancy, which were not observed with secondary amenorrhea alone. Additionally, infants born to participants with a history of REDs were significantly lighter than those with no history of secondary amenorrhea or a history of secondary amenorrhea. Further research investigating the severity and duration of REDs experienced prior to pregnancy is critical to understand the impact of the condition on pregnancy and postpartum health outcomes.
Authors’ contributions
PATJ contributed to the conception of the study, performed the data analysis, assisted with the statistical analysis, and was the principal writer of the manuscript; MHD contributed to the conception of the study, assisted in the interpretation of the data and statistical analysis, and is the guarantor; EB, SD, and AH contributed to the conception of the study; BAM performed the statistical analysis. All authors contributed to the drafting and revision of the final article. All authors have approved the final version of the manuscript, and agree with the order of presentation of the authors.
Competing interests
The authors declare that they have no competing interests.
Acknowledgments
Data availability statement
Data are available upon reasonable request.
Acknowledgments
MHD is funded by a Christenson Professorship in Active Healthy Living. PATJ is funded by the Health Sciences TD Bank Undergraduate Research Award, this project received support from the FIFA Female Athlete Project. The authors wish to thank Belinda Wilson and Andreas Serner for their critical review of the manuscript.
Footnotes
Peer review under responsibility of Shanghai University of Sport.
Supplementary materials associated with this article can be found in the online version at doi:10.1016/j.jshs.2025.101072.
Supplementary materials
References
- 1.Gimunová M., Paulínyová A., Bernaciková M., Paludo A.C. The prevalence of menstrual cycle disorders in female athletes from different sports disciplines: A rapid review. Int J Environ Res Public Health. 2022;19 doi: 10.3390/ijerph192114243. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Adam M.E.K., Bristow A., Neely K.C., Erlandson M.C. Do women athletes’ experiences of menstrual function and dysfunction vary across competition levels? A mixed methods exploration. Psychol Sport Exerc. 2022;63 doi: 10.1016/j.psychsport.2022.102270. [DOI] [Google Scholar]
- 3.Mountjoy M., Sundgot-Borgen J.K., Burke L.M., et al. IOC consensus statement on relative energy deficiency in sport (RED-S): 2018 update. Br J Sports Med. 2018;52:687–697. doi: 10.1136/bjsports-2018-099193. [DOI] [PubMed] [Google Scholar]
- 4.Mountjoy M., Ackerman K.E., Bailey D.M., et al. 2023 International Olympic Committee's (IOC) consensus statement on relative energy deficiency in sport (REDs) Br J Sports Med. 2023;57:1073–1097. doi: 10.1136/bjsports-2023-106994. [DOI] [PubMed] [Google Scholar]
- 5.Mountjoy M., Sundgot-Borgen J., Burke L., et al. The IOC consensus statement: Beyond the female athlete triad-relative energy deficiency in sport (RED-S) Br J Sports Med. 2014;48:491–497. doi: 10.1136/bjsports-2014-093502. [DOI] [PubMed] [Google Scholar]
- 6.Angelidi A.M., Stefanakis K., Chou S.H., et al. Relative energy deficiency in sport (REDs): Endocrine manifestations, pathophysiology and treatments. Endocr Rev. 2024;45:676–708. doi: 10.1210/endrev/bnae011. [DOI] [PubMed] [Google Scholar]
- 7.Allaway H.C., Southmayd E.A., De Souza M.J. The physiology of functional hypothalamic amenorrhea associated with energy deficiency in exercising women and in women with anorexia nervosa. Horm Mol Biol Clin Investig. 2016;25:91–119. doi: 10.1515/hmbci-2015-0053. [DOI] [PubMed] [Google Scholar]
- 8.Iwasa T., Matsuzaki T., Yano K., et al. Effects of low energy availability on reproductive functions and their underlying neuroendocrine mechanisms. J Clin Med. 2018;7:166. doi: 10.3390/jcm7070166. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Gopalan C., Nadamuni AN. Nutrition and fertility. The Lancet. 1972;300:1077–1079. doi: 10.1016/s0140-6736(72)92355-0. [DOI] [PubMed] [Google Scholar]
- 10.Kauffman A.S., Bojkowska K., Rissman E.F. Critical periods of susceptibility to short-term energy challenge during pregnancy: Impact on fertility and offspring development. Physiol Behav. 2010;99:100–108. doi: 10.1016/j.physbeh.2009.10.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Baer R.J., Bandoli G., Jelliffe-Pawlowski L.L., Rhee K.E., Chambers C.D. Adverse live-born pregnancy outcomes among pregnant people with anorexia nervosa. Am J Obstet Gynecol. 2024;231 doi: 10.1016/j.ajog.2023.11.1242. 248.e1–14. [DOI] [PubMed] [Google Scholar]
- 12.Davenport M.H., Nesdoly A., Ray L., Khurana R., Thornton J., McHugh T.F. “Is it realistic?”: A qualitative study of the experiences of elite women athletes considering parenthood. Sports Med. 2024;54:2411–2421. doi: 10.1007/s40279-024-02019-y. [DOI] [PubMed] [Google Scholar]
- 13.Harris P.A., Taylor R., Minor B.L., et al. The redcap consortium: Building an international community of software platform partners. J Biomed Inform. 2019;95 doi: 10.1016/j.jbi.2019.103208. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Harris P.A., Taylor R., Thielke R., Payne J., Gonzalez N., Conde J.G. Research electronic data capture (REDCap): A metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42:377–381. doi: 10.1016/j.jbi.2008.08.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Eysenbach G. Improving the quality of web surveys: The checklist for reporting results of internet E-surveys (CHERRIES) J Med Internet Res. 2004;6:e34. doi: 10.2196/jmir.6.3.e34. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.World Health Organization. Newborn mortality; 2024. Available at:https://www.who.int/news-room/fact-sheets/detail/newborn-mortality. [accessed 15.10.2024].
- 17.World Health Organization. Preterm birth; 2023. Available at:https://www.who.int/news-room/fact-sheets/detail/preterm-birth/. [accessed 15.10.2024].
- 18.Ohuma E.O., Moller A.B., Bradley E., et al. National, regional, and global estimates of preterm birth in 2020, with trends from 2010: A systematic analysis. The Lancet. 2023;402:1261–1271. doi: 10.1016/S0140-6736(23)00878-4. [DOI] [PubMed] [Google Scholar]
- 19.Consortium on Safe Labor. Hibbard J.U., Wilkins I., Sun L., et al. Respiratory morbidity in late preterm births. JAMA. 2010;304:419–425. doi: 10.1001/jama.2010.1015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Crump C., Groves A., Sundquist J., Sundquist K. Association of preterm birth with long-term risk of heart failure into adulthood. JAMA Pediatr. 2021;175:689–697. doi: 10.1001/jamapediatrics.2021.0131. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Hakeem G.F., Oddy L., Holcroft C.A., Abenhaim H.A. Incidence and determinants of sudden infant death syndrome: A population-based study on 37 million births. World J Pediatr. 2015;11:41–47. doi: 10.1007/s12519-014-0530-9. [DOI] [PubMed] [Google Scholar]
- 22.Parkinson J.R., Hyde M.J., Gale C., Santhakumaran S., Modi N. Preterm birth and the metabolic syndrome in adult life: A systematic review and meta-analysis. Pediatrics. 2013;131:e1240–e1263. doi: 10.1542/peds.2012-2177. [DOI] [PubMed] [Google Scholar]
- 23.Luyckx V.A., Brenner B.M. Birth weight, malnutrition and kidney-associated outcomes: A global concern. Nat Rev Nephrol. 2015;11:135–149. doi: 10.1038/nrneph.2014.251. [DOI] [PubMed] [Google Scholar]
- 24.de Jong F., Monuteaux M.C., van Elburg R.M., Gillman M.W., Belfort M.B. Systematic review and meta-analysis of preterm birth and later systolic blood pressure. Hypertension. 2012;59:226–234. doi: 10.1161/HYPERTENSIONAHA.111.181784. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Wu P., Gulati M., Kwok C.S., et al. Preterm delivery and future risk of maternal cardiovascular disease: A systematic review and meta-analysis. J Am Heart Assoc. 2018;7 doi: 10.1161/JAHA.117.007809. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Silverman M.E., Reichenberg A., Savitz D.A., et al. The risk factors for postpartum depression: A population-based study. Depress Anxiety. 2017;34:178–187. doi: 10.1002/da.22597. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Tanz L.J., Stuart J.J., Williams P.L., et al. Preterm delivery and maternal cardiovascular disease in young and middle-aged adult women. Circulation. 2017;135:578–589. doi: 10.1161/CIRCULATIONAHA.116.025954. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Manuck T.A., Rice M.M., Bailit J.L., et al. Preterm neonatal morbidity and mortality by gestational age: A contemporary cohort. Am J Obstet Gynecol. 2016;215 doi: 10.1016/j.ajog.2016.01.004. 103.e1–14. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Jain V., McDonald S.D., Mundle W.R., Farine D. Guideline No. 398: Progesterone for prevention of spontaneous preterm birth. J Obstet Gynaecol Can. 2020;42:806–812. doi: 10.1016/j.jogc.2019.04.012. [DOI] [PubMed] [Google Scholar]
- 30.Meah V.L., Davies G.A., Davenport M.H. Why can’t I exercise during pregnancy? Time to revisit medical “absolute” and “relative” contraindications: Systematic review of evidence of harm and a call to action. Br J Sports Med. 2020;54:1395–1404. doi: 10.1136/bjsports-2020-102042. [DOI] [PubMed] [Google Scholar]
- 31.National Institute of Health . U.S. Department of Health and Human Services; Washington, DC: 2023. What are the risk factors for preterm labor and birth? [Google Scholar]
- 32.Goldenberg R.L., Culhane J.F., Iams J.D., Romero R. Epidemiology and causes of preterm birth. The Lancet. 2008;371:75–84. doi: 10.1016/S0140-6736(08)60074-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Hasan R., Baird D.D., Herring A.H., Olshan A.F., Jonsson Funk M.L., Hartmann K.E. Association between first-trimester vaginal bleeding and miscarriage. Obstet Gynecol. 2009;114:860–867. doi: 10.1097/AOG.0b013e3181b79796. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Wahabi H.A., Fayed A.A., Esmaeil S.A., Bahkali K.H. Progestogen for treating threatened miscarriage. Cochrane Database Syst Rev. 2018;8 doi: 10.1002/14651858.CD005943.pub5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Lykke J.A., Dideriksen K.L., Lidegaard Ø., Langhoff-Roos J. First-trimester vaginal bleeding and complications later in pregnancy. Obstet Gynecol. 2010;115:935–944. doi: 10.1097/AOG.0b013e3181da8d38. [DOI] [PubMed] [Google Scholar]
- 36.Goonewardene M., Shehata M., Hamad A. Anaemia in pregnancy. Best Pract Res Clin Obstet Gynaecol. 2012;26:3–24. doi: 10.1016/j.bpobgyn.2011.10.010. [DOI] [PubMed] [Google Scholar]
- 37.Levy A., Fraser D., Katz M., Mazor M., Sheiner E. Maternal anemia during pregnancy is an independent risk factor for low birthweight and preterm delivery. Eur J Obstet Gynecol Reprod Biol. 2005;122:182–186. doi: 10.1016/j.ejogrb.2005.02.015. [DOI] [PubMed] [Google Scholar]
- 38.Lin L., Wei Y., Zhu W., et al. Prevalence, risk factors and associated adverse pregnancy outcomes of anaemia in chinese pregnant women: A multicentre retrospective study. BMC Pregnancy Childbirth. 2018;18:111. doi: 10.1186/s12884-018-1739-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Smith C., Teng F., Branch E., Chu S., Joseph K.S. Maternal and perinatal morbidity and mortality associated with anemia in pregnancy. Obstet Gynecol. 2019;134:1234–1244. doi: 10.1097/AOG.0000000000003557. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Johnson A., Vaithilingan S., Avudaiappan S.L. The interplay of hypertension and anemia on pregnancy outcomes. Cureus. 2023;15 doi: 10.7759/cureus.46390. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Morniroli D., Tiraferri V., Maiocco G., et al. Beyond survival: The lasting effects of premature birth. Front Pediatr. 2023;11 doi: 10.3389/fped.2023.1213243. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Zanker C.L. Regulation of reproductive function in athletic women: An investigation of the roles of energy availability and body composition. Br J Sports Med. 2006;40:489–490. doi: 10.1136/bjsm.2004.016758. discussion 490. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Sadhir S., Pontzer H. Impact of energy availability and physical activity on variation in fertility across human populations. J Physiol Anthropol. 2023;42:1. doi: 10.1186/s40101-023-00318-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Van Selm M., Jankowski N.W. Conducting online surveys. Qual Quant. 2006;40:435–456. [Google Scholar]
- 45.Althubaiti A. Information bias in health research: Definition, pitfalls, and adjustment methods. J Multidiscip Healthc. 2016;9:211–217. doi: 10.2147/JMDH.S104807. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Lewandowski E., Specht H. Influence of volunteer and project characteristics on data quality of biological surveys. Conserv Biol. 2015;29:713–723. doi: 10.1111/cobi.12481. [DOI] [PubMed] [Google Scholar]
- 47.Cabre H.E., Moore S.R., Smith-Ryan A.E., Hackney A.C. Relative energy deficiency in sport (RED-S): Scientific, clinical, and practical implications for the female athlete. Dtsch Z Sportmed. 2022;73:225–234. doi: 10.5960/dzsm.2022.546. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
Data are available upon reasonable request.