Effects of Calcium and Phytate on Zinc Absorption: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Effects of Calcium and Phytate on Zinc Absorption (NCT00754390), a randomized na study. The primary outcome is Zinc Absorption.

2. Clinical Question

3. Trial Design

This was a randomized factorial dietary study of four combinations of calcium and phytate: Moderate Calcium, Low Phytate; Moderate Calcium, High Phytate; High Calcium, Low Phytate; and High Calcium, High Phytate. Participants consumed each experimental diet for 4 weeks, with the diets taken in randomized order. The reported primary endpoint timeframe was 16 weeks, consistent with the stated sequence of four diet periods. The registry lists enrollment of 17.

The primary analysis population was restricted to women who completed all four treatment periods. The record does not separately state how many women met this criterion, nor does it explain how missing or incomplete periods were handled. Each diet’s posted endpoint summary lists n=10. Because participants consumed all four diets in randomized order, these summaries should not automatically be read as four independent parallel groups; the registry describes a repeated diet sequence. The precise structure used in the sponsor’s mixed model is not reported in the registry record.

Masking is listed as none, and allocation is listed as randomized. The record identifies the study as factorial but does not describe the randomization procedure or allocation concealment. The study status is completed, with start listed as 2005-11 and primary completion listed as 2006-05. The sponsor is the USDA Grand Forks Human Nutrition Research Center. No phase is applicable. The registry record does not report the original sample-size justification or the design assumptions used to plan enrollment.

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: 205 participants applied, 157 were eligible, 27 accepted invitation to attend an information meeting, 10 started study, 7 of the alternates joined study as original participants withdrew or were discharged.

Ca/Phytate Test Meal 1 (Randomized)

Reasons for not completing this period:

Ca/Phytate Test Meal 2 (Randomized)

Ca/Phytate Test Meal 3 (Randomized)

Reasons for not completing this period:

Ca/Phytate Test Meal 4 (Randomized)

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Analysis restricted to women who completed all 4 treatment periods

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 Zinc Absorption, measured over 16 weeks.

The primary endpoint, Zinc Absorption, is reported as the percentage of Zinc-65 absorbed. It is a continuous measure, summarized in the registry as a mean with standard error for each diet. The recorded timeframe is 16 weeks. The endpoint description says retention of Zinc-65 was monitored for 28 days using whole body scintillation counting. The percentage absorbed was estimated from the y-intercept of the linear portion of a semilogarithmic plot of percent Zinc-65 retained against time.

This measurement is used to quantify absorption through the observed retention pattern rather than relying only on dietary intake. As a general statistical point, a continuous endpoint preserves the scale of the measurement and allows summaries of average values and differences between diet conditions. The standard error describes uncertainty around an estimated mean; it is not the spread of individual observations. The registry does not provide individual-level measurements or standard deviations for the four summaries.

The posted means are 32.8 for Moderate Calcium, Low Phytate; 26.9 for Moderate Calcium, High Phytate; 39.4 for High Calcium, Low Phytate; and 26.2 for High Calcium, High Phytate. These are endpoint summaries for the stated completer population, not estimates of a broader clinical effect. The registry record does not report a minimally important difference or another threshold for judging the practical importance of a change in this endpoint.

7. Results Posted in the Registry

• Moderate Calcium, High Phytate Diet: mean 26.90 versus 32.80 on control; difference -5.90 (95% CI -12.42 to 0.62), standardized effect d = -0.79; z-test p = 0.076.
• High Calcium, Low Phytate Diet: mean 39.40 versus 32.80 on control; difference 6.60 (95% CI 0.08 to 13.12), standardized effect d = 0.89; z-test p = 0.047.
• High Calcium, High Phytate Diet: mean 26.20 versus 32.80 on control; difference -6.60 (95% CI -12.98 to -0.22), standardized effect d = -0.91; z-test p = 0.042.

8. Statistical Interpretation

9. Statistical Methods Explained

The registry identifies the design as randomized and factorial, with no masking. Participants consumed all four experimental diets in randomized order, each for 4 weeks. The endpoint is continuous and reported as a mean with standard error. Those details matter when interpreting the summaries: a randomized sequence of repeated diet periods is not the same structure as four unrelated groups, and the within-participant nature of the sequence can affect the appropriate uncertainty calculation. The registry says the sponsor used mixed models, but its model specification is not reported in the registry record.

What does a factorial design ask?

In general, a factorial design examines combinations of factors. Here, the diet combinations cross moderate or high calcium with low or high phytate. This structure can support questions about each factor and whether the factors act differently in combination. A comparison of one diet with another changes one or both components, so its interpretation depends on which combination is being compared. The registry provides three overall mixed-model p-values but does not identify the effect or contrast tested by each one. It does not report a specific interaction estimate.

What does a mixed model contribute?

In general, mixed models can represent both systematic treatment differences and dependence among observations, such as repeated measurements from the same participant. They can also accommodate certain unbalanced data structures, subject to their assumptions. The posted record names “Mixed Models Analysis” but gives no model formula, covariance structure, fixed or random effects, adjustment variables, or handling of incomplete periods. It is therefore not possible to reconstruct or fully assess the sponsor’s fitted model from the registry entry. The model label alone does not reveal which comparisons were tested or how the reported p-values relate to the four diet means.

What are the re-calculated comparisons?

The additional pairwise results are unadjusted re-calculations using posted summary statistics. They compare each of the three other diet means with Moderate Calcium, Low Phytate and report a mean difference, an interval, and an unadjusted p-value. “Unadjusted” means that the calculation does not account for multiple comparisons. These calculations are not a substitute for the sponsor’s mixed-model analysis, particularly because the record describes a randomized sequence in which participants consumed all four diets. The posted summary statistics do not provide the participant-level covariance information needed to verify a repeated-measures comparison independently.

The standard errors attached to the means describe uncertainty in each reported mean. They are not standard deviations and do not describe the full distribution of participants’ endpoint values. The re-calculation includes pooled standard deviations, but those values do not capture the repeated-measures correlation described by the study design. A simple comparison based on summary statistics can therefore be useful as a descriptive check without reproducing the sponsor’s analysis.

How should p-values be read?

As a general concept, a p-value measures how surprising data at least as extreme as those observed would be under a specified null hypothesis and analysis model. It is not the probability that the null hypothesis is true, and it does not quantify the size or importance of an effect. The re-calculated p-values are unadjusted: 0.076, 0.047, and 0.042. The sponsor’s mixed-model p-values are 0.17, < 0.001, and 0.09. Since the registry does not map the sponsor’s p-values to particular effects, these two sets should not be treated as direct duplicates or compared as though they answer an identical contrast.

When multiple comparisons are made, the chance of at least one small p-value can increase. General statistical practice may address this through a prespecified adjustment or a clearly defined hierarchy of tests. The registry does not report a multiplicity adjustment or a testing hierarchy. The pairwise re-calculations should consequently be read as exploratory, unadjusted comparisons rather than as a family-wise controlled set of tests.

What does the endpoint summary show?

The registry reports means and standard errors for each diet, with n=10 listed for each. The primary analysis is described as restricted to women completing all four periods. The record does not explain the relationship between these n values and the number of women in the completer population, so the n values should be understood as listed summaries rather than used to infer an unreported population count. No participant-level data are posted in the record.

The endpoint was estimated from Zinc-65 retention over 28 days, using the y-intercept of a linear portion of a semilogarithmic retention plot. This is the endpoint construction described by the registry; further details about assay procedures, quality control, or the selected plot segment are not reported in the registry record. As a general matter, endpoint definitions and measurement procedures determine what the numerical results represent. The posted percentages concern this specific Zinc-65 absorption measure under the experimental diets, rather than all dimensions of zinc status or health.

10. Confidence Intervals and Precision

Precision can be considered from the standard errors reported for each diet and the intervals attached to the pairwise re-calculations. The means are 32.8, 26.9, 39.4, and 26.2, with standard errors of 2.3, 2.4, 2.4, and 2.3, respectively. Standard errors indicate uncertainty in estimated means; they do not show the range of individual observations. The record does not provide standard deviations or participant-level data for assessing the distributions directly.

The re-calculated mean difference for Moderate Calcium, High Phytate versus Moderate Calcium, Low Phytate is -5.9, with an interval from -12.42 to 0.615. For High Calcium, Low Phytate versus the reference diet, the estimate is 6.6, with an interval from 0.085 to 13.12. For High Calcium, High Phytate versus the reference, the estimate is -6.6, with an interval from -12.98 to -0.225. The comparison intervals have no confidence level stated in the re-calculation fields. The registry does identify 95% confidence intervals for its mixed-model analyses, but it does not give those intervals’ endpoints.

In general, a confidence interval describes a range of effect estimates compatible with the data and the calculation’s assumptions. Wider intervals indicate less precision, and an interval that includes zero is compatible with both directions of a mean difference under that calculation. An interval excluding zero does not establish practical importance, nor does it resolve multiplicity or model concerns. The re-calculated intervals rely on summary-statistic assumptions and should not be mistaken for the sponsor’s mixed-model intervals. Those model-based effect estimates and interval bounds are not reported in the registry record.

11. 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 figures are participants per arm, not total event counts. The registry’s planning assumptions are a two-sided significance level of 0.05, equal allocation between two arms, a normal approximation, and an effect to detect set as a stated fraction of the observed effect. These are planning illustrations based on the observed effects, not the original trial’s documented design assumptions. The original sample-size justification is not reported in the registry record.

The 80% power column gives the planned number of participants per arm for an 80% chance of detecting the specified effect under those assumptions, if that effect and the assumptions are correct. The 90% power column gives the corresponding per-arm planning number for a 90% chance. These are prospective design calculations, not measures of what the completed study achieved.

The display considers planning for 100%, 75%, and 50% of the observed effect. For the Moderate Calcium, High Phytate comparison, the per-arm figures are 25 and 34 for planning at 100% of the observed effect, 45 and 60 for 75%, and 100 and 134 for 50%, for 80% and 90% power respectively. The other comparisons have their own listed figures. In general, planning for a smaller effect requires more participants, because a subtler difference is harder to distinguish from random variation. This is not observed power: it does not describe the probability that the completed trial detected an effect after the data were collected. The planning display does not reproduce the study’s original rationale for its enrollment or analysis population.

12. 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 = -5.900; pooled standard deviation σ = 7.433.
2. n = 2 × (1.96 + 0.842)² × 7.433² / -5.900² = 24.9, rounded up to 25 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 <- -5.9                      # observed difference in means
sigma <- 7.43303437365925                     # 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(754390)
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 = 25 (80% power), 34 (90% power)
 75% of observed effect: n per arm = 45 (80% power), 60 (90% power)
 50% of observed effect: n per arm = 100 (80% power), 134 (90% power)
power.t.test: 25.9 
Simulated power at n = 25 per arm: 0.788 (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.

13. Analyses Reported by the Sponsor

The registry reports three sponsor analyses using mixed models, with p-values 0.17, < 0.001, and 0.09. Each is marked as having a 95% confidence interval, but the effect estimates and interval bounds are blank. The record does not state which factorial effect or contrast corresponds to each p-value. As a result, those model results cannot be matched confidently to the three pairwise re-calculations.

The pairwise values are simple unadjusted re-calculations from posted group summaries. They compare each non-reference diet with Moderate Calcium, Low Phytate and produce p-values of 0.076, 0.047, and 0.042. They do not reproduce the sponsor’s reported mixed-model analysis and do not account for all features of the randomized sequence. Where the sponsor’s analysis and a re-calculation differ, the sponsor’s own analysis takes precedence as the trial’s reported analysis. The re-calculations are best treated as supplementary descriptive checks, not as replacements or a reconciliation of the model results.

Interpretation is constrained because the record does not provide the sponsor’s coefficients, exact tested hypotheses, model specification, or confidence interval bounds. It also does not report whether multiplicity was addressed. These omissions prevent a direct audit of the reported p-values or a clear account of the sponsor’s intended primary contrasts.

14. Multiplicity, Missing Data and Analysis Populations

The registry reports one primary outcome measure and three mixed-model analyses, but it does not state a multiplicity plan, adjustment method, or hierarchy of hypotheses. The three additional pairwise re-calculations are explicitly unadjusted. As a general statistical matter, testing multiple contrasts without adjustment can increase the chance of observing at least one small p-value even when no underlying differences exist. This concern does not determine the results, but it is relevant when interpreting several tests together. The record does not say whether the sponsor addressed this issue in an analysis plan outside the registry entry.

The primary analysis population is described as women who completed all four treatment periods. This is a completer analysis rather than a clearly described analysis of everyone randomized. The number of women included in that restricted analysis is not separately reported in the registry record. The record also does not describe missing-data methods, reasons for non-completion, adherence to each diet, or how partially observed treatment periods were handled. Therefore, the effect of missing or incomplete observations on the estimates cannot be assessed from this entry.

The registry lists enrollment of 17 and n=10 for each diet summary. It does not explain the relationship between these figures and the completer population. Since all four diets were consumed in randomized order, each participant’s repeated measurements may be related. The sponsor’s use of mixed models is recorded, but details needed to understand how repeated observations and any incomplete periods were modeled are not reported in the registry record.

The reported outcome is continuous and the registry gives means and standard errors. It does not provide distributions, diagnostic checks, sensitivity analyses, or a detailed analysis plan. The model’s assumptions and robustness therefore cannot be evaluated from the registry record. No secondary outcomes are posted. These gaps do not establish that analyses were inappropriate; they limit how fully the reported results and their sensitivity can be assessed.

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.

The registry’s adverse-event summary covers the Overall Study group. It lists 17 participants at risk for serious adverse events and 0 affected; for other adverse events it also lists 17 at risk and 0 affected. No serious adverse-event terms are listed. These figures describe what is entered in the registry record for this study, not a comprehensive assessment of all possible risks.

The deaths field is blank, so deaths are not reported in the registry record. A zero count for affected participants is not the same as evidence that no event could occur, and it does not address events that were not collected, not reported, or outside the registry’s definitions. The record does not provide adverse-event definitions, observation details, severity grading, or a diet-specific breakdown. It therefore does not support comparisons of safety among the four diets. These figures should be read as registry reporting, rather than as a general conclusion about the safety of any diet.

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

The registry reports a randomized study in which women who completed all four periods consumed four experimental diets in randomized order. The primary endpoint was the percentage of Zinc-65 absorbed, estimated from retention measurements. The posted means differed across diet combinations: 32.8 for Moderate Calcium, Low Phytate; 26.9 for Moderate Calcium, High Phytate; 39.4 for High Calcium, Low Phytate; and 26.2 for High Calcium, High Phytate. These values describe the endpoint summaries in the reported analysis population.

The sponsor’s mixed-model analysis is the registry’s reported analysis, but the p-values are not linked to named effects or contrasts, and no model estimates or interval bounds are entered. The pairwise re-calculations compare each other diet with Moderate Calcium, Low Phytate; they are unadjusted and should not be treated as equivalent to the sponsor’s model. The posted results therefore do not yield a fully specified account of which calcium or phytate effect the sponsor tested.

Statistical significance alone does not state whether a difference is important in practice. The registry does not report an interpretation threshold for the Zinc-65 absorption measure. Nor does this dietary endpoint establish effects on health outcomes, long-term nutritional status, or other populations. It is a measure of absorption under the experimental conditions described, in a completer population, and its reach should be understood accordingly.

The record also does not report the original sample-size rationale, multiplicity handling, detailed missing-data methods, or full model specification. Those omissions limit assessment of precision and robustness. The most defensible reading is descriptive: the posted endpoint means vary among diet combinations, and the registry records sponsor mixed-model p-values whose exact contrasts are unclear. The data do not, on their own, resolve the contribution of each diet component or establish a practical consequence.

17. Why This Trial Matters Statistically

This study is statistically interesting because its factorial structure combines two dietary factors across four conditions, while each participant consumed all four diets in randomized order. That design raises distinct questions about the main effects of calcium and phytate, their possible interaction, and the comparison of individual diet combinations. A single pairwise contrast does not answer all of these questions. The registry’s limited description of the mixed-model tests makes it especially important to distinguish the sponsor’s overall analysis from the supplementary pairwise re-calculations.

The repeated diet sequence also illustrates why the analysis structure matters. In general, measurements from the same participant may be correlated, and modeling that relationship can affect estimates and uncertainty. The registry names mixed models, but does not report enough detail to determine how the sequence or incomplete periods were represented. The re-calculations from group summaries are consequently useful as a check on the direction and scale of listed means, but cannot replace the sponsor’s model.

The endpoint provides a quantitative absorption measure rather than a broad clinical outcome. Its interpretation is tied to the Zinc-65 retention method and the completer population. The registry’s mean summaries and uncertainty estimates offer a way to describe observed variation, but the missing model estimates, interval bounds, and multiplicity plan limit a complete inferential account. The study therefore illustrates a broader lesson: design labels and p-values are not enough without clearly reported hypotheses, effect estimates, uncertainty, and analysis populations.

Finally, the planning illustrations show how the required sample size depends on the effect a future study aims to detect. Smaller target effects require more participants under the listed assumptions. Those illustrations are distinct from the original study’s design rationale, which is not reported in the registry record, and they should not be confused with evidence about the completed study’s power.

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 several trial-specific uncertainties. Although it labels the study factorial and reports three mixed-model p-values, it does not identify the particular effects or contrasts associated with those values. It also omits model estimates, interval bounds, model specification, and any interaction estimate. This prevents direct interpretation of the sponsor’s tests in terms of the four diet combinations.

The endpoint summaries list n=10 per diet, while the primary analysis is restricted to women completing all four periods and enrollment is listed as 17. The relationship among these figures is not explained. The registry does not report the number completing the full sequence, missing-data procedures, reasons for incomplete participation, adherence, or sensitivity analyses. As a result, the effects of incomplete periods and the composition of the analysis population cannot be assessed.

Only unadjusted pairwise re-calculations are available in addition to the sponsor’s model p-values. The registry does not report a multiplicity strategy or explain whether multiple testing was addressed in the sponsor’s analysis. The re-calculations use posted summary statistics and do not reproduce the repeated-measures model. Their intervals also have no stated confidence level in the re-calculation record.

The registry does not report the original sample-size justification, detailed randomization procedures, or measurement quality-control information. It posts no secondary outcomes. The adverse-event record gives overall counts but not diet-specific reporting or event definitions. These reporting limitations do not establish that the study procedures or analyses were deficient; they describe what cannot be assessed using the registry record.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Effects of Calcium and Phytate on Zinc Absorption — NCT00754390.
• Registry record last updated 2018-07-02; status last verified 2018-05.
• Results first posted 2009-06-08.
• 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

NCT00754390, titled “Effects of Calcium and Phytate on Zinc Absorption,” is a completed randomized factorial dietary study sponsored by the USDA Grand Forks Human Nutrition Research Center. Enrollment is listed as 17. Participants consumed four calcium-and-phytate diet combinations for 4 weeks each in randomized order.

The primary endpoint was the percentage of Zinc-65 absorbed, measured over the 16-week timeframe and analyzed among women who completed all four treatment periods. The registry reports four diet means with standard errors and three sponsor mixed-model p-values, but does not link those p-values to specified contrasts or provide model estimates and interval bounds. Supplementary pairwise re-calculations are unadjusted and do not replace the sponsor’s analysis. The record does not report the original sample-size justification, multiplicity plan, detailed missing-data methods, or full model specification.