Gestational Weight Gain and Postpartum Weight Loss in Active Duty Women (Moms Fit 2 Fight): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Gestational Weight Gain and Postpartum Weight Loss in Active Duty Women (Moms Fit 2 Fight) (NCT03057808), a randomized na study. The primary outcome is Changes in the Mother's Body Weight Pre and Post Pregnancy.

2. Clinical Question

The study’s central question concerns weight management across two distinct periods: pregnancy and the months after birth. It therefore distinguishes support aimed at gestational weight gain from support aimed at postpartum weight loss, while also examining a group that received both interventions in sequence. This design permits comparisons of the posted mean weight-change outcome between the gestational-only group and each of the other two groups. It does not, by itself, answer every possible question about the separate contribution of each intervention or the best timing of support.

The primary outcome was defined for participants completing the 6-month postpartum visit. The registry record does not report the number of participants originally assigned to each arm who completed that visit or the reasons some participants may not have contributed to the primary outcome. The results therefore describe the posted outcome groups; they should not automatically be generalized to every person enrolled or to all active-duty women.

3. Trial Design

Moms Fit 2 Fight was a randomized, parallel-group study with no masking reported. The registry lists an enrollment of 430 and a completed status. It gives a start date of 2017-02-06 and a primary completion date of 2021-11-10. The brief summary describes a plan to enroll approximately 450 subjects, while the enrollment field records 430. The sponsor was the University of Tennessee.

The three arms were the gestational weight-gain intervention alone, the postpartum weight-loss intervention alone, and a combined intervention. In the gestational-only arm, the intervention began at randomization and continued until birth. In the postpartum-only arm, support began at 6 weeks postpartum and continued until 6 months postpartum. Participants in the combined arm received the same intervention as the gestational-only group during pregnancy, followed by the same intervention as the postpartum group after birth. The design descriptions do not establish what participants in each arm received outside the stated intervention periods.

The primary comparison summaries use 132 participants in the gestational-only group, 121 in the postpartum-only group, and 127 in the combined group. These outcome counts are distinct from the enrollment figure and refer to the primary outcome summaries, whose stated population is participants completing the 6-month postpartum visit. The registry record does not report a participant-flow account explaining how enrollment relates to those analysis counts.

Randomization can help balance known and unknown participant characteristics across groups on average, but it does not ensure identical groups in a particular trial. The record does not report the randomization method, any stratification factors, or the original statistical analysis plan. It also does not report the trial’s own design assumptions for its planned sample size. The phase is listed as NA.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Before assignment: Potentially eligible participants presented for a screening visit where full eligibility was assessed, informed consent was obtained, and study measures were collected. Participants were then asked to track their diet and exercise for one week and obtain their obstetrician's clearance for participation. Active duty personnel were also required to submit their fitness test scores for the year prior to study enrollment, to facilitate comparisons with their postpartum fitness test scores.

Overall Study

Analysis population for the primary outcome, as defined in the registry: Those who completed the 6 month postpartum visit

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

6. Primary Endpoint

The registry lists the primary outcome as Changes in the Mother's Body Weight Pre and Post Pregnancy, measured over Baseline to 6 months postpartum.

The primary endpoint is titled “Changes in the Mother's Body Weight Pre and Post Pregnancy.” It concerns weight measured from baseline to 6 months postpartum, with weight recorded in kilograms. The registry describes use of a calibrated digital scale, duplicate measurements, light clothing, and no shoes. At baseline, investigators measured the mother’s weight; the record also notes a self-reported pregravid weight from before the last menstrual period.

Weight is a continuous outcome, so it can be summarized by a mean and a measure of spread. The posted arm summaries report means and standard deviations for the primary outcome. The mean describes the group’s average recorded change, while the standard deviation describes how spread out participant values are around that average. These summaries show both the central tendency and the variability, but they do not reveal the full distribution of individual outcomes.

Following weight over pregnancy and postpartum is relevant to the study’s stated behavioral weight-management question because it tracks the outcome the interventions were intended to address. The chosen follow-up point also places the comparison after the postpartum intervention period described for the relevant arms. However, the registry record does not give a fuller operational definition of the change calculation, including the exact calculation convention or whether any adjustments were made. It also does not report how missing or incomplete weight measurements were handled. Those details matter when interpreting the mean differences and deciding how closely the posted outcome reflects change for all randomized participants.

7. Results Posted in the Registry

• Postpartum Weight Loss Intervention (PPWL-only): mean 1.25 versus 2.39 on control; difference -1.14 (95% CI -2.47 to 0.19), standardized effect d = -0.21; z-test p = 0.092.
• Combined: mean 1.37 versus 2.39 on control; difference -1.02 (95% CI -2.38 to 0.34), standardized effect d = -0.18; z-test p = 0.140.

8. Secondary Efficacy Endpoints

The registry also posts results for secondary outcomes. For each outcome below, the endpoint type, the test applied to the posted summary statistics, the result and its interpretation are given in turn. Secondary endpoints are usually not adjusted for multiple testing, so they support rather than confirm the primary finding.

Birth Weight of Infant

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Comparison Condition (PPWL-only): mean 3,365 versus 3,364 on control; difference 1.80 (95% CI -123.00 to 126.60), standardized effect d = 0.00; z-test p = 0.977.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Comparison Condition (PPWL-only) and the control. The interval gives the range of effects that remain compatible with the data.

Length of Infant

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Comparison Condition (PPWL-only): mean 50.80 versus 51.30 on control; difference -0.50 (95% CI -1.37 to 0.37), standardized effect d = -0.15; z-test p = 0.261.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Comparison Condition (PPWL-only) and the control. The interval gives the range of effects that remain compatible with the data.

The registry lists eight secondary outcomes, including maternal and fetal conditions during pregnancy, infant birth weight and length, fitness-test measures, waist circumference, and a program evaluation form. Numerical summaries and unadjusted comparisons are posted for infant birth weight and infant length. The registry record does not report analyses for the remaining secondary outcomes, and it does not provide a full set of secondary results across all listed measures.

The two posted infant measures have mean differences whose confidence intervals include zero. This broad pattern is consistent with the primary comparisons in one limited respect: the posted intervals do not isolate a difference from zero. It does not make the secondary findings a confirmation of the primary outcome. Infant measurements and maternal weight change represent different outcomes, with different units and meanings, and their results cannot be combined into one overall treatment effect.

Secondary endpoints can help describe other outcomes relevant to a trial, but they often involve multiple comparisons. General statistical explanation: when many outcomes or contrasts are examined, the chance of at least one apparently unusual result can increase, even when there is no underlying effect for any of them. An unadjusted p-value treats a particular test as if it were considered on its own; it does not account for a wider family of tests. The registry record does not report a multiplicity strategy, such as which secondary outcomes were confirmatory or whether any adjustment was planned.

Accordingly, unadjusted secondary findings carry less weight as standalone evidence than a prespecified primary comparison, particularly when the analysis plan and multiplicity handling are not available. The posted summaries can inform what was measured and the direction and uncertainty of the reported comparisons. They do not establish a consistent benefit or harm across outcomes, and they should not be used to fill gaps for secondary outcomes without posted analyses.

Secondary outcomes registered for this trial, for reference (only those above were recalculated):

• Maternal and Fetal Conditions During Pregnancy
• Birth Weight of Infant
• Length of Infant
• Waist Circumference on Fitness Test Scores
• Number of Push Ups on Fitness Test Scores
• Number of Sit Ups on Fitness Test Scores
• 1.5 Mile Run on Fitness Test Scores
• Moms Fit 2 Fight Program Evaluation Form

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is continuous, and the registry identifies the summary parameter as a mean with standard deviation. A mean difference compares the average outcome in one group with the average in the reference group. Here, the posted differences compare postpartum-only or combined support with gestational-only support. The negative signs indicate that the reported means in the named comparison groups are lower than the reference-group mean for this outcome. A mean difference retains the original unit, kilograms, which helps describe the size of the group contrast in terms of the measured outcome.

What do the standard deviations describe?

A standard deviation describes the spread of participant measurements around a group mean. It is not the uncertainty in the mean difference and is not the range containing every participant’s result. When individuals vary substantially, the standard deviation can be large even when the group mean is estimated with some precision. The primary arm summaries report standard deviations of 5.36, 5.4, and 5.76 kilograms. They indicate that individual measurements vary around their respective group averages; they do not show whether the distribution is symmetric or whether it contains unusual values.

What does a confidence interval add?

General statistical explanation: a confidence interval gives a range of values that are compatible with the data and the method used to construct the interval. It communicates uncertainty around an estimate, rather than simply labeling a result as positive or negative. When an interval for a mean difference includes zero, values corresponding to no mean difference remain compatible with the data under that method. An interval that also includes values on both sides of zero allows for more than one interpretation of the underlying difference. The confidence level and interval-construction method for the posted primary comparisons are not reported in the registry record.

The primary comparison intervals cross zero, so they do not resolve whether the population mean difference is exactly zero or differs in either direction. Their widths also matter: an interval can include zero while still ruling out some larger differences, or it can remain broad enough to allow a wider range. The interval bounds are not repeated; the key interpretive point is that each crosses zero. The point estimates alone should not be treated as if they were known population effects.

How should the p-values be read?

The posted p-values are unadjusted: 0.092 for postpartum-only versus gestational-only and 0.14 for combined versus gestational-only. General statistical explanation: a p-value describes how unusual the observed data, or data more extreme, would be under a specified null model. It is not the probability that the null hypothesis is true, and it does not measure the probability that the finding will replicate. A p-value also does not indicate the size or practical importance of an effect. Because these values are unadjusted, they do not account for the fact that more than one comparison or outcome may be considered.

The registry record does not report the investigators’ primary analysis method, the null hypothesis they specified, or a prespecified threshold for the primary test. Consequently, the posted p-values are best interpreted alongside the estimates and intervals, rather than as stand-alone verdicts. Their unadjusted status should also remain clear when considering outcomes beyond the primary endpoint.

Why can over-dispersion matter?

General statistical explanation: over-dispersion means that observed variation is greater than a model assumes. If a model understates variability, its standard errors may be too small and its intervals too narrow, making the data appear more precise than they are. For a continuous outcome, the spread of individual values and the suitability of the model’s assumptions can affect uncertainty calculations. The registry record does not report a specific assessment of model assumptions or over-dispersion. The posted standard deviations give a basic view of variability but are not, on their own, a diagnostic check of a statistical model.

The sample-size planning illustrations use a normal approximation, two-sided significance level 0.05, equal allocation between two arms, and a specified fraction of the observed effect as the target to detect. These are planning assumptions for the illustrations, not documented design assumptions for the original trial. General explanation: normal-approximation planning translates an assumed effect and variability into an estimated number of participants needed to reach a chosen probability of detecting that effect under the planning model. The result depends on those assumptions and should not be confused with the analysis of the participants who took part.

Finally, a comparison of group means does not establish that the intervention caused any particular participant’s outcome. Randomization supports group comparisons, but interpretation still depends on the analyzed population, missing outcomes, adherence, and the analysis plan. Those details are not fully reported in the registry record. The summaries are useful for describing the observed group averages and their uncertainty, but they do not replace a complete trial report.

11. Confidence Intervals and Precision

Precision concerns how narrowly the data estimate a group difference. The primary mean-difference estimates are -1.14 kilograms for postpartum-only versus gestational-only and -1.02 kilograms for combined versus gestational-only. Each corresponding confidence interval spans values below and above zero. Thus, each estimate has uncertainty that includes no mean difference, as well as differences in either direction. The point estimates describe the direction and size of the observed contrasts; the intervals show why the estimates should not be read as exact effects.

The registry record does not state the confidence level used for these intervals. Nor does it provide enough information to assess whether the analysis accounted for all relevant sources of uncertainty, such as missing outcome measurements or any adjustment for baseline characteristics. The posted comparisons are unadjusted summaries. Their precision should therefore be understood in the context of the available outcome counts and the lack of a reported analysis plan, rather than treated as a complete uncertainty assessment for every possible analysis.

Variation within groups is also relevant. The standard deviations are 5.36 kilograms for gestational-only, 5.4 kilograms for postpartum-only, and 5.76 kilograms for combined. The observed group spreads are appreciable relative to the estimated mean differences, so the averages do not imply that participants’ individual changes were clustered tightly around the estimated contrast. The record does not report distributions that would show how individual outcomes were arranged within each group.

For the secondary comparisons, the posted confidence intervals for infant birth weight and infant length also include zero. Those results likewise leave uncertainty about the direction and magnitude of the corresponding population mean differences. The registry record does not report confidence levels for these intervals either. Precision is not the same as importance: even a precisely estimated difference would need substantive interpretation, while an imprecise estimate may leave a potentially relevant range unresolved.

12. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The planning illustrations give participants per arm, not total participants, for these continuous-outcome comparisons. The registry record does not report a time-to-event planning result requiring a total event count. The illustrations use a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. They assume the target effect is a stated fraction of the observed effect. These are planning assumptions for the illustrations; the trial’s own original design assumptions are not reported in the registry record.

For the postpartum-only comparison, planning for 100% of the observed effect gives 350 participants per arm for 80% power and 468 participants per arm for 90% power. Planning for 75% of the observed effect gives 622 per arm for 80% power and 832 per arm for 90% power. For 50% of the observed effect, the illustrations give 1,399 and 1,872 participants per arm, respectively. For the combined comparison, the corresponding figures are 467 and 625 per arm for 100% of the observed effect; 830 and 1,110 per arm for 75%; and 1,866 and 2,498 per arm for 50%.

General explanation: the 80% power column describes the planned number per arm under the stated assumptions for an 80% chance of detecting the target effect if that effect is the true one. The 90% column uses a higher target chance under those assumptions and therefore calls for more participants. Smaller effects are harder to distinguish from random variation, so planning to detect a smaller fraction of the observed effect requires more participants per arm.

These are planning illustrations, not observed power. They use the observed effect as the starting point for hypothetical planning, and they are sensitive to that estimate and to the listed assumptions. They should not be read as evidence that the completed trial had a particular probability of finding a result, or as a description of the trial’s intended sample size.

13. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = -1.140; pooled standard deviation σ = 5.379.
2. n = 2 × (1.96 + 0.842)² × 5.379² / -1.140² = 349.5, rounded up to 350 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
delta <- -1.14                      # observed difference in means
sigma <- 5.3791606152171                     # pooled standard deviation
n_per_arm <- function(power, frac = 1) {
  ceiling(round(2 * (z_a + qnorm(power))^2 * sigma^2 / (delta * frac)^2, 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Check against R's built-in function (t-based, so very slightly larger)
cat("power.t.test:", round(power.t.test(delta = delta, sd = sigma, power = 0.80)$n, 1), "\n")

# Simulation: exact two-sample t-test using simulated means and variances
set.seed(3057808)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 350 (80% power), 468 (90% power)
 75% of observed effect: n per arm = 622 (80% power), 832 (90% power)
 50% of observed effect: n per arm = 1,399 (80% power), 1,872 (90% power)
power.t.test: 350.5 
Simulated power at n = 350 per arm: 0.803 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

14. Multiplicity, Missing Data and Analysis Populations

The registry record lists a primary outcome and a range of secondary outcomes, but it does not report a statistical analysis plan or a strategy for handling multiplicity. That leaves important questions unanswered: which comparisons were intended to be confirmatory, whether the primary outcome had a prespecified model, and whether secondary tests were to be adjusted or interpreted as exploratory. The posted primary comparisons are unadjusted, and the available secondary comparisons are also unadjusted. When several outcomes and contrasts are considered, isolated p-values require cautious interpretation because they do not account for the broader set of tests.

Missing data are another unresolved issue. The primary outcome population is described as participants who completed the 6-month postpartum visit, but the record does not report how many participants in each randomized group were eligible for that visit, how many completed it, or why measurements may be missing. The group counts in the primary summaries are 132, 121, and 127. Without a participant-flow account, it is not possible to determine from the registry record whether missingness differed across groups or how it may have affected the comparisons.

The record also does not state whether the primary analysis followed an intention-to-treat principle, whether participants were analyzed according to assigned group, or whether a per-protocol or other population was used. It does not describe imputation, sensitivity analyses, or other methods for addressing missing outcome data. These are not minor technical details: conclusions can depend on how incomplete follow-up is handled, especially when the outcome is defined for visit completers.

There are additional analysis details not reported in the registry record, including the prespecified statistical model, any adjustment for baseline measures, the method used to construct confidence intervals, and any interim analyses. The registry record also does not provide the investigators’ original sample-size justification. In the absence of these details, the posted summaries remain useful descriptions of the recorded outcomes, but they do not reveal the full analytic choices or establish that all sources of bias and uncertainty were addressed.

15. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: preterm labor/delivery (4.9%), caesarean section (4.2%), preeclampsia (3.5%), miscarriage (2.8%), uterine bleeding (1.4%).

The registry reports serious adverse events for all three groups, with a denominator of 144 at risk in the gestational-only group, 142 in the postpartum-only group, and 144 in the combined group. The corresponding numbers affected were 23, 13, and 22. Other adverse events were reported for 30 of 144, 38 of 142, and 46 of 144, respectively. The record lists zero deaths in each group.

The serious-event terms listed include preterm labor/delivery (4.9%), caesarean section (4.2%), preeclampsia (3.5%), miscarriage (2.8%), uterine bleeding (1.4%), and appendectomy (0.7%). The registry record does not specify the denominator or complete counting context for those percentages in the information, so they should be read as the listed event percentages rather than recalculated group risks.

These counts are descriptive. The registry record does not provide a formal statistical comparison of adverse-event frequency between groups, event timing, or an attribution assessment linking events to an intervention. The at-risk counts also differ from the primary outcome counts, reflecting that safety and primary outcome summaries are not necessarily based on the same analysis population. The figures should not be treated as evidence that group safety profiles are equivalent or different without a suitable comparative analysis.

16. What the Result Does, and Does Not, Mean

The results show that the posted mean weight-change estimates were lower in both groups receiving postpartum weight-loss support than in the gestational-only reference group. The unadjusted mean differences were -1.14 kilograms for postpartum-only and -1.02 kilograms for combined support. Both intervals crossed zero, so the estimates remain compatible with no population mean difference as well as with differences in either direction. The results communicate a direction in the observed summaries, but not a precise or conclusive separation between the groups.

That interpretation applies to the posted primary outcome population: participants who completed the 6-month postpartum visit. The registry record does not explain how missing outcomes were handled or whether the groups retained after follow-up were comparable to all randomized participants. It also does not report a full analysis plan. Those limits mean the summaries cannot, on their own, establish the causal effect of assignment to an intervention for every enrolled participant.

The findings do not show that every participant experienced a change close to the group mean. The standard deviations indicate variability, and the registry does not provide individual-level distributions or responder categories. Nor do the mean comparisons answer whether the observed difference would matter to participants or clinicians; the record does not specify a threshold for a meaningful difference.

The secondary results concern infant measurements rather than maternal weight change. Their intervals also include zero, but they address separate questions and should not be combined with the primary finding to make a general claim across outcomes. Safety counts are descriptive and do not establish comparative safety.

Overall, the posted data are best read as estimates with substantial uncertainty and incomplete information about analysis and follow-up. They do not justify saying that an intervention works or does not work. They show what the recorded group averages and comparisons were, while leaving unresolved the precise population differences, their practical importance, and how the results would look under alternative missing-data or analysis assumptions.

17. Why This Trial Matters Statistically

This trial is statistically informative because it distinguishes intervention timing and sequence rather than treating all weight-management support as one exposure. The three-arm design places gestational-only support alongside postpartum-only support and a combined sequence. That structure creates more than one relevant comparison and makes clear why the reference group and the intervention period must be identified when interpreting an estimated mean difference.

The primary endpoint is a continuous measure of maternal weight change, so the result can be expressed in the outcome’s original unit as a difference between group means. That is often easier to interpret than a test statistic alone. At the same time, the standard deviations show that a mean difference is only one part of the picture: substantial individual variation can coexist with a smaller average contrast.

The confidence intervals are central to the statistical reading. Both primary intervals include zero, which makes the uncertainty visible and prevents the point estimates from being treated as exact. The unadjusted p-values give a related but narrower summary; they do not describe effect size, practical importance, or the results of all possible analyses. Considering estimates, intervals, group variation, and analysis limitations together is more informative than focusing on a single significance label.

The registry also illustrates why enrollment and analysis counts should not be conflated. The total enrollment is 430, while the primary outcome summaries include smaller group counts and are defined for visit completers. Without participant-flow and missing-data information, the relationship between those numbers remains unclear. That gap is relevant to precision and to the population represented by the results.

Finally, the planning illustrations show how assumed effect size influences the number of participants needed under stated assumptions. They are not a substitute for the trial’s own design rationale, which is not reported. Together, these features make the record a useful example of interpreting randomized comparisons while keeping design, analysis population, uncertainty, and planning assumptions separate.

18. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

Several limitations are specific to the information recorded for this trial. Although enrollment is listed as 430 and the primary outcome population is defined as visit completers, no participant-flow details explain the group counts used for the primary summaries. The record does not report how many randomized participants failed to complete the 6-month visit, whether follow-up differed across groups, or why data were unavailable. This prevents a clear assessment of potential selection from restricting the outcome population to completers.

The intervention periods are described, but the registry record does not give detailed information about the content, frequency, adherence, or delivery of the behavioral programs. It also does not report whether participants received other weight-management support. These omissions make it difficult to judge how consistently the interventions were implemented or how the recorded comparisons relate to actual participation.

The primary outcome description notes investigator-measured baseline weight and self-reported pregravid weight, but the posted primary endpoint timeframe is baseline to 6 months postpartum. The registry does not give a fuller definition of the calculation used for change or explain how the self-reported pregravid measure relates to the primary outcome calculation. This limits detailed interpretation of the outcome’s construction.

The record does not report the investigators’ analysis plan, primary model, missing-data procedures, multiplicity approach, or interim analyses. It also does not explain the original sample-size rationale. Consequently, the posted unadjusted comparisons should not be mistaken for a complete account of all prespecified analyses. The secondary outcome list is broader than the numerical secondary results available in the record, and the secondary analyses are not reported there.

Finally, the primary comparisons use group means and standard deviations. The record does not provide participant-level distributions or analyses of subgroups, so it cannot show whether average results were similar across different participant characteristics. These limitations concern what can be learned from the registry record; they do not establish that the trial did or did not address these issues in other documentation.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Gestational Weight Gain and Postpartum Weight Loss in Active Duty Women (Moms Fit 2 Fight) — NCT03057808.
• Registry record last updated 2022-12-23; status last verified 2022-07.
• Results first posted 2022-12-23.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

22. Record Summary

NCT03057808, “Gestational Weight Gain and Postpartum Weight Loss in Active Duty Women (Moms Fit 2 Fight),” was a randomized, parallel-group study with no masking reported. The sponsor was the University of Tennessee. The record lists enrollment of 430, a completed status, a start date of 2017-02-06, and a primary completion date of 2021-11-10.

The three groups received gestational weight-gain support alone, postpartum weight-loss support alone, or the combined sequence. The primary outcome was maternal weight change from baseline to 6 months postpartum among participants completing that visit. The posted unadjusted mean differences versus gestational-only support were -1.14 kilograms for postpartum-only and -1.02 kilograms for combined support; both intervals crossed zero.

Numerical secondary comparisons are posted for infant birth weight and length, and the registry lists adverse-event counts for each group. The record does not report a complete analysis plan, missing-data methods, or multiplicity strategy. The results are therefore most appropriately read as posted group summaries and uncertain unadjusted comparisons, not as a complete account of every planned analysis.