Weight Management for Improved Pregnancy Outcomes: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Weight Management for Improved Pregnancy Outcomes (NCT00950235), a randomized na study. The primary outcome is Maternal Weight Change.

2. Clinical Question

3. Trial Design

This was a randomized, single-masked, parallel-group study. The registry records 118 participants enrolled and marks the study as completed. It lists the phase as not applicable. The sponsor was Kaiser Permanente. The recorded start was 2009-10 and the primary completion was 2012-03.

The two arms were usual care and weight-management counseling. The usual-care description includes routine prenatal care and one additional nutrition session. The counseling arm received in-person and group-session counseling. The registry’s brief summary describes the intervention as a more intensive dietary program, with weight maintenance and avoidance of postpartum weight retention as goals. The record does not state who was masked, so the meaning of single masking in practice is not reported in the registry record.

The primary outcome was maternal weight change, measured in kilograms from baseline to two weeks postpartum. The registry explains that this postpartum measurement was selected instead of an end point during pregnancy to avoid weight contributions from products of conception, maternal edema, and increased maternal blood volume. Primary-outcome data came from a follow-up visit or validated clinical data.

The registry also lists pregnancy weight change from baseline to 34 weeks’ gestation and large for gestational age at birth as secondary outcomes. The posted outcome data include results for both arms, but the registry lists no reported analyses for either secondary outcome. The original sample-size rationale, detailed randomization procedures, and original statistical analysis plan are not reported in the registry record.

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: Women were invited to attend an informational meeting which explained the study and covered the elements of consent. Interested volunteers were asked to come back to the research setting for the baseline visit. Randomization occurred at the baseline visit after a final review of eligibility and signing a consent.

Overall Study

Analysis population for the primary outcome, as defined in the registry: Data was from follow up visit or validated clinical data

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 Maternal Weight Change, measured over baseline to 2 weeks post partum.

The primary endpoint is maternal weight change in kilograms from baseline to two weeks postpartum. It is a continuous outcome, and the registry reports the mean and standard deviation for each arm. The comparison therefore concerns average change between groups; it does not indicate that each participant gained or lost the amount represented by an arm mean.

The registry gives a reason for measuring weight at this postpartum time point rather than at the end of pregnancy. Weight during pregnancy can include contributions from products of conception, maternal edema, and increased maternal blood volume. Measuring at two weeks after delivery was intended to avoid those contributions when assessing the endpoint. The registry states that outcome data came from a follow-up visit or validated clinical data.

The posted mean change was 1.2 kg in usual care and -2.6 kg in weight-management counseling. The reported mean difference, counseling compared with usual care, was -3.8 kg, with a 95% confidence interval from -5.838 to -1.762 kg. The negative sign indicates that the counseling arm’s mean change was lower. The endpoint does not by itself establish why the groups differed, whether the difference reflects the intervention alone, or how individual participants’ weights changed.

7. Results Posted in the Registry

• Weight Management Counseling: mean -2.60 versus 1.20 on control; difference -3.80 (95% CI -5.84 to -1.76), standardized effect d = -0.68; z-test p = <0.001.

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.

Pregnancy Weight Change

• 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:
  • Weight Management Counseling: mean 5.00 versus 8.40 on control; difference -3.40 (95% CI -5.02 to -1.78), standardized effect d = -0.77; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Weight Management Counseling than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Large for Gestational Age (LGA)

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Weight Management Counseling: 8.9% (5/56) versus 25.9% (15/58) on control; risk difference -16.9 percentage points (95% CI -30.5 to -3.4), risk ratio 0.35 (0.13–0.89); unadjusted two-proportion z-test p = 0.017.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically lower for Weight Management Counseling than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary outcomes extend the primary question in two directions: weight change during pregnancy and large for gestational age at birth. Together, their posted results show a pattern in the same broad direction as the primary comparison, with lower weight change and fewer large-for-gestational-age participants in the counseling arm. They offer context about pregnancy-period measurements and a birth outcome, but they do not establish that the primary result caused either secondary pattern.

The outcomes are measured on different scales and at different times. Pregnancy weight change is continuous and measured from baseline to 34 weeks’ gestation; large for gestational age is a binary outcome assessed at birth. The primary endpoint is instead postpartum weight change. Differences in timing and outcome type mean that consistency in direction is not equivalent to replication of the same finding.

The registry lists no reported analyses for the secondary outcomes. Their posted p-values are unadjusted, and a multiplicity strategy is not reported in the registry record. In general, interpreting multiple tests without accounting for the number of comparisons can make isolated small p-values less persuasive than a single prespecified primary test. The secondary results should therefore be considered supportive and descriptive, with less inferential weight than the primary endpoint.

The record does not state whether the secondary outcomes were prespecified in a detailed analysis plan, how missing observations were addressed, or whether any covariate adjustment was performed. Their pattern can motivate further study, but the summaries do not establish a mechanism, a causal pathway, or a definitive conclusion about outcomes beyond the posted measurements.

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

• Pregnancy Weight Change
• Large for Gestational Age (LGA)

9. Statistical Interpretation

10. Statistical Methods Explained

What does a mean difference describe?

A mean summarizes the average outcome in a group. For this continuous endpoint, the comparison is the counseling-arm mean minus the usual-care-arm mean. The reported value of -3.8 kg indicates that the counseling-arm average was lower. It is a comparison of group averages, not a prediction for an individual participant. The standard deviation describes how dispersed participant measurements are around a group mean; it is not the uncertainty interval for the mean difference.

The registry reports standard deviations of 5.6 kg for usual care and 5.5 kg for counseling. These values indicate variability among the observed weight changes within each arm. The reported confidence interval for the difference addresses a different question: how precisely the mean difference is estimated under the comparison’s statistical assumptions.

How should the confidence interval and p-value be read?

A confidence interval gives a range of values compatible with the observed data and the method used to calculate the interval. It conveys uncertainty about the estimated between-group difference. The interval from -5.838 to -1.762 kg lies below zero, the value that would represent no mean difference. The unadjusted p-value is <0.001. A p-value measures how unusual results at least as incompatible with a no-difference model would be, if that model and the analysis assumptions held. It is not the probability that the no-difference model is true, nor does it measure the size or importance of the difference.

The registry does not report the original statistical analysis plan, including whether this p-value was the planned primary test or whether any covariate adjustment was used. The posted comparison is unadjusted. The original approach to repeated measurements, if any, is not reported in the registry record; the stated primary endpoint itself is a single change measure over the named interval.

Why does the outcome scale matter?

Weight change is continuous and measured in kilograms, so means and standard deviations summarize the arm results naturally. A difference in means retains the measurement scale and direction: negative values in this comparison favor a lower average change in counseling relative to usual care. That description concerns the numerical outcome, not a judgment about the desirability of a particular weight change.

For a binary outcome such as large for gestational age, the relevant summaries are counts and proportions, and a risk difference compares the proportions between arms. Such outcomes are not interpreted using a mean difference in kilograms. The registry posts both continuous and binary secondary outcomes, so their estimates use different scales and should not be directly compared as if they measured the same thing.

What is over-dispersion, and is it reported?

In general, over-dispersion means that observed variation is greater than a statistical model expects. It can make standard errors too small and confidence intervals too narrow if the model does not account for the extra variation. It is a concern in some count or clustered-data analyses, but the registry does not report an over-dispersion assessment or describe a model requiring such an adjustment. It would therefore be inappropriate to assert that over-dispersion affected this trial’s results.

What do the secondary-outcome tests establish?

The posted secondary p-values are unadjusted. In general, when several outcomes are tested, the chance of finding at least one apparently unusual result can increase if each test is interpreted without accounting for the collection of tests. Multiplicity adjustments are methods for addressing that issue. The registry does not report a multiplicity strategy, so the secondary tests should be read with appropriate caution. The record also lists no reported analyses for the secondary outcomes.

The trial’s original handling of missing observations, exclusions, and analysis populations is not reported in the registry record. These matters can affect the interpretation of estimates because the people included in an analysis may differ from those enrolled. No assumptions about those procedures can be recovered from the posted summaries alone.

11. Confidence Intervals and Precision

The primary mean difference is -3.8 kg, with a 95% confidence interval from -5.838 to -1.762 kg. The interval communicates uncertainty around the estimated average difference. Its limits are both negative, so the range of values compatible with this calculation indicates a lower mean change in the counseling arm than in usual care. The estimate is not exact: values across the interval represent different plausible magnitudes of the difference under the method used.

The reported standard deviations are 5.6 kg for usual care and 5.5 kg for weight-management counseling. They describe the spread of participant outcomes within each group and show why the mean difference should not be mistaken for a uniform individual response. Participant numbers in the primary summaries are 58 for usual care and 56 for counseling.

The interval’s width reflects the precision available from these data and this analysis. A narrower interval would generally indicate more precision, while a wider interval would leave more uncertainty about the effect’s magnitude. Precision is distinct from statistical significance and from clinical importance. The unadjusted p-value is <0.001, but that alone does not convey the full range of plausible differences or define what size of difference matters to participants.

The registry does not report an interval for every outcome in the arm summaries, nor does it describe adjustments that might change the uncertainty estimates. The interval should therefore be interpreted as belonging to the posted comparison and its stated outcome, not as a complete account of all uncertainty about the study or its generalizability.

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 use participants per arm, not total events. They are based on a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. Each row considers detecting a stated fraction of the observed effect. The registry’s original design assumptions and original sample-size justification are not reported in the registry record. These figures are planning illustrations, not observed power.

For the primary endpoint, planning for 100% of the observed effect gives 34 participants per arm for 80% power and 45 participants per arm for 90% power. Planning for 75% of the observed effect gives 60 participants per arm for 80% power and 80 participants per arm for 90% power. Planning for 50% of the observed effect gives 134 participants per arm for 80% power and 180 participants per arm for 90% power.

In plain language, the 80% column describes the planned number per arm under which a study would have an 80% chance of detecting the specified effect if that effect were present and the planning assumptions held. The 90% column describes the corresponding planning target for a 90% chance. These are design concepts, not probabilities that the trial’s finding is correct. Smaller effects are harder to detect and require more participants: the entries increase as the assumed fraction of the observed effect decreases.

The plotted curve can be read as a visual version of the planning relationship: the required number of participants depends on the effect size selected and the target power. These calculations use the observed effect as their reference, so they should not be mistaken for the study’s original design calculations or for evidence about the probability that a result would replicate.

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 = -3.800; pooled standard deviation σ = 5.551.
2. n = 2 × (1.96 + 0.842)² × 5.551² / -3.800² = 33.5, rounded up to 34 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 <- -3.8                      # observed difference in means
sigma <- 5.55111796976841                     # 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(950235)
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 = 34 (80% power), 45 (90% power)
 75% of observed effect: n per arm = 60 (80% power), 80 (90% power)
 50% of observed effect: n per arm = 134 (80% power), 180 (90% power)
power.t.test: 34.5 
Simulated power at n = 34 per arm: 0.792 (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

Multiplicity concerns arise when a study evaluates more than one outcome or makes multiple statistical comparisons. In general, the more tests considered, the greater the possibility that at least one result appears unusual by chance if each test is judged separately. Methods such as a prespecified hierarchy or an adjustment to the testing threshold can address this concern. The registry lists one primary outcome and two secondary outcomes, but a multiplicity plan is not reported in the registry record. The posted secondary p-values are unadjusted.

The registry records no reported analyses for the secondary outcomes. It does not explain whether the posted summaries were the only analyses conducted, whether other outcomes or subgroup comparisons were assessed, or whether an analysis hierarchy was planned. Those details are not reported in the registry record, so it is not possible to assess how the reported tests fit within a complete testing strategy.

Missing-data procedures are also not reported in the registry record. The primary endpoint summaries list 58 participants in usual care and 56 in counseling, while total enrollment was 118. The record does not explain the difference between these figures, identify how many participants had unavailable outcomes, or state whether missing values were imputed or otherwise handled. The outcome description says data came from a follow-up visit or validated clinical data, but it does not specify how those sources were combined or how unavailable measurements affected inclusion.

The analysis population is not reported in the registry record. It is therefore unclear whether the posted comparisons include all randomized participants, only those with outcome data, or another defined group. The record also does not describe exclusions after randomization or an intention-to-treat approach. These omissions matter because analysis choices and missingness can affect both the estimate and its uncertainty. They do not prove that the results are biased, but they limit independent evaluation of the analysis.

15. Safety Results

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

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: miscarriage (3.3%).

The adverse-event summaries use different at-risk group sizes from the primary outcome summaries. For serious adverse events, the registry lists 2 affected participants among 60 at risk in usual care and 0 among 58 at risk in weight-management counseling. For other adverse events, it lists 40 among 60 at risk in usual care and 30 among 58 at risk in counseling. These are counts and denominators as recorded; they should not be confused with the primary endpoint sample sizes.

Miscarriage is listed among the top serious adverse-event terms at 3.3%. The registry does not give further detail about event timing, severity beyond the serious-event classification, or how events were attributed. Death counts are not reported in the registry record. The summaries describe recorded events in this study and do not by themselves establish that an intervention caused or prevented an event. Differences in observed counts should be interpreted cautiously, particularly without additional information about ascertainment and analysis.

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

The primary result describes an average difference in postpartum weight change between the randomized arms. The counseling arm’s mean change was lower than the usual-care arm’s, and the confidence interval is consistent with a negative between-arm difference under the posted analysis. This is a statement about the observed comparison, not a guarantee about an individual participant’s outcome.

The result does not establish why the group averages differed. The registry describes a dietary counseling program with in-person and group sessions, but the posted summaries do not show which elements participants received, how consistently the program was delivered, or which aspects might account for the difference. The comparison also does not establish a mechanism connecting weight change with the secondary birth outcome.

The record does not report a threshold for a clinically important difference, and statistical evidence alone cannot supply one. The confidence interval conveys uncertainty about the magnitude of the average difference, while the standard deviations indicate variation among participants. Neither statistic says that all participants experienced a change resembling the group mean.

Interpretation is also limited by information not reported in the registry record, including the original analysis plan, missing-data procedures, analysis population, and multiplicity approach. The posted secondary findings are unadjusted and should be treated cautiously. Safety counts describe the recorded events and do not demonstrate causation. The results can inform understanding of this randomized comparison, but the registry summaries alone do not resolve broader questions about applicability to people or settings beyond those represented in the trial.

17. Why This Trial Matters Statistically

This study illustrates how endpoint timing can shape what a clinical trial measures. The primary outcome is weight change through two weeks postpartum, rather than weight at an end point during pregnancy. The registry explicitly notes that pregnancy weight can include contributions from products of conception, maternal edema, and increased maternal blood volume. That rationale helps readers distinguish the targeted postpartum measure from pregnancy-period weight change.

It also shows why effect estimates, confidence intervals, and within-arm standard deviations answer different questions. The mean difference describes the contrast between average outcomes, the interval conveys uncertainty about that contrast, and the standard deviations describe participant-level spread. A small p-value does not replace any of these quantities or establish clinical importance.

The secondary outcomes demonstrate another interpretive challenge: multiple outcomes can make a consistent-looking pattern informative, while unadjusted tests and absent analysis details limit the strength of conclusions. The registry does not report a multiplicity strategy or the original analysis plan. Similarly, enrollment and outcome-summary counts are not identical, but the reasons are not documented. These are reminders that transparent reporting of analysis populations and missing-data handling is important for assessing trial results.

Finally, planning illustrations based on an observed effect are not the same as the study’s original design justification. They show how assumptions about effect size and target power affect participant requirements, but do not reveal what assumptions shaped the actual trial. Keeping these distinctions clear helps prevent statistical summaries from being interpreted more broadly than the record supports.

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.

The registry record leaves important design and analysis details unspecified. Although the study is described as randomized and single-masked, the masking role and randomization procedures are not reported in the registry record. Allocation concealment, if used, is also not described. The original sample-size rationale and planned statistical methods are not reported.

The primary outcome summaries include fewer participants than the enrollment total, but the record does not explain why. The missing-data approach and analysis population are not reported in the registry record, so it is not possible to determine how participants without posted outcome measurements were handled. This limits assessment of possible effects of attrition or exclusions.

The registry posts unadjusted secondary p-values and does not report a multiplicity strategy. It also lists no reported analyses for the secondary outcomes. Accordingly, the secondary findings warrant caution and cannot be placed within a fully documented analysis hierarchy. The registry does not give a clinically important difference threshold for the primary endpoint.

Outcome data are described as coming from a follow-up visit or validated clinical data, but details about measurement procedures, timing variation, or combining data sources are not reported. The safety summaries give event counts and at-risk denominators, but additional information about ascertainment, attribution, and event timing is not reported in the registry record. These limitations do not negate the posted results; they constrain how fully their methods and scope can be evaluated.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Weight Management for Improved Pregnancy Outcomes — NCT00950235.
• Registry record last updated 2015-07-09; status last verified 2015-06.
• Results first posted 2015-07-09.
• 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

The registry describes a completed randomized, single-masked, parallel-group study of weight-management counseling versus usual care in pregnant women with obesity. Enrollment was 118. The primary endpoint was mean maternal weight change from baseline to two weeks postpartum. The posted means were 1.2 kg for usual care and -2.6 kg for counseling, with a mean difference of -3.8 kg and a 95% confidence interval from -5.838 to -1.762 kg; the unadjusted p-value was <0.001.

The registry also posts pregnancy weight change and large-for-gestational-age outcomes. The posted secondary tests are unadjusted, and the original analysis plan, missing-data approach, analysis population, and multiplicity strategy are not reported in the registry record. Planning illustrations use stated assumptions and are not the trial’s original sample-size justification or observed power.