PLoS ONE plos plosone PLOS ONE 1932-6203 Public Library of Science San Francisco, CA USA 10.1371/journal.pone.0255248 PONE-D-21-04875 Research Article Medicine and health sciencesWomen's healthMaternal healthPregnancy Medicine and health sciencesWomen's healthObstetrics and gynecologyPregnancy Medicine and health sciencesPublic and occupational healthPhysical activityPhysical fitness Biology and life sciencesPhysiologyPhysiological parametersBody weight Biology and life sciencesPhysiologyPhysiological parametersBody weightWeight gain Medicine and health sciencesWomen's healthMaternal healthBreast feeding Medicine and health sciencesPediatricsNeonatologyBreast feeding Medicine and health sciencesWomen's healthMaternal healthBirthLabor and delivery Medicine and health sciencesWomen's healthObstetrics and gynecologyBirthLabor and delivery Medicine and health sciencesEpidemiologyMedical risk factors Medicine and health sciencesWomen's healthObstetrics and gynecology The effect of pregnancy and the duration of postpartum convalescence on the physical fitness of healthy women: A cohort study of active duty servicewomen receiving 6 weeks versus 12 weeks convalescence The effect of extended postpartum convalescence in active duty soldiers DeGroot David W. Conceptualization Data curation Formal analysis Investigation Methodology Project administration Supervision Writing – original draft Writing – review & editing 1 https://orcid.org/0000-0001-5528-2525 Sitler Collin A. Data curation Formal analysis Investigation Methodology Writing – review & editing 2 Lustik Michael B. Data curation Formal analysis Investigation Validation Visualization Writing – review & editing 3 Langan Kelly L. Conceptualization Data curation Investigation Writing – review & editing 4 ‡ Hauret Keith G. Data curation Investigation Methodology Writing – review & editing 5 ‡ Gotschall Michael H. Data curation Investigation 6 ‡ https://orcid.org/0000-0001-5971-2385 Gehrich Alan P. Conceptualization Data curation Formal analysis Investigation Methodology Project administration Supervision Writing – original draft Writing – review & editing 7 * Fort Benning Heat Center, Martin Army Community Hospital, Fort Benning, Georgia, United States of America Department of Obstetrics and Gynecology, Walter Reed National Military Medical Center, Bethesda, Maryland, United States of America Department of Clinical Investigation, Tripler Army Medical Center, Honolulu, Hawaii, United States of America Department of Obstetrics and Gynecology, Madigan Army Medical Center, Joint Base Lewis-McChord, Washington, United States of America Army Public Health Center, Aberdeen Proving Ground, Maryland, United States of America Department of Pediatrics, Tripler Army Medical Center, Honolulu, Hawaii, United States of America Department of Obstetrics and Gynecology, Tripler Army Medical Center, Honolulu, Hawaii, United States of America Laganà Antonio Simone Editor University of Insubria, ITALY

No authors have competing interests.

‡ These authors also contributed equally to this work.

 * E-mail: apgurogyn@gmail.com 28 7 2021 2021 16 7 e0255248 12 2 2021 3 7 2021 This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication. Introduction

Pregnancy profoundly affects cardiovascular and musculoskeletal performance requiring up to 12 months for recovery in healthy individuals.

 Objective

To assess the effects of extending postpartum convalescence from 6 to 12 weeks on the physical fitness of Active Duty (AD) soldiers as measured by the Army Physical Fitness Test (APFT) and Body Mass Index (BMI).

 Methods

We conducted a retrospective study of AD soldiers who delivered their singleton pregnancy of ≥ 32weeks gestation at a tertiary medical center. Pre- and post-pregnancy APFT results as well as demographic, pregnancy, and postpartum data were collected. Changes in APFT raw scores, body composition measures, and failure rates across the 6-week and 12-week convalescent cohorts were assessed. Multivariable regressions were utilized to associate risk factors with failure.

 Results

Four hundred sixty women met inclusion criteria; N = 358 in the 6 week cohort and N = 102 in the 12 week cohort. Demographic variables were similar between the cohorts. APFT failure rates across pregnancy increased more than 3-fold in both groups, but no significant differences were found between groups in the decrement of performance or weight gain. With the combined cohort, multivariable regression analysis showed failure on the postpartum APFT to be independently associated with failure on the pre-pregnancy APFT (OR = 16.92, 95% CI 4.96–57.77), failure on pre-pregnancy BMI (OR = 8.44, 95% CI 2.23–31.92), elevated BMI at 6–8 weeks postpartum (OR = 4.02, 95% CI 1.42–11.35) and not breastfeeding at 2 months (OR = 3.23, 95% CI 1.48–7.02). Within 36 months of delivery date, 75% of women had achieved pre-pregnancy levels of fitness.

 Conclusion

An additional 6 weeks of convalescence did not adversely affect physical performance or BMI measures in AD Army women following pregnancy. Modifiable factors such as pre- and post-pregnancy conditioning and weight, weight gain in pregnancy and always breastfeeding were found to be significant in recovery of physical fitness postpartum.

 The author(s) received no funding for this work. Data Availability All relevant data are within the manuscript and its Supporting information Files. Introduction

Pregnancy has a profound impact on physical fitness. The physiologic adaptation of pregnancy on the cardiac, pulmonary, renal and musculoskeletal systems has been extensively studied and defined. These changes, in addition to the gestational weight gain and concern for fetal well-being, limit the amount and intensity of exercise that women undertake during pregnancy [1]. Delivery does not allow for rapid return to peak performance levels, as physiologic changes can persist for greater than 1 year after delivery [2]. Even healthy individuals with uncomplicated pregnancies can experience prolonged decrements in physical fitness as compared to their non-pregnant counterparts [3]. The direct impact of pregnancy on physical conditioning is challenging to measure due not only to the difficulty identifying a cohort of women with adequate physical fitness data both before and after pregnancy, but also to the multiple factors beyond the physical that play a role in a woman’s recovery from pregnancy. Survey studies and focus groups have identified multiple barriers to postpartum exercise, including limited time, lack of childcare, financial cost of gym memberships and equipment, fatigue, negative self-image, and poor social support [4–6]. These emotional, psychosocial and economic factors are more nuanced but likely as impactful as the physical changes of pregnancy. Full time Active Duty (AD) women who become pregnant while serving in the military provide a cohort in whom some of these challenges to study design are overcome through incentives, established physical fitness standards, regular standardized fitness testing and paid maternity leave. Data from this cohort may provide a more accurate assessment of the impact of pregnancy and delivery on physical fitness, and the length of time it takes for women to recover their fitness postpartum.

The US Army requires all soldiers to maintain physical fitness. Every six months the fitness level of an individual soldier is measured utilizing the Army Physical Fitness Test (APFT); in conjunction with an assessment of body composition. The APFT consists of three events: the push-up, the sit-up and the 2 mile run [7]. These events test the muscular and aerobic endurance of the soldier. Body composition is screened by measuring the soldiers’ height and weight [8]. The soldier who has failed an APFT or does not meet body composition standards is placed into a training program to improve her physical conditioning [9]. While in this status, soldiers cannot attend schooling or be promoted. Recurrent failures lead to separation from the military.

A high percentage of women become pregnant during their time on active duty. Data from the Armed Forces Health Surveillance Branch shows that approximately 13% of service women of child-bearing potential have a pregnancy-related event each year which, in the US Army, equates to 12,000 service women [10]. All AD women are given 6 months following delivery to prepare to undergo an APFT for record in conjunction with body composition assessment [7]. To prepare for this assessment, pregnant AD women are given dedicated time to engage in modified fitness training during pregnancy. After completing their postpartum convalescence and receiving medical clearance, they return to organized fitness training with their units. In February 2016, the US Army implemented a postpartum convalescent leave policy which extended postpartum leave from 6 to 12 weeks [11]. Previously, all AD soldiers had returned to formal physical fitness training, pending medical clearance, 6 weeks after delivery. Following implementation of the revised policy, all women were granted 12 weeks of postpartum convalescence. Regardless of the duration of leave afforded them, both cohorts of women were required to be prepared for the APFT six months after delivery. The question arose whether the duration of postpartum convalescence impacts soldier readiness.

The purpose of this study was to examine the effects of the extended convalescent leave policy on the service woman’s physical fitness and body composition. We hypothesized that women in the 12 week convalescent leave group would have lower APFT scores and worse body composition measures postpartum compared to women in the 6 week convalescent leave group. Secondarily, we sought to evaluate the effects of pregnancy on the performance of individual APFT events. Additionally we sought to elucidate risk factors before, during and after pregnancy, that may limit a woman’s ability to regain her physical fitness. Lastly, we sought to determine the time necessary for an AD soldier to regain her pre-pregnancy level of physical fitness after delivery.

 Methods Army physical fitness test

As described in the Introduction, the APFT consists of three individual events. The push-up event assesses the muscular endurance of the chest and upper arm musculature. Rest during the event is only permitted with arms completely extended. Resting on the ground with any part of the body other than hands or feet results in event termination. The sit-up event assesses the muscular endurance of the core and hip flexor muscles. The sit-up is performed with knees bent, hands clasped behind the head and with another soldier holding the feet down. Rest is only permitted when the spine is perpendicular to the ground. The soldier is not permitted to unclasp her hands from behind her head. These first two events primarily measure muscular endurance, and the score is based on the maximum number of reps performed in two minutes [12]. The 2-mile run is a timed event and measures aerobic fitness. Walking is permitted, but discouraged, and the soldier must complete the run without assistance. Research has reported correlation coefficients of 0.70–0.90 comparing the 2-mile run to a treadmill incremental maximal oxygen uptake test [12]. Each of these events is scored according to age and sex-adjusted standards, whereby more repetitions (push-ups, sit-ups) and faster time (2-mile run) results in a higher score [9]. Failure on any one event, e.g., failure to perform the minimum number of push-up or sit-up repetitions or 2-mile run time greater than the maximum allowable time, is recorded as a failure for the entire APFT. During the APFT, a soldier’s BMI is assessed using height and weight measurements. If a soldier fails to meet the screening standard, percent body fat is estimated using circumferential measures of the neck, hip and waist. These results are compared to age and sex-adjusted standards, and maximum allowable weight varies, based on sex, height and age [8].

 Data collection

Data for this retrospective cohort study were obtained from three independent sources. APFT data was retrieved from a centralized repository within the US Army Digital Training Management System. The APFT data, including raw and adjusted scores as well as the soldier’s height and weight is entered into the DTMS system by the soldier’s unit following an APFT. This record allows for comparison of APFT results across an extended time frame before and after pregnancy. Compliance with APFT and body composition standards was assessed according to US Army standards [8, 13]. Select pre-pregnancy, antepartum, intrapartum and postpartum data were collected from the inpatient and outpatient electronic medical records (EMR). The de-identified APFT and pregnancy data were compiled in a Microsoft Excel spreadsheet for analysis. The protocol was approved by the Regional Health Command–Pacific Institutional Review Board, which waived the requirement to obtain informed consent. The study was conducted in accordance with federal regulations for the protection of human research volunteers.

 Subjects

All subjects were AD Army women giving birth at a single tertiary Army medical center with a Level 3 neonatal intensive care unit. The study included all women who had delivered their first or second singleton pregnancy of ≥ 32weeks gestation between 1 January 2011 and 31 March 2017. Women delivering their third or greater child, or who had a medical condition preventing them from completing the APFT were excluded. A roster of eligible women was generated by the medical center clinical bioinformatics office in November 2017. This roster was then used to extract the appropriate APFT and height/weight data from DTMS, in January 2018. The pre-pregnancy APFT must have been completed within 15 months of the new obstetric registration appointment, and the first postpartum APFT within 15 months of the delivery date. Subjects meeting inclusion criteria were dichotomized into 6- and 12-week convalescent leave groups based on the delivery date.

Demographic and descriptive data included age at time of delivery, race, military rank, marital status and pre-pregnancy height, weight and BMI. Individual patient data were extracted from the electronic medical records from January 2018 through March 2019. Individual Department of Defense Identification numbers were used to link the data from each source; once the master file was compiled, source files were deleted and personal identifiers in the master file were replaced with unique numerical identifiers to preserve anonymity. Obstetric data included gestation age at delivery, weight gain during pregnancy, antepartum complications as well as mode and complications of delivery. The weight at the obstetric registration appointment at 6–8 weeks gestation was used as the baseline pregnancy weight. Weight gain was evaluated according to the Institute of Medicine (IOM) Guidelines for Weight Gain during pregnancy [14]. As these guidelines are based on the body mass index (BMI), height and weight data were used to calculate BMI, which was used for all subsequent analyses. Breastfeeding rates were assessed using the documentation in the neonatal outpatient EMR. Analysis of APFT data was conducted using raw scores (sit-up and push-up reps, and run time) [13]. Scaled scores were used to determine failure rates on the APFT. The primary outcomes were APFT raw scores and BMI measures across the 6-week and 12-week convalescent leave cohorts. The secondary outcomes were the failure rates on both the APFT events and BMI measurements.

 Statistics

Standard descriptive statistics were used to characterize the cohorts overall and to compare the two convalescent leave groups. Continuous variables are summarized as mean (standard deviation) or median (interquartile range), and also categorized for presentation. Based on sample sizes for the two leave groups and letting alpha = 0.05, a post hoc power analysis showed that the study had 80% power to detect a 5% difference in mean postpartum APFT total scores.

Chi-square tests and Fisher’s exact tests were used to assess associations between categorical variables, and unpaired t-tests and nonparametric Wilcoxon rank sum tests were used to evaluate differences between leave groups for continuous variables. Paired t-tests were used for unadjusted analyses to compare postpartum APFT scores with pre-pregnancy levels and McNemar’s tests were used for unadjusted analyses to compare failure rates between pre-pregnancy and postpartum APFTs. Analysis of covariance was used for analyses of postpartum APFT scores adjusted for pre-pregnancy scores, and multivariable logistic regression was used for adjusted analyses of postpartum failure rates. A stepwise approach was used to develop adjusted models, with a p<0.10 criterion to enter and p<0.05 to remove. Demographic factors, obstetric data, BMI, and weight gain during pregnancy were eligible to be included in the models. Age was included in the final model regardless of significance. The majority of variables had no missing data or 1 or 2 records with missing data. BMI at six to eight weeks postpartum was missing for 19 women, marital status was missing for 34, breast feeding status at two months was missing for 60, and BMI measures at the time of APFT was missing for 173 women pre-pregnancy and 166 women postpartum. Because excluding records with missing data may lead to biased results, we used the SAS MI procedure to conduct Markov Chain Monte Carlo multiple imputation to impute 20 data sets with complete data. Logistic regression analyses were subsequently performed on each of the 20 imputed data sets, and parameter estimates were combined using SAS MIanalyze.

Linear repeated measures mixed effects models were used to evaluate changes in mean APFT scores over time, with time as a fixed effect and patient as a random effect. Kaplan-Meier curves were generated to assess time to attain pre-pregnancy fitness levels, treating data as censored if the soldier failed to achieve pre-pregnancy levels by the time of her last recorded APFT. All analyses were conducted using SAS statistical software version 9.4 (SAS Institute, Cary, NC).

 Results Demographics

A total of 2103 AD Army women who met initial inclusion criteria delivered singleton pregnancies at Tripler Army Medical Center between 1 January 2011 and 31 March 2017. We identified 460 who met inclusion criteria and had recorded pre pregnancy and postpartum APFT data available for analysis (Fig 1). Eighty percent of the subjects delivered before the new postpartum leave policy had been implemented. Distributions of age, rank and race were similar between the two leave policy groups (Table 1). Ages ranged from 19 to 42 years, with a mean of 25.8 years (4.7) for the 6-week group and 25.8 years (4.2) for the 12-week group. Approximately 3 of 4 women were enlisted soldiers. Unmarried soldiers comprised 22% of the cohort. Approximately four-fifths of deliveries were primiparous, and 22% of deliveries were by cesarean. The BMI distribution was slightly different among the two cohorts. The elapsed time between delivery and the first postpartum APFT was 25 days shorter in the 12-week convalescent cohort. This cohort also had higher breastfeeding rates at 2 month postpartum. The remaining demographic, social, and pregnancy variables were not different between cohorts. All data collected for this research is contained in the S1 Table.

10.1371/journal.pone.0255248.g001 Selection of study participants.

APFT, Army Physical Fitness Test. * Inclusion criteria are U.S. Army Servicewomen; delivery of pregnancy at Tripler Army Medical Center; delivery between January 1, 2011 and March 31, 2017; and gestational age at delivery greater than or equal to 32 completed weeks. # Exclusion criteria are duplicate record; multiple gestation; parity of three or more. ## Incomplete APFT record included last pre-pregnancy APFT more than 15 months before new obstetric appointment or record of 1st postpartum APFT more than 15 months after delivery in the Digital Training Management System.

 10.1371/journal.pone.0255248.t001 Demographic and pregnancy characteristics.
Characteristics All 6-week leave policy 12-week leave policy p-value
(n = 460) (n = 358) (n = 102)
N (%) N (%) N (%)
Age (years) 0.695
 19–24 216 (47) 170 (47) 46 (45)
  25–30 169 (37) 128 (36) 41 (40)
  31–42 75 (16) 60 (17) 15 (15)
  mean ± std 25.8±4.6 25.8±4.7 25.8±4.2 0.949
Race 0.477
  White 176 (38) 133 (37) 43 (42)
  Black 120 (26) 93 (26) 27 (36)
  Asian/Pacific Islander 57 (12) 43 (12) 14 (14)
  Other 107 (23) 89 (25) 18 (18)
Rank 0.431
  Enlisted 350 (76) 269 (75) 81 (79)
  Officer 110 (24) 89 (25) 21 (21)
Marital Status 0.109
  Single 93 (22) 80 (24) 13 (15)
  Married 333 (78) 259 (76) 74 (85)
Tobacco use 0.308
  Never 388 (84) 297 (83) 91 (89)
  Former 65 (14) 55 (15) 10 (10)
  Current 7 (2) 6 (2) 1 (1)
Parity 0.494
  1 363 (79) 285 (80) 78 (76)
  2 97 (21) 73 (20) 24 (24)
BMI at initial OB visit (kg/m2) 0.006
  <25 271 (59) 220 (61) 51 (50)
  25-<30 164 (36) 115 (32) 49 (48)
  30-<35 25 (5) 23 (6) 2 (2)
  mean ±std 24.5±3.1 24.4±3.2 24.9±2.7 0.100
BMI at 6–8 weeks postpartum 0.103
  <25 176 (40) 147 (42) 29 (31)
  25-<30 200 (45) 149 (43) 51 (54)
  ≥30 65 (15) 51 (15) 14 (15)
  Mean 26.2±3.7 26.1±3.8 26.8±3.4 0.103
Weight gain (lbs.)
  mean ± std 32.9±13.8 32.9±14.2 32.8±12.2 0.937
Weight gain per IOM guidelines 0.694
  Adequate 150 (33) 120 (34) 30 (29)
  Excessive 226 (49) 174 (49) 52 (51)
  Insufficient 82 (18) 62 (17) 20 (20)
Mode of delivery 0.586
  SVB 339 (74) 261 (73) 78 (76)
  Cesarean 102 (22) 83 (23) 19 (19)
  Operative Vaginal 19 (4) 14 (4) 5 (5)
Gestational age at delivery (weeks) 0.197
  30–36 29 (6) 24 (7) 5 (5)
  37–38 108 (23) 76 (21) 32 (31)
  39–40 269 (58) 215 (60) 54 (53)
  41 54 (12) 43 (12) 11 (11)
median (IQR) 39.6 (38.7–40.3) 39.7 (38.7–40.4) 39.4 (38.4–40.1) 0.135
Fetal weight (grams) 0.911
  <2500 17 (4) 13 (4) 4 (4)
  2500–3999 406 (88) 315 (88) 91 (89)
  4000+ 36 (8) 29 (8) 7 (7)
 mean ± std 3320±460 3320±463 3323±451 0.952
Breast feeding at 2 months 0.030
  Always 204 (51) 146 (47) 58 (63)
  Sometimes 80 (20) 67 (22) 13 (14)
  Never 116 (29) 95 (31) 21 (23)
Pregnancy Comorbidities
Shoulder dystocia 8 (2) 8 (2) 0 (0) 0.209
Gestational Diabetes 15 (3) 14 (4) 1 (1) 0.209
Hypertensive Diseases of Pregnancy 57 (12) 42 (12) 15 (15) 0.400
Blood transfusion 6 (1) 4 (1) 1 (1) >0.999
EBL ≥ 1000 (ml) 7 (2) 6 (2) 0 (0) 0.346
≥ 3rd degree laceration 13 (3) 9 (3) 4 (4) 0.497
APGAR 1 minute <6 23 (5) 22 (6) 1 (1) 0.037
APGAR 5 minute <6 6 (1) 6 (2) 0 (0) 0.346
Any complication 111 (24) 89 (25) 21 (21) 0.431
Months from delivery to APFT 0.088
  2–5 50 (11) 36 (10) 14 (14)
 6–8 242 (53) 182 (51) 60 (59)
 9–12 126 (27) 102 (29) 24 (24)
 13–15 42 (9) 38 (11) 4 (4)
 median (IQR) 8.0 (6.9–10.3) 8.2 (7.0–10.9) 7.7 (6.7–9.4) 0.007

Data are n (%), mean ± std, or median (IQR).

BMI, Body Mass Index; lbs., pounds; IOM, Institute of Medicine; EBL, estimated blood loss; SVB, spontaneous vaginal birth; IQR, interquartile range.

 Comparison of physical performances across 6-week and 12-week cohort

Both the 6-week and 12-week leave policy cohorts experienced a significant decrement in performance at the first APFT postpartum (APFTPOST) compared to results on their last APFT prior to delivery (APFTPRE) for each APFT event and in overall performance. The decrement of performance across push-ups, sit-ups and run events was equivalent between the two convalescent leave groups (Table 2). Failure rates for the APFT increased from 3.3% pre-pregnancy to 12.4% postpartum for the 6-week leave policy group and from 3.9% to 13.6% for the 12-week leave policy group, (p<0.001 for both), with no difference in the increase in failure rates between leave groups. As a combined cohort, all events and combined scores document significant decrements between APFTPRE and APFTPOST (Table 3). Analysis of failure rates across combined cohort showed significant increases for sit-ups and the 2-mile run but not for push-ups (Fig 2).

10.1371/journal.pone.0255248.g002 Army Physical Fitness Test (APFT) and body composition failure rates.

* P<0.01 vs pre-pregnancy.

 10.1371/journal.pone.0255248.t002 Comparison in each APFT measure across pregnancy between 6-week and 12-week cohorts.
APFT Event 6-Week Leave Group (n = 358) 12-Week Leave Group (n = 102)
Change from pre-pregnancy Absolute scores Change from pre-pregnancy Absolute scores
Push-ups (reps) -4.4 ± 11.0 36.3 ± 11.9 -3.6 ± 8.8 35.5 ± 10.9
Sit-ups (reps) -7.0 ± 11.9 62.2 ± 12.8 -6.9 ± 11.9 61.5 ± 13.2
2-mile run (min) 0.86 ± 1.63 18.0 ± 2.0 0.93 ± 1.62 18.2 ± 1.7
Overall APFT score* -17.6 ± 32.9 240 ± 40 -19.5 ± 31.4 234 ± 38
Weight (lbs.)† 5.3 ± 12.8 147 ± 23.5 5.5 ± 10.9 148 ± 21.6

APFT, Army Physical Fitness Test.

Data are mean ± SD.

No APFT events were significantly different across pregnancy between cohorts (p <.05).

* Raw scores of individual APFT events (sit-ups, push-ups, and 2-mile run) are assigned a point value based on age and sex. The overall APFT score is the total point summation of the individual events, and a passing score is 180 points or greater.

† Weight change was not recorded for all subjects; n = 172 and n = 34 for 6-week leave group and 12-week leave group, respectively.

 10.1371/journal.pone.0255248.t003 Raw APFT score and weight comparison before and after pregnancy for combined cohort.
APFT Event Pre-Pregnancy Results (n = 460) Post-Pregnancy Results (n = 460)
Push-ups (reps) 40.3 ± 11.6 36.1 ± 11.7
Sit-ups (reps) 69.0 ± 11.8 62.0 ± 12.9
2-mile run (min) 17.1 ± 1.6 18.0 ± 1.9
Overall APFT score * 257 ± 30 239 ± 39
Weight (kg) † 141.9 ± 21.4 147.2 ± 23.7

APFT, Army Physical Fitness Test.

Data are mean ± SD.

All post-pregnancy APFT events were significantly different vs pre-pregnancy (p <.001).

* Raw scores of individual APFT events (sit-ups, push-ups, and 2-mile run) are assigned a point value based on age and sex. The overall APFT score is the total point summation of the individual events, and a passing score is 180 points or greater.

† Weight was not recorded for all subjects; n = 206 for women with both pre- and post-pregnancy weight.

 Analysis of APFT changes across the combined 6-week and 12-week cohorts

Mean APFT raw scores postpartum for each event and overall composite scores did not differ between leave groups (Table 2). Models adjusted for parity, age, BMI at new OB appointment, and pre-pregnancy APFT score showed no differences between leave groups. As no significant difference in postpartum performance was found between the 6-week and 12-week cohorts, risk factor analysis was performed on the combined data. Unadjusted analyses examining risk factors for failure on the APFT show significant effects of demographic, social, pre-pregnancy conditioning and weight factors, but did not show any pregnancy related factors to be significant. Breastfeeding at 2 months was also significantly associated with fewer failures on the APFT. Time to APFTPOST was dichotomized as <9 months vs. ≥9 months after delivery and was not associated with postpartum performance on the APFT (Table 4). Multivariable logistic regression analysis showed that failure on APFTPOST was strongly associated with failure on APFTPRE, failure on pre-pregnancy BMI measurements, elevated BMI at 6 to 8-weeks postpartum, and never breastfeeding (Table 5).

10.1371/journal.pone.0255248.t004 Risk factors for failure on APFT and BMI compliance.
Postpartum APFT Postpartum BMI
Risk Factors for Failure on Postpartum APFT PASS N (%) FAIL N (%) P-value PASS N (%) FAIL N (%) P-value
Social/Demographic Factors
Age (years) 0.036 0.080
  19–24 182 (84) 34 (16) 111 (85) 19 (15)
  25–30 152 (90) 17 (10) 103 (93) 8 (7)
  ≥ 31 71 (95) 4 (5) 50 (94) 3 (6)
Race 0.051 0.079
  White 160 (91) 16 (9) 109 (94) 7 (6)
  Black 103 (86) 17 (14) 54 (84) 10 (16)
  Asian/Pacific Islander 54 (95) 3 (5) 36 (95) 2 (5)
  Other 88 (82) 19 (18) 65 (86) 11 (14)
Rank 0.017 0.005
  Officer 104 (95) 6 (5) 82 (98) 2 (2)
  Enlisted 301 (86) 49 (14) 182 (87) 28 (13)
Marital status 0.039 0.448
  Single/divorced 77 (83) 16 (17) 47 (87) 7 (13)
  Married 302 (91) 31 (9) 195 (91) 20 (9)
Tobacco use 0.111 0.065
  Never 346 (89) 42 (11) 224 (91) 21 (9)
  Former/current 59 (82) 13 (18) 40 (82) 9 (18)
Pre-pregnancy Conditioning
APFT pre-pregnancy <0.001 0.053
  Passed 400 (90) 45 (10) 258 (91) 27 (9)
  Failed 5 (33) 10 (67) 6 (67) 3 (33)
BMI standards (kg/m2) 0.001 0.001
  Passed 247 (90) 28 (10) (90) 19 (10)
  Failed 6 (50) 6 (50) 4 (44) 5 (56)
Weight Factors
Pre-pregnancy BMI 0.019 <0.001
  Pre-pregnancy BMI ≥ 25 158 (84) 31 (16) 104 (82) 23 (18)
  Pre-pregnancy BMI < 25 247 (91) 24 (9) 160 (96) 7 (4)
Weight gain per IOM guidelines 0.196 0.004
  Within or below guidelines 209 (90) 23 (10) 136 (95) 7 (5)
  Weight gain above guidelines 194 (86) 32 (14) 126 (85) 23 (15)
BMI 6 to 8 weeks postpartum 0.003 <0.001
  BMI ≥ 30 52 (80) 13 (20) 32 (68) 15 (32)
  BMI 25 –<30 171 (86) 29 (14) 113 (89) 14 (11)
  BMI < 25 166 (94) 10 (6) 107 (100) 0 (0.0)
Weight at 6–8 weeks postpartum compared to 6–8 weeks EGA 0.176 <0.001
  ≥ 15 lbs. 115 (84) 22 (16) 64 (77) 19 (23)
  5 –< 15 lbs. 137 (90) 15 (10%) 97 (98) 2 (2)
  <5 lbs. 137 (90) 15 (10%) 91 (92) 8 (8)
Pregnancy Factors
Pregnancy/Postpartum Comorbidities
  Shoulder dystocia 8 (100) 0 (0.0) 0.604 5 (100) 0 (0) >0.999
  Gestational diabetes 13 (87) 2 (13) 0.697 7 (78) 2 (22) 0.231
  GHTN/Pre-eclampsia 47 (82) 10 (18) 0.189 34 (87) 5 (13) 0.570
  Blood transfusion 5 (100) 0 (0) >0.999 1 (100) 0 (0) >0.999
  EBL ≥ 1000 (ml) 5 (83) 1 (17) 0.537 6 (100) 0 (0) >0.999
  3rd or 4th degree laceration 11 (85) 2 (15) 0.661 8 (100) 0 (0) >0.999
  APGAR 1 minute < 6 20 (87) 3 (13) 0.747 11 (79) 3 (21) 0.161
  APGAR 5 minute < 6 6 (100) 0 (0) >0.999 4 (80) 1 (20) 0.419
  Any complication 95 (86) 15 (14) 0.613 60 (87) 9 (13) 0.371
Parity 0.289 0.641
  1 316 (87) 47 (13) 205 (89) 25 (11)
  2 89 (92) 8 (8) 59 (92) 5 (8)
Mode of delivery 0.118 >0.999
  SVB 320 (89) 38 (11) 206 (90) 24 (10)
  Cesarean Birth 85 (83) 17 (17) 58 (91) 6 (9)
Newborn weight (grams) 0.374 0.112
  <2500 14 (82) 3 (18) 8 (73) 3 (27)
  2500–4000 356 (88) 50 (12) 236 (90) 25 (10)
  >4000 34 (94) 2 (6) 20 (95) 1 (5)
EGA at time of delivery (weeks) 0.452 0.028
  <36 10 (77) 3 (23) 6 (67) 3 (33)
  36–40 347 (88) 46 (12) 239 (91) 23 (9)
  ≥41 48 (89) 6 (11) 19 (83) 4 (17)
Breast feeding at 2 months <0.001 0.503
  Always 189 (93) 15 (7) 119 (92) 10 (8)
  Sometimes 71 (89) 9 (11) 48 (91) 5 (9)
  Never 91 (78) 25 (22) 61 (87) 9 (13)
Timing of APFT 0.555 0.690
<9 months for 1st postpartum APFT 259 (89) 33 (11) 170 (90) 18 (10)
≥9 months for 1st postpartum AFPT 146 (87) 22 (13) 94 (89) 12 (11)

APFT, Army Physical Fitness Test; BMI, Body Mass Index; IOM, Institute of Medicine; EGA, estimated gestational age; GHTN, gestational hypertension; EBL, estimated blood loss; SVB, spontaneous vaginal birth

 10.1371/journal.pone.0255248.t005 Adjusted odds ratio for risk factors of postpartum APFT and body composition failure with imputed data.
Risk Factors for Postpartum APFT failure (n = 460) Unadjusted Odds Ratio (CI) P value Adjusted Odds Ratio (CI) P value
Failed last APFT prior to pregnancy 9.00 (3.57–22.67) <0.001 16.92 (4.96–57.77) <0.001
Failed last BMI measurement (kg/m2) prior to pregnancy 8.92 (2.64–30.17) <0.001 8.44 (2.23–31.92) 0.002
BMI at 6 to 8 weeks postpartum *
 ≥ 30 vs. < 25 4.44 (1.86–10.04) <0.001 4.02 (1.42–11.35) 0.009
 25 –< 30 vs. < 25 2.98 (1.41–6.29) 0.004 2.92 (1.27–6.68) 0.011
Breast feeding at 2 months
 Never vs. always 3.49 (1.77–6.88) <0.001 3.23 (1.48–7.02) 0.003
 Sometimes vs. always 1.54 (0.64–3.70) 0.339 1.71 (0.67–4.35) 0.261
Age (years) 19–27 vs. 28+† 3.31 (1.46–7.52) 0.004 2.28 (0.93–5.57) 0.070
Risk Factors for Postpartum BMI Failure (n = 460) Unadjusted Odds Ratio (CI) Adjusted Odds Ratio (CI)
Failed last APFT prior to pregnancy 4.77 (1.26–18.13) 0.022 5.40 (1.19–24.61) 0.030
Failed last BMI measurement (kg/m2) prior to pregnancy 14.24 (3.66–55.39) <0.001 6.30 (1.31–30.41) 0.022
BMI at 6 to 8 weeks postpartum*
 ≥30 vs. <30 7.86 (3.49–17.68) <0.001 8.27 (3.25–21.03) <0.001
Age (years) 19–27 vs. 28+† 3.31 (1.12–9.77) 0.031 4.82 (1.42–16.41) 0.012

APFT, Army Physical Fitness Test; BMI, Body Mass Index; CI, confidence interval

Data in bold are statistically significant (p <.05).

*BMI at 6–8 weeks postpartum was dichotomized as <30 vs. 30+ because there were no APFT BMI failures for women whose BMI was <25 at 6–8 weeks postpartum, so odds ratio would be non-estimable for comparisons with the <25 group.

†Age was dichotomized as 19–27 vs. > = 28 based on trend seen in unadjusted failure rates vs. expanded age categories (19–21, 22–24, 25–27, 28–30, and >30).

 Analysis of BMI changes across the combined 6-week and 12-week cohorts

APFT height and weight data with calculated BMI were recorded for 229 women at the time of the pre-pregnancy and postpartum APFT. In the 6-week cohort, the failure rates increased from 4.7% to 11.6% (p = 0.008); in the 12-week cohort, the failure rates increased from 2.9% to 11.8% (p = 0.335). Combined BMI failure rates increased from 4.4% pre-pregnancy to 11.7% post (p<0.001). Increases in failure rates did not differ between the 6-week and 12-week leave groups. Using data from the combined cohort, unadjusted analysis of BMI showed female soldiers who were officers, had passed the APFT and BMI standards pre-pregnancy, had weight gain within IOM standards, and had more rapid weight loss in the first 6–8 weeks postpartum, were significantly more likely to pass BMI standards postpartum (Table 4). Multivariable logistic regression analysis shows age <28 years, BMI >30 kg/m2 at the 6–8 week postpartum appointment and failure of the pre-pregnancy APFT and BMI measurements were significant risk factors for failure on BMI measurements postpartum (Table 5). The mean weight gain comparing AFPTPRE and APFTPOST was 5.3 lbs. with no significant difference between the 6-week and 12-week convalescent leave groups. Mean weight gain between pre- and post-pregnancy APFT was significantly lower for women who were always breastfeeding at 2 months vs. women sometimes or never breastfeeding (2.9 lbs. vs. 7.6 lbs., p = 0.012). Thirty-one percent of all soldiers gained more than 10 lbs. between physical fitness tests across pregnancy. Fifty percent of African American, 21% of Caucasian and 13% of Asian American/Pacific Island soldiers fell into this category. Those soldiers with a BMI ≤25 kg/m2 had an incidence of 33% of excessive weight gain above IOM guidelines whereas soldiers with BMI >25 kg/m2 had an incidence of 70% excessive weight gain above IOM guidelines in pregnancy (p<0.001).

 Duration of pregnancy effect on APFT performance

For the evaluation of the length of time required for an AD soldier to achieve pre-pregnancy physical fitness, the number of postpartum APFTs available for analysis ranged from one to six per individual. The total time interval ranged from 4.5 to 72 months postpartum. Raw scores gradually approached pre-pregnancy levels. On the first APFT postpartum, 25% of women performed equal to or greater than on their sit-up reps and run time, and 37% performed equal to or greater on their push-ups compared to the APFTPRE. Fifty-five percent of women achieved their pre-pregnancy score on their APFT in the 30 months following pregnancy, but the number of push-ups, sit-ups and run times (36.7±12.4 reps, 66.6±12.8 reps and 17.7±1.7 minutes, respectively) remained significantly lower than pre-pregnancy for each event, (p<0.01). By 36 months, 75% of women were able to achieve pre-pregnancy fitness levels (Fig 3a & 3b). Fig 4 shows the Kaplan Meier estimates for time to meet pre-pregnancy APFT levels. The failure rate steadily decreased postpartum from a peak of 13.8% reaching a nadir of 7.7%. The most common individual event failure during the 30+ months was the 2-mile run. Women more quickly regained their push-up scores than those on the sit-up and run events.

10.1371/journal.pone.0255248.g003 Postpartum APFT event raw scores and overall scores over time.

APFT, Army Physical Fitness Test. Pre- denotes the last pre-pregnancy APFT. * P<0.01 vs pre-pregnancy.

 10.1371/journal.pone.0255248.g004 Kaplan-Meier estimates of time to achieve postpartum individual APFT event and overall APFT score equal to or greater than the last pre-pregnancy APFT.

APFT, Army Physical Fitness Test.

 Discussion

The primary findings of this study document that an increase of postpartum leave from 6 to 12 weeks did not adversely affect raw scores on any of the APFT events nor did it decrease the ability of postpartum soldiers to meet physical fitness and body composition standards in the first year postpartum. Risk factors for failure to meet standards on either the APFT or BMI included age <28 years, BMI >30 kg/m2 at the 6–8 week postpartum appointment and failure on the pre-pregnancy APFT and BMI. AD women who successfully met standards postpartum were more likely to meet standards before pregnancy, had gestational weight gain within the IOM guidelines, and were always breastfeeding at 2 months postpartum. We found great variability among our cohort in the ability of individual soldiers to attain pre-pregnancy fitness standards with some women quickly achieving or even exceeding standards while others never doing so.

The secondary outcomes assessed the effects of pregnancy on the performance of individual APFT events. Women experienced a significant 10% drop in push-up and sit-up repetitions and a 1-minute increase in run time postpartum with a concomitant four-fold increase in the failure rate. These findings are similar to other, smaller studies across military services that reported failure rates between 7–25% on fitness assessments in the first year postpartum [15–19]. We also demonstrated a lower rate of failure on the push-up event postpartum as compared to the sit-up or run, in agreement with Rogers et al. [19]. Based on these results it appears that chest, shoulder and upper arm strength is less likely to be adversely affected by pregnancy than is the core abdominal musculature.

There is limited research documenting how quickly a postpartum woman recovers her strength and cardiovascular conditioning. In a cohort of non-military women, Treuth et al. documented a significant decrement in aerobic and to a lesser degree anaerobic performance at 6 weeks postpartum. At 6 months, strength measures had nearly recovered to pre-pregnancy levels, whereas aerobic assessment measures showed a persistent 10–15% decrement [20]. Studies of trunk flexion showed marked decreases in strength and endurance of isometric contractions postpartum as compared to a nulliparous matched control group at 2 and 6 months postpartum [21, 22]. Our data indicates that core strength decrements persists in the first 9 months postpartum.

As our dataset contained the results of multiple APFT events over an extended period of time, we were able to determine the time course necessary to return to pre-pregnancy fitness levels. Rogers et al. analyzed longitudinal data in AD Navy women over a 4-year interval postpartum comparing those to the general population of AD Navy Women. They found that at 2.5–4 years postpartum women were more likely to be overweight, have decreased endurance and decreased core muscle strength as compared to their non -pregnant counterparts [19]. We extend these findings and modeled the time to achieve at least 1 postpartum APFT with a score at least as good as the pre-pregnancy APFT (Fig 4). These data suggest that at 48+ months postpartum 15–20% of AD women will not attain pre-pregnancy levels of physical fitness. Given that some women do rapidly return to pre-pregnancy fitness suggests that lifestyle and/or motivational factors play a larger role than physiological limits.

Unique to our study is the comprehensive evaluation of potential risk factors which could affect the ability of a mother to recover her physical fitness. Unadjusted risk factors for failure on the postpartum APFT events were pre-pregnancy BMI, postpartum BMI, and failing APFT scores before pregnancy. Based on these findings, the decrement in performance postpartum is not due to specific pregnancy associated conditions or complications, but rather due to a generalized deconditioning affecting strength, anaerobic and aerobic capacity before, during and after pregnancy in healthy active women. These findings indicate that the risk for decreased performance on the APFT postpartum may be modifiable with careful monitoring of weight before and during pregnancy as well as early weight loss following pregnancy. Obstetric factors did not adversely affect postpartum physical performance. Other smaller studies have found gestational diabetes, anemia and cesarean section may impact physical performance postpartum, however none of those factors were significant predictors in our analyses [18, 23].

Research has documented significant benefits of breast feeding on the postpartum mother [24]. The effect of breastfeeding on weight loss and exercise tolerance is mixed in studies on military populations. The consensus, however, is that breast feeding does contribute to weight loss postpartum. Our data shows benefits of breast feeding on physical fitness as mothers who were breast feeding at 2 months had higher pass rates than did those that never breast fed. Although no significant reduction in BMI failure rates were seen in the breast-feeding group, significantly more women who were breast feeding achieved pre-pregnancy weight in the first year postpartum. Additionally, our data indicate that the increased convalescence period instituted in February 2016 was associated with increased breast-feeding rates.

Meeting BMI standards, and by inference losing weight postpartum, is as critical for career advancement among military women as is regaining physical fitness. Although related to fitness, weight loss postpartum has been clearly shown to result from diet and not exercise alone [25]. Women in the military must therefore not only be rehabilitating their strength and aerobic conditioning postpartum, but must actively manage their diet to ensure compliance with standards. Our results document pre-pregnancy weight and weight gain above IOM guidelines as risk factors for failure on BMI measurements at the time of the postpartum APFT. Based on their analysis comparing postpartum Navy and Marine women, Greer et al. also conclude that pre-pregnancy weight is the most critical risk factor for failing postpartum BMI standards [26]. In a large Navy cohort, Chauhan et al. had similar findings but additionally determined cesarean section to be a risk factor for weight retention at 6 months postpartum [27]. Cesarean delivery was not documented as a risk factor in our cohort at eight and a half months postpartum. Our data also indicates that an age <28 years was an independent risk factor for not meeting BMI standards postpartum. We attribute this to the attrition of less fit women in military service during their early career, thereby selecting for women who are better able to achieve fitness standards postpartum as they grow older within military service.

Incomplete weight loss following pregnancy has been documented among civilian populations to an even greater degree than in military cohorts. Fifty percent of US women gain excessive weight during pregnancy [28]. According to Endres et al., 75% of women do not lose their gestational weight within one year postpartum [29]. In the meta-analysis by Nehring et al., excess gestational weight gain leads to significant weight retention of approximately 10 lbs. at 15 years postpartum, and the SPAWN study documents the deleterious long term effects of this weight retention [30, 31]. As compared to her civilian counterparts, the AD woman is better conditioned before pregnancy, has a lower prevalence of BMI >25 kg/m2, and engages in organized physical fitness training before, during and after pregnancy, all of which is incentivized. Nevertheless, one-third of women retained more than 10 lbs. and one out of eight did not meet BMI standards at the time of their first postpartum APFT. Although not as profound, racial as well as socioeconomic differences mirror those found by Endres et al. [29].

Strengths of our study include the large sample size of healthy women with the accompanying diversity of racial, socioeconomic and age groups which make the results widely applicable to a civilian population. Obstetric and non-obstetric data were carefully compiled to evaluate for potential risk factors. The socioeconomic effects of bearing a child while on active duty are cushioned as AD women receive full pay while on maternity leave. The AD cohort is incentivized and allotted dedicated time to maintain fitness and lose gestational weight. This study is limited by the inherent limitations of a retrospective study with incomplete records and selection biases. The study could not assess the exercise habits and diet of individuals during and after pregnancy nor could it determine the amount of sleep women experienced, all of which can have a profound impact on weight and conditioning [32]. No control group was utilized in this study but normative values have been established and the pre-pregnancy characteristics of our cohort are similar to those found in previously published studies [33, 34]. A large number of women were excluded from our study. The majority of these did not have APFT data entered into DTMS. We hypothesize that this is due to random incomplete data entry and not a selection bias. Lastly, although we attempted to incorporate indirect measures of stress on the new mother to include marital and economic status, this cannot replicate a matched randomized prospective study assessing the complex psychological, social and economic effects of motherhood and ultimately how these affect physical fitness.

 Conclusion

Pregnancy poses significant challenges for a woman’s physical fitness. This study documents that women who are granted 12 weeks as opposed to 6 weeks of convalescent leave had no adverse outcome on physical fitness at 9 months postpartum. This study also illustrates the decrement in both aerobic and anaerobic fitness among a healthy and physically active cohort of women and the associated risk factors, some of which are modifiable. Female soldiers who are in better physical condition and of normal weight before pregnancy and at 6–8 weeks postpartum, have gestational weight gain within the IOM guidelines and are breast feeding, are at significantly lower risk of failing the APFT and BMI measures postpartum. These findings can be applied to healthy women desiring to regain their physical fitness after pregnancy.

 Supporting information Pregnancy active duty and physical training dataset.

(XLSX)

Ashley Maranich MD (Pediatrician) for her assistance in developing the method of appropriately assessing breast feeding rates; Ms. Elisha Capstick (Research Assistant) for her assistance in collecting data from the inpatient and outpatient electronic medical records. Ms. Diane Kunichika (Medical Librarian) for her assistance in background research and formatting the manuscript.

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Am J Clin Nutr. 2011;94: 1225–1231. doi: 10.3945/ajcn.111.015289 21918221 Linne Y, Dye L, Barkeling B, Rossner S. Weight development over time in parous women—the SPAWN study—15 years follow-up. Int J Obes Relat Metab Disord. 2003;27: 1516–1522. doi: 10.1038/sj.ijo.0802441 14634683 Gunderson EP, Rifas-Shiman SL, Oken E, Rich-Edwards JW, Kleinman KP, Taveras EM, et al. Association of fewer hours of sleep at 6 months postpartum with substantial weight retention at 1 year postpartum. Am J Epidemiol. 2008;167: 178–187. doi: 10.1093/aje/kwm298 17971337 Knapik JJ, Bullock SH, Canada S, Toney E, Wells JD, Hoedebecke E, et al. Influence of an injury reduction program on injury and fitness outcomes among soldiers. Inj Prev. 2004;10: 37–42. doi: 10.1136/ip.2003.002808 14760025 Martin RC, Grier T, Canham-Chervak M, Anderson MK, Bushman TT, DeGroot DW, et al. Validity of Self-Reported Physical Fitness and Body Mass Index in a Military Population. J Strength Cond Res. 2016;30: 26–32. doi: 10.1519/JSC.0000000000001026 26683633 10.1371/journal.pone.0255248.r001 Decision Letter 0 Laganà Antonio Simone Academic Editor 2021 Antonio Simone Laganà This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Submission Version 0

19 Apr 2021

PONE-D-21-04875

The effect of pregnancy and the duration of postpartum convalescence on the physical fitness of healthy women: A cohort study of active duty servicewomen receiving 6 weeks vs 12 weeks convalescence

PLOS ONE

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Reviewer #1: This study evaluates convalescent period length after delivery on fitness. This was a very well written manuscript.

Abstract: please define AD. Lone p-value are unnecessary.

The introduction was very well written.

Excluding data on covariable is a less robust methods and can lead to biased results. Recommend an alternative method so as to not drop all these participants.

I’m not sure raw scores in the tables are necessary; these could be supplement

Although the findings are well described and if the discussion was just about 6 vs 12 weeks convalescence, this would be great. However, the discussion moved into other ideas as to why the failure rate was at the reported level. Virtually no attention was given to potentially other issues that a woman faces beyond exercise and pre-pregnancy fitness /weight levels. Either reduce the speculation in the discussion or add pieces that were not collected such as the brief mention of sleep, smoking status, etc.

Reviewer #2: I have some questions regarding the methodology and results, as well as some suggestions for clarification of your report.

Abstract

Objective – Here you say your outcome is physical fitness but your purpose statement on Line 98 includes body composition.

Methods – You do not clearly describe here or in the methods section of your paper how body composition was assessed.

Introduction

Lines 51-52 – Can you provide support for your statement here? You seem to be reporting cause and effect, but have no evidence to support it.

Line 54 – Your use of textbooks limits readers’ access to your references. Please replace these with research studies demonstrate the prolonged effect of the physiologic changes you’re describing.

Lines 58-60 – Please provide evidence of the multiple factors (emotional, psychosocial, and economic) you’re describing.

Line 63 – You report that the physical fitness standards are validated. Please cite the validation studies.

APFT – Please provide a description of the individual tests either here or as part of your methods. Describe the procedure and the scoring.

Push-ups and sit-ups – Please provide evidence that they are primarily measures of muscular strength and endurance. Since strength and endurance are not the same, please explain which measures strength and which measures endurance.

2-mile run – Please provide evidence that this is a measure of aerobic fitness. And describe the procedure and scoring.

Line 73 – How is “failure” for each event defined?

Line 74 – You seem to be describing calculation of BMI (height and weight) as body composition measurement. They are not interchangeable. Please provide evidence that circumferential measurements are a valid measure of body fat.

Reviewer #3: This manuscript was to assess the differences in physical fitness of active-duty soldiers who had postpartum convalescence of 6 compared to 12 weeks. The rational is well justified, and results mostly support the discussion and conclusion. I have a few comments.

Introduction: It might not be correct to say "... performance... takes 6 to 12 months to completely normalize". The fact is a good proportion of women take much longer to be relatively back to normal than 12 months.

Under objective, AD needs to spell out.

Why was delivering third or greater child exclusionary?

Results: The elapsed time between delivery and first postpartum APFT was 25 days shorter in the 12-week convalescent cohort. Was this considered in any of the risk factor analysis? This may not seem long, but during postpartum it might make a difference.

Some descriptions of table and figure do not match what are included in the respective table or figure. For example, page 13, line 211; page 14, line 231, page 19, line 296.

On page 18, line 271-274, the description of table 4 does not include BMI at 6-8 weeks postpartum or weight at 6-8 weeks postpartum. However, both were significant.

In table 5, some significant findings are bolded, some are not. Please be consistent.

Tables 4 and 5 include different age categories. Table 4 has 19-24, 25-30, and 31, while table 5 has 19-27 and 28+. No reason was provided for the different classification. Similarly, in table 4, BMI at 6-8 weeks postpartum has 30+, 25-30, and <25, while in table 5, only <30 vs. 30+. Please indicate why.

Throughout the manuscript, units should be added where appropriate including tables and text. For example, years should be added for age...

The authors concluded that pregnancy comorbidities did not influence the comparison results between the 6 and 12 week cohorts. It is noted that these comorbidities were examined individually. However, the small number of cases for each comorbidity might not allow this conclusion to be made. Have the authors considered having any one comorbidity vs. no comorbidity in analyses?

The manuscript may be strengthened by additional analyses examining what factors are associated with time it takes for fitness to return to pre-pregnancy level. Data seem to be available.

**********

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 10.1371/journal.pone.0255248.r002 Author response to Decision Letter 0 Submission Version 1

15 Jun 2021

Alan Paul Gehrich MD COL, MC

Chief, Department of Obstetrics and Gynecology Chief, FPMRS

Tripler Army Medical Center

Antonio Simone Laganà M.D., Ph.D. Academic Editor

PLOS ONE

Dr. Laganà,

Thank-you for giving my team the opportunity to submit revisions of our manuscript to PLOS ONE. In this rebuttal letter, we will respond to the critiques posited by the review of our manuscript entitled: The effect of pregnancy and the duration of postpartum convalescence on the physical fitness of healthy women: A cohort study of active duty servicewomen receiving 6 weeks vs 12 weeks convalescence.

All references to line numbers in the itemized responses refer to the manuscript without track changes.

Journal Requirements:

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf

We have made the required changes which are documented with track changes.

2. In the ethics statement in the manuscript and in the online submission form, please provide additional information about the patient records used in your retrospective study, including: a) whether all data were fully anonymized before you accessed them; b) the date range (month and year) during which patients' medical records were accessed; c) the date range (month and year) during which patients whose medical records were selected for this study sought treatment

Response: The following has been added to the method section of the manuscript:

“A roster of eligible women was generated by the medical center clinical bioinformatics office in November 2017. This roster was then used to extract the appropriate APFT and height/weight data from DTMS, in January 2018.” (Line 156-158)

“Individual patient data were extracted from the electronic medical records from January 2018 through March 2019. Individual Department of Defense Identification numbers were used to link the data from each source; once the master file was compiled, source files were deleted and personal identifiers in the master file were replaced with unique numerical identifiers to preserve anonymity.” (Line 165-168)

3. If the ethics committee waived the need for informed consent, or patients provided informed written consent to have data from their medical records used in research, please include this information.

Response: A statement clarifying that the IRB waived the requirement for informed consent has been added. (Line 147-148)

Reviewer #1:

1.

2. 3.

Abstract- Please define AD.

Response: AD is the abbreviation for Active Duty Soldiers. These are soldiers who are serving full time in the US Army. The abbreviation has been defined in the abstract and manuscript.

Lone p-values are unnecessary

Response: The 2 lone p-values have been removed from the abstract.

Methods - Excluding data on covariable is a less robust methods and can lead to biased results. Recommend an alternative method so as to not drop all these participants.

Response: We very much appreciate this comment by Reviewer #1 analysis has augmented the results of our study.

In the paper we state:” Records with incomplete data were excluded from analyses for the variable that was missing. The majority of variables had no missing data or 1 or 2 records with missing data. BMI at six to eight weeks postpartum was missing for 19 women, marital status was missing for 34, breast feeding at two weeks was missing for 60, and APFT body composition was missing for 173 women pre-pregnancy and 166 women postpartum.”

In response to this inquiry, we ran models to impute missing data, which affects primarily breast feeding and BMI, for the analyses summarized in Table 5. The method we used to answer the above inquiry is the Markov chain Monte Carlo method (MCMC). For this analysis, the imputation fills in missing data based on relationships with non- missing variables in the database. After applying MCMC, the same variables as before show up as significant predictors of postpartum APFT failure except that the pre- pregnancy pass/fail for HT/WT also becomes significant.

Manuscript Table 5 (pg. 19) presents odds ratios and 95% confidence limits for two outcomes, postpartum APFT failure and postpartum BMI failure. We created tables using the imputed values. These tables are now included in the manuscript.

To describe the imputation approach used, we also added the following statement to the Methods section of the manuscript: “Because excluding records with missing data may lead to biased results, we used SAS MI to conduct Markov Chain Monte Carlo multiple imputation to impute 20 data sets with complete data. Logistic regression analyses were subsequently performed on each of the 20 imputed data sets, and parameter estimates were combined using SAS MIanalyze.” (Line 201-205)

4. Results – I’m not sure raw scores in the tables are necessary; these could be supplement.

Response: We feel that these raw scores contribute important information to the reader, and we therefore wish to keep these in the manuscript. We defer to the editor.

5. Discussion Comments : Although the findings are well described and if the discussion was just about 6 vs 12 weeks convalescence, this would be great. However, the discussion moved into other ideas as to why the failure rate was at the reported level. Virtually no attention was given to potentially other issues that a woman faces beyond exercise and pre-pregnancy fitness /weight levels. Either reduce the speculation in the discussion or add pieces that were not collected such as the brief mention of sleep, smoking status, etc.

Response: We appreciate Reviewer #1’s comments. We do not feel we have speculated extensively in the discussion. In our comment on weaknesses within the study, we state that sleep, diet and physical activity could not be measured by our study. We do not comment on tobacco use, as it was not found to be statistically significant in our initial analysis.

Reviewer #2

1. Abstract

Objective – Here you say your outcome is physical fitness but your purpose statement on Line 98 includes body composition

Response: We clarified abstract to include BMI in the objective

2. Methods – You do not clearly describe here or in the methods section of your paper how body composition was assessed.

Response: We appreciate this critique and have therefore moved a more comprehensive description of the APFT and body composition assessment into the Methods section and abbreviated this description in the Introduction.

“Army Physical Fitness Test: ( new subheading under Methods)

As described in the introduction, the APFT consists of three individual events. Push- ups and sit-ups are scored by the number of repetitions (reps) performed in 2 minutes. The push-up event assesses the muscular endurance of the chest and upper arm musculature. Rest during the event is only permitted with arms completely extended. Resting on the ground with any part of the body other than hands or feet results in event termination. The sit-up event assesses the muscular endurance of the core and hip flexor muscles. The sit-up is performed with knees bent, hands clasped behind the head and with another soldier holding the feet down. Rest is only permitted when the spine is perpendicular to the ground. The soldier is not permitted to unclasp her hands from behind her head. These first two events primarily measure muscular endurance and the score is based on the maximum number of reps performed in two minutes. [12] Walking is permitted, but discouraged, and the soldier must complete the run without assistance. Previous research has reported correlation coefficients from 0.70-0.90 compared to a treadmill incremental maximal oxygen uptake test. [12] Each of these events is scored according to age and sex- adjusted standards, whereby more reps (push-ups, sit-ups) and faster time (2-mile run) results in a higher score. [9] Failure on any one event, e.g. failure to perform the minimum number of push-up or sit-up reps or 2-mile run time greater than the maximum allowable time, is recorded as a failure for the entire APFT. During the APFT, a soldier’s BMI is assessed using height and weight measurements. If a soldier fails to meet the screening standard, percent body fat is estimated using circumferential measures of the neck, hip and waist. These results are compared to age and sex-adjusted standards, and maximum allowable weight varies, based on sex, height and age. [8]” (Line 115-136)

3. Line 51-52 Can you provide support for your statement here? You seem to be reporting cause and effect, but have no evidence to support it.

Response: We have included a reference for this statement.

4. Line 54 – Your use of textbooks limits readers’ access to your references. Please replace these with research studies demonstrate the prolonged effect of the physiologic changes you’re describing.

Response: We have eliminated the textbook references and replaced them with primary sources documenting this effect. (REF 1-3)

5. Lines 58-60 – Please provide evidence of the multiple factors (emotional, psychosocial, and economic) you’re describing.

Response: We have added multiple references to provide evidence for the above. (REF 4-6)

6. Line 63 – You report that the physical fitness standards are validated. Please cite the

validation studies.

Response: Thank you for this comment. As the standards have not been externally validated, we replaced ‘validated’ with ‘established’. (Line 77)

7. APFT – Please provide a description of the individual tests either here or as part of your methods. Describe the procedure and the scoring.

Response: We appreciate this critique. A paragraph has been added to the Methods section detailing the test events and BMI measurements. See response to Reviewer # 2 Item 2

8. Push-ups and sit-ups – Please provide evidence that they are primarily measures of muscular strength and endurance. Since strength and endurance are not the same, please explain which measures strength and which measures endurance.

Response: Due to the number of repetitions necessary to meet minimum standards, both of these events are primarily tests of muscular endurance and reference to strength has been deleted. An appropriate citation has been added as well. (Line 118)

9. 2-mile run – Please provide evidence that this is a measure of aerobic fitness. And describe the procedure and scoring.

Response: Previous research has reported correlation coefficients of 0.70-0.90 between a 2- mile run and a treadmill incremental VO2max test; we have added an appropriate citation.

(Line 121) The test procedure has been described in the Methods section that has been expanded to describe the APFT.

10. Line 73 – How is “failure” for each event defined?

Response: This has been clarified in the description of the APFT event with references (Line 115-136). Further reference is made in the Legend on Table 3.

11. Line 74 – You seem to be describing calculation of BMI (height and weight) as body composition measurement. They are not interchangeable. Please provide evidence that circumferential measurements are a valid measure of body fat.

Response: We agree with the reviewer regarding BMI vs. calculated BMI. Several equations are available in the literature which can be used to estimate percent body fat from circumference measurements. Unfortunately, Army Regulation 600-9, The Army Body Composition Program, does not provide a citation for the specific equations used in the Army.

Reviewer #3

1. Introduction (Abstract) : It might not be correct to say "... performance... takes 6 to 12 months to completely normalize". The fact is a good proportion of women take much longer to be relatively back to normal than 12 months.

Response: The introductory sentence has been changed. “Pregnancy profoundly affects cardiovascular and musculoskeletal performance requiring up to 12 months for recovery in healthy individuals.”

2. Under objective (Abstract), AD needs to be spelled out.

Response: AD – Active Duty has been spelled out

3. Why was the third delivery exclusionary?

Response: We hypothesized that there is a cumulative effect of multiple pregnancies on physical fitness. By examining pre- and post-pregnancy fitness for the 3rd or greater child, we would be introducing a new covariate. This would likely be a small proportion of the total population we studied, making it difficult to control for.

4. Results: The elapsed time between delivery and first postpartum APFT was 25 days shorter in the 12-week convalescent cohort. Was this considered in any of the risk factor analysis? This may not seem long, but during postpartum it might make a difference.

Response: Yes, time between delivery and postpartum APFT was considered as a risk factor for adjusted analyses. As can be seen in table 4 unadjusted, timing of APFT was not associated with either event failure at postpartum APFT (11% for <9 months vs. 13% for >=9 months, p=0.555) or BMI failure (10% for <9 months vs. 11% for >=9 months, p=0.690). Broken down into more categories, event failure rates were 4.0% (2/50), 12.8% (31/242), 15.1% (19/126), and 7.1% (3/42) for 2-5 months, 6-8 months, 9-12 months, and 13-15 months, respectively. Time between delivery and APFT was examined in adjusted models but was not significant, so not retained in final models.

5. Some descriptions of table and figure do not match what are included in the respective table or figure. For example, page 13, line 211; page 14, line 231, page 19, line 296.

Response: The references to Tables on page 13 and page 14 have been corrected. Thank- you for catching this. The figure reference on page 19 was correct.

6. On page 18, line 271-274, the description of table 4 does not include BMI at 6-8 weeks postpartum or weight at 6-8 weeks postpartum. However, both were significant.

Response: Thank-you for recognizing this oversight. The comment was changed to include reference to 6-8week postpartum weight/BMI.

“Using data from the combined cohort, unadjusted analysis of BMI showed female soldiers who were officers, had passed the APFT and BMI standards pre-pregnancy, had weight gain within IOM standards, and had more rapid weight loss in the first 6-8 weeks postpartum,, were significantly more likely to pass BMI standards postpartum (Table 4).”(Line324-328)

7. In table 5, some significant findings are bolded, some are not. Please be consistent.

Response: All results which were found to be significant have been bolded.

8. Tables 4 and 5 include different age categories. Table 4 has 19-24, 25-30, and 31, while table 5 has 19-27 and 28+. No reason was provided for the different classification. Similarly, in table 4, BMI at 6-8 weeks postpartum has 30+, 25-30, and <25, while in table 5, only <30 vs. 30+. Please indicate why.

Response: Age was broken out into three categories in the demographics table to give a general description of the age distribution. Based on unadjusted failure rates for expanded

age categories (19-21, 22-24, 25-27, 28-30, and >30), age was dichotomized as 19-27 vs. >=28 for the risk factor table because the unadjusted failure rates showed a sharp drop after age 27 (19.3%, 13.3%, 13.3%, 4.7%, and 5.3% for the five categories, respectively.

BMI at 6-8 weeks postpartum was dichotomized as <25, 25-<30, and 30+ for Tables 1, 4 and the analysis of postpartum APFT event failure in Table 5. BMI was dichotomized as <30 vs. 30+ in Table 5 for the analysis of postpartum APFT BMI failure because there were no APFT BMI failures for women whose BMI was <25 at 6-8 weeks postpartum, so odds ratio would be non-estimable for the <25 group.

These responses were placed into the footnote section of TABLE 5 to clarify.

9. Throughout the manuscript, units should be added where appropriate including tables and text. For example, years should be added for age...

Response: Units have been added where appropriate.

10. The authors concluded that pregnancy comorbidities did not influence the comparison results between the 6 and 12 week cohorts. It is noted that these comorbidities were examined individually. However, the small number of cases for each comorbidity might not allow this conclusion to be made. Have the authors considered having any one comorbidity vs. no comorbidity in analyses?

Response: This analysis was included in Table 4 in the original submission and was shown at the bottom of Pregnancy/Postpartum Comorbidities section. Analysis of “Any Complication” showed no difference between Pass/Fail in either the APFT or BMI cohorts.

11. The manuscript may be strengthened by additional analyses examining what factors are associated with time it takes for fitness to return to pre-pregnancy level. Data seems available.

Response: We appreciate this recommendation for our manuscript and did perform adjusted Cox proportional hazard analyses in an attempt to address this question. Results, however, identified the same significant predictors that were shown to be associated with failure at first postpartum APFT (e.g. pre-pregnancy levels, age, gravida/parity, and BMI at 6 to 8 weeks postpartum), and so did not appear to add much new. We also are limited in that we do not have data for time-varying covariates that could affect time to return to pre- pregnancy fitness.

Our Kaplan-Meier analysis was intended to be an additional descriptive statistic simply to show how long it may take to achieve pre-pregnancy levels. We have adequate data to show factors affecting the return to physical fitness in the first year postpartum, however we feel our data is not robust enough to evaluate for factors in the 1-3 year postpartum timeframe, and that overanalyzing this data could detract from the manuscript.

This concludes our responses to the reviewer and editor comments for our manuscript. We very much appreciate the review as these have improved the quality of our presentation. All substantial edits are shown in the track changes copy of the manuscript. Once again we thank the team at PLOS ONE for their support of our research.

V/R

Alan Paul Gehrich MD

Submitted filename: Response to Reviewers PADAPT study.pdf

 10.1371/journal.pone.0255248.r003 Decision Letter 1 Laganà Antonio Simone Academic Editor 2021 Antonio Simone Laganà This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Submission Version 1

13 Jul 2021

The effect of pregnancy and the duration of postpartum convalescence on the physical fitness of healthy women: A cohort study of active duty servicewomen receiving 6 weeks vs 12 weeks convalescence

PONE-D-21-04875R1

Dear Dr. Gehrich,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Antonio Simone Laganà, M.D., Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

I carefully evaluated the revised version of this manuscript.

Authors have performed the required changes, improving significantly the quality of the paper.

Reviewers' comments:

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Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

**********

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The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

Reviewer #3: (No Response)

**********

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Reviewer #2: Yes

Reviewer #3: (No Response)

**********

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The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: (No Response)

Reviewer #3: (No Response)

**********

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Reviewer #2: Yes

Reviewer #3: (No Response)

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Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: Thank you for your thoughtful responses to my questions and comments. Your revisions are well thought out and detailed. In particular, I commend your interest in this population and believe your findings will make a valuable contribution to the current state of the evidence.

Reviewer #3: (No Response)

**********

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If you choose “no”, your identity will remain anonymous but your review may still be made public.

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Reviewer #2: No

Reviewer #3: No

 10.1371/journal.pone.0255248.r004 Acceptance letter Laganà Antonio Simone Academic Editor 2021 Antonio Simone Laganà This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

19 Jul 2021

PONE-D-21-04875R1

The effect of pregnancy and the duration of postpartum convalescence on the physical fitness of healthy women: A cohort study of active duty servicewomen receiving 6 weeks versus 12 weeks convalescence

Dear Dr. Gehrich:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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