The LIFE Study - Lifestyle Interventions and Independence for Elders: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for The LIFE Study - Lifestyle Interventions and Independence for Elders (NCT01072500), a randomized phase 3 study. The primary outcome is Major Mobility Disability, Defined as Incapacity to Walk 400 Meters.

2. Clinical Question

3. Trial Design

The LIFE Study was a Phase 3, randomized, parallel-group trial with single masking. It was sponsored by the University of Florida and is listed as completed. The registry records a start of 2010-02 and primary completion of 2013-12. Enrollment was 1,635, with 818 participants assigned to physical activity and 817 assigned to successful-aging education.

The physical activity arm combined moderate-intensity walking with lower-extremity resistance, balance, and stretching exercises, alongside behavioral counseling. The successful-aging arm received health education seminars and upper-extremity stretching. Thus, the trial compared two behavioral programs with different emphases. The registry does not report the identity of the masked party or provide further detail about how masking was maintained.

The brief summary describes a multicenter randomized controlled trial and says participants were followed for an average of 2.7 years. The primary outcome record gives a timeframe of median 2.7 years and average 2.6 years. Those descriptions are both recorded; the registry does not explain the difference between them. The primary aim was to assess long-term effects on major mobility disability, defined as inability to walk 400 meters.

The record lists persistent mobility disability, assessed every 6 months, as a secondary outcome. It reports outcome counts and Cox regression analyses for the primary and secondary outcomes. Details of the original sample-size rationale, allocation concealment, the full visit schedule, and the analysis populations are not reported in the registry record. The word randomized identifies the recorded allocation type, but does not by itself answer those additional design questions.

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.

Overall Study

Reasons for not completing this period:

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.

Population: Baseline characteristics were similar in the 2 groups.

6. Primary Endpoint

The registry lists the primary outcome as Major Mobility Disability, Defined as Incapacity to Walk 400 Meters, measured over Median 2.7 years/Average 2.6 years.

Major mobility disability was the primary endpoint. It captured whether a participant could complete a 400-meter walk within 15 minutes, without sitting and without help from another person or a walker. Cane use was acceptable. The walking assessment used a 20 meter course for 10 laps, with participants walking at their usual pace and permitted to stop for up to 1 minute for fatigue or related symptoms.

This endpoint focuses on a functional task rather than a laboratory measure. In older adults at risk of disability, the ability to walk a specified distance can represent an important aspect of mobility and independence. The registry’s definition also makes clear that the result depended on a task-based assessment, not simply a participant’s report of general activity.

When an objective 400-meter assessment could not be made because a participant could not attend the clinic and no suitable walking course was available at home, in an institution, or in a hospital, the outcome could be adjudicated using alternative criteria. These included objective inability to walk 4 meters in less than 10 seconds, or self-, proxy-, or medical-record-reported inability to walk across a room. The record explains that meeting those criteria indicated inability to complete the 400-meter test within 15 minutes. The registry does not report how often each assessment or adjudication route was used.

7. Results Posted in the Registry

• Successful Aging: 35.5% (290/817) versus 30.1% (246/818) on control; risk difference 5.4 percentage points (95% CI 0.9 to 10.0), risk ratio 1.18 (1.03–1.36); unadjusted two-proportion z-test p = 0.020.

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.

Persistent Mobility Disability (Assessed Every 6 Months)

• 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:
  • Successful Aging: 19.8% (162/817) versus 14.7% (120/818) on control; risk difference 5.2 percentage points (95% CI 1.5 to 8.8), risk ratio 1.35 (1.09–1.68); unadjusted two-proportion z-test p = 0.006.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for Successful Aging than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The posted secondary result follows the same broad direction as the primary finding: the reported Cox hazard ratio is below 1, and the recorded event counts are lower in the physical activity arm than in the successful-aging arm. This directional agreement is useful as context because persistent mobility disability is related to the trial’s central concern with mobility. It does not make the secondary outcome an independent confirmation of the primary result.

The secondary endpoint is persistent mobility disability, assessed every 6 months. Its definition and analysis are related to the primary mobility outcome, so the outcomes may not represent wholly separate evidence. The record reports a hazard ratio of 0.72, with a 95% confidence interval from 0.57 to 0.91 and p=0.006. The endpoint-level counts and interpretation belong with the posted outcome results and need not be repeated to understand the overall pattern.

Secondary outcomes often have less confirmatory weight because a study may examine several outcomes, time points, or analyses. If no multiplicity adjustment or prespecified hierarchy is reported, a nominal p-value does not show that the chance of a false-positive finding across all analyses has been controlled. The registry does not report such procedures or describe whether this outcome had a confirmatory role.

Accordingly, the secondary result can be described as directionally consistent with the primary result, while retaining more caution about its evidential status. Similarity between related endpoints can reflect a coherent pattern, but it can also mean the results are correlated rather than independent. The registry does not report enough detail to quantify that relationship or establish how the secondary analysis was prioritized in the trial’s original plan.

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

• Persistent Mobility Disability (Assessed Every 6 Months)

9. Statistical Interpretation

10. Statistical Methods Explained

The posted results combine event counts with a reported time-to-event analysis and simple recalculations from the counts. Each approach answers a related but not identical statistical question. Understanding the distinction helps avoid treating the estimates as interchangeable.

What do the event counts describe?

The primary outcome is binary at the participant level in the posted counts: a participant is counted as having major mobility disability or not. The record lists 246 events among 818 participants in physical activity and 290 among 817 in successful aging. These counts give a direct account of the recorded outcomes by randomized arm. A count comparison does not, on its own, convey when an event occurred, how long each participant was observed, or how censoring was handled.

The recalculated risk difference expresses the difference between the event proportions in the comparison groups. A positive difference, with the registry’s contrast defined as successful aging against physical activity, corresponds to a greater event proportion in the successful-aging group. The recalculated relative risk compares those proportions as a ratio, and the odds ratio compares the event odds. These measures use the posted counts and are unadjusted. They can be useful descriptive summaries, but they do not reproduce a model that accounts for follow-up time.

What does the Cox analysis estimate?

The sponsor reports regression using a Cox method and gives a hazard ratio. In general, a Cox model compares the instantaneous event rate between groups over follow-up, conditional on the model’s structure. It uses information about event timing and can incorporate censored follow-up. A hazard ratio is not the same as a risk difference, a risk ratio, or a probability that a participant will experience the outcome. The registry reports the method and estimates but does not give the model specification, covariate set, proportional-hazards assessment, or details of censoring.

For a hazard ratio, a value of 1 represents equal hazards under the specified contrast. Values on either side indicate a relative difference whose direction depends on which group is in the numerator. The registry lists the groups as physical activity and successful aging, but does not separately describe the coding convention. The estimate should therefore be read together with the listed group comparison and the observed event pattern, without assuming unreported model details.

How should the p-values be read?

A p-value describes how incompatible the observed data are with a specified null model, under the assumptions of the analysis. It is not the probability that the null hypothesis is true, and it does not measure the size or practical importance of an effect. The sponsor’s primary p-value is 0.03. The recalculated, unadjusted p-value is 0.02. Their difference is not inherently a contradiction: the analyses differ in method and in the information used. The registry does not report a broader statistical analysis plan that would explain the prespecified role of each analysis.

The secondary Cox result has p=0.006. A smaller p-value does not automatically make a secondary endpoint more important than the primary endpoint. The number and relationship of outcomes tested, the analysis plan, and the level of evidence intended for each outcome matter. Multiplicity procedures are not reported in the registry record, so the posted secondary p-value should be read as an unadjusted result unless further information establishes otherwise.

What does a confidence interval contribute?

A confidence interval gives a range of estimates compatible with the data under the model and its assumptions. It communicates precision as well as direction. A narrower interval generally indicates greater precision, while a wider interval indicates more uncertainty about the effect’s magnitude. A confidence interval is not a guarantee that the true effect falls inside its particular limits, and it does not account for limitations such as an incorrectly specified model or missing information.

The sponsor’s 95% confidence interval for the primary hazard ratio is 0.69 to 0.98. Its limits are both below 1, consistent with the reported p-value for that model. The interval nevertheless includes a range of possible relative hazard contrasts, so the point estimate should not be treated as exact. The registry does not provide confidence intervals for the simple recalculated risk difference in a form used for the sponsor’s Cox analysis; the two types of estimates should remain distinct.

Why do the planning illustrations vary by effect size?

Sample-size calculations translate an assumed effect and statistical design into a planning number. The illustrations use the observed effect as a reference and also consider smaller fractions of that effect. If the effect to detect is smaller while other assumptions are held constant, more participants are generally needed to distinguish it from random variation. The figures are planning illustrations based on stated assumptions, not a reconstruction of the trial’s original design.

The record states a two-sided significance level of 0.05, equal allocation between arms, and a normal approximation. The target effect is the stated fraction of the observed effect. For the time-to-event calculations, the displayed requirement is a total number of events using the Schoenfeld method; for other calculations, it is participants per arm. The trial’s own original design assumptions and sample-size justification are not reported in the registry record.

Over-dispersion matters in outcomes where variability exceeds what a simple probability model assumes, because standard errors can otherwise be too small. It is not a feature to infer from these binary participant counts, and no over-dispersion estimate is reported. More generally, analysis assumptions should be distinguished from details observed in a trial: the estimates are model-based, and the registry record does not report enough detail to assess every assumption.

11. Confidence Intervals and Precision

Precision concerns how tightly the data and analysis constrain an estimate. The sponsor’s primary hazard ratio is 0.82, with a 95% confidence interval from 0.69 to 0.98. The interval spans values that imply different magnitudes of relative hazard contrast. Its upper limit is close to 1, so the reported estimate is compatible with a more modest contrast as well as with a larger one within the interval. The p-value is 0.03, but the interval gives more information about the range of estimates than the p-value alone.

The confidence interval is conditional on the Cox model and the analysis assumptions. It does not capture every source of uncertainty, including uncertainty created by missing data, unreported choices in model specification, or limits on generalizability. The registry does not provide the information needed to assess all of those sources. Nor should the interval be translated into certainty about the outcome for an individual participant.

The primary event counts are 246 of 818 and 290 of 817. The groups are similar in size, but the statistical precision still depends on the number and timing of events, follow-up, and analysis method. A time-to-event interval and an interval for an unadjusted difference in event proportions would not have the same interpretation. The reported confidence interval belongs to the sponsor’s hazard-ratio analysis; it should not be attached to the separate count-based recalculation.

The secondary hazard ratio is 0.72, with a 95% confidence interval from 0.57 to 0.91. It is also an estimate with uncertainty, not an exact measure of effect. Since multiplicity handling is not reported, its interval should not be interpreted as if it necessarily accounts for examining multiple outcomes. Precision in a statistical sense does not resolve questions about prespecification, data completeness, or the appropriateness of a model.

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 figures are illustrations based on the observed effect, not the trial’s original design calculation. For the time-to-event calculations, the required quantity is the total number of events, using the Schoenfeld method. For the other calculations, the figures are participants per arm. The assumptions listed are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation; the effect to detect is the stated fraction of the observed effect. The trial’s own original design assumptions and sample-size justification are not reported in the registry record.

The 80% power column gives the planned number of participants per arm, or total events for time-to-event calculations, associated with an 80% chance of detecting the assumed effect under the calculation’s assumptions if that effect is real. The 90% power column gives the corresponding requirement for a 90% chance. These are design concepts, not guarantees that a future study will obtain a statistically significant result. Actual power depends on the effect, event occurrence, follow-up, and whether the planning assumptions hold.

The rows use the observed effect and smaller fractions of it. As the assumed effect becomes smaller, the planning requirement increases. That relationship is expected: smaller differences are harder to distinguish from random variation, so they require more information. The displayed values should be read as conditional planning quantities, not as evidence about the probability that the completed trial found an effect. This is not observed power.

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, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.301; treatment proportion p₁ = 0.355; average p̄ = 0.328.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6639 = 1.3012.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6628 = 0.5578.
4. n = (1.3012 + 0.5578)² / (0.0542)² = 1,175.3, rounded up to 1,176 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
p0 <- 0.300733496332518                          # control proportion
p1 <- 0.354957160342717                          # treatment proportion
n_per_arm <- function(power, frac = 1) {
  q1 <- p0 + (p1 - p0) * frac               # smaller effect = fraction of the observed difference
  pbar <- (p0 + q1) / 2
  z_b <- qnorm(power)
  ceiling(round((z_a * sqrt(2 * pbar * (1 - pbar)) + z_b * sqrt(p0 * (1 - p0) + q1 * (1 - q1)))^2 / (q1 - p0)^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 (unrounded n per arm)
cat("power.prop.test:", round(power.prop.test(p1 = p0, p2 = p1, power = 0.80)$n, 1), "\n")

# Simulation: how often does the z-test reject at the 80%-power sample size?
set.seed(1072500)
n    <- n_per_arm(0.80)
reps <- 20000
x0 <- rbinom(reps, n, p0); x1 <- rbinom(reps, n, p1)
ph <- (x0 + x1) / (2 * n)
z  <- ((x1 - x0) / n) / sqrt(ph * (1 - ph) * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE), reps))

Output from running the code

100% of observed effect: n per arm = 1,176 (80% power), 1,573 (90% power)
 75% of observed effect: n per arm = 2,068 (80% power), 2,768 (90% power)
 50% of observed effect: n per arm = 4,602 (80% power), 6,160 (90% power)
power.prop.test: 1175.3 
Simulated power at n = 1,176 per arm: 0.800 (20000 replicates)

The simulation draws many pairs of event counts at the planned sample size and counts how often the two-proportion z-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. Analyses Reported by the Sponsor

The sponsor’s primary result is a Cox regression hazard ratio of 0.82, with a 95% confidence interval from 0.69 to 0.98 and p=0.03. The registry identifies the analysis method as regression, Cox. This is the sponsor’s reported time-to-event analysis and should be distinguished from the recalculation made directly from the posted event counts.

The count-based recalculation compares the recorded number of participants with an event in each arm and is unadjusted. Its p-value is 0.02. It does not use the event-time information in the same way as a Cox model, and the registry does not report the sponsor model’s full specification. The estimates therefore need not match exactly or have identical interpretations. The registry record does not flag a discrepancy between the posted results and the recalculation.

The sponsor’s own analysis takes precedence as the reported trial analysis. The recalculation serves as a transparent, simple comparison of the posted counts, not a correction or replacement. The registry does not report whether the sponsor’s model adjusted for covariates, how missing observations were handled, or whether the analysis population followed an intention-to-treat definition.

15. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when investigators evaluate more than one outcome, comparison, subgroup, or analysis. Even if each individual test uses a conventional significance threshold, examining many tests can increase the chance that at least one result appears statistically significant by chance. Researchers may address this through a prespecified outcome hierarchy, adjustment procedures, or a clearly stated distinction between confirmatory and exploratory analyses.

The registry lists a primary outcome and a secondary outcome, with reported analyses for both. It does not report a multiplicity adjustment, a testing hierarchy, or the full statistical analysis plan. Therefore, the primary analysis has the clearest stated priority in the record, while the secondary result should be treated more cautiously. The record does not establish that the secondary result was adjusted for the presence of other analyses.

Missing-data handling is also not reported. The registry gives arm sizes and event counts, but does not describe whether all randomized participants were included in each analysis, how participants without an assessable outcome were handled, or how censoring and loss to follow-up were addressed. A reported count is not enough to determine whether missingness was rare, balanced between arms, or potentially related to outcome status.

The analysis populations are not reported in the registry record. It is therefore not possible from this record alone to determine whether the primary estimate used all randomized participants, a modified intention-to-treat group, or another population. The registry also does not report protocol deviations, sensitivity analyses for missing outcomes, interim analyses, or stopping rules. These omissions do not establish that such procedures were absent; they mean their details cannot be assessed from the registry record.

16. 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 0% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: surgical and medical procedures - other, specify (9.1%), fall (3.8%), general disorders and administration site conditions - other, specify (3.8%), neoplasms benign, malignant and unspecified (incl cysts and polyps) - other, specify (2.9%), atrial fibrillation (2.8%).

The registry lists 404 participants affected by serious adverse events among 818 at risk in the physical activity arm, and 373 among 817 at risk in the successful-aging arm. It also lists other adverse events affecting 181 among 818 in physical activity and 88 among 817 in successful aging. These figures should be read as the posted counts of participants affected, not as a complete account of event severity, timing, or attribution.

The listed serious-event terms include surgical and medical procedures, falls, general disorders and administration-site conditions, neoplasms, atrial fibrillation, and stroke. The registry gives percentages for these terms, including 9.1% for surgical and medical procedures and 3.8% for falls. The record does not explain the denominator or provide sufficient detail to determine whether the terms are mutually exclusive, how multiple events in one participant were counted, or whether events were judged related to an intervention.

Deaths are not reported in the adverse-event record. These figures cannot by themselves establish comparative safety or causation. They should be interpreted alongside the trial’s event definitions and reporting context, details that are not fully described in the registry record.

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

The results describe a randomized comparison of a structured physical activity program with successful-aging health education among sedentary older adults. The primary outcome was a defined measure of major mobility disability, and the sponsor reported a Cox analysis with a hazard ratio of 0.82 and a 95% confidence interval from 0.69 to 0.98. The posted event counts show fewer participants with the primary event in the physical activity arm than in the comparison arm.

These findings do not mean that every participant in the physical activity group avoided mobility disability, or that every participant in the comparison group experienced it. Group-level estimates describe patterns across participants; they do not determine an individual outcome. Nor do the data establish that the intervention caused every difference, independent of the trial’s assumptions, conduct, and analysis.

The result is specific to the population enrolled, the intervention programs as implemented in the trial, the comparison program, and the registry’s endpoint definition. Details such as age eligibility criteria, adherence, intervention exposure, and representativeness are not reported in the registry record. Generalizing beyond the enrolled group or to other versions of physical activity or education requires information beyond these posted results.

The statistical evidence also has limits. The sponsor’s estimate is model-based, and the record does not provide the full Cox model specification or missing-data methods. The unadjusted recalculation is a separate summary rather than a substitute for the sponsor analysis. The secondary result is related to the primary outcome and multiplicity handling is not reported. These points do not erase the observed pattern; they define what can and cannot be concluded from the registry record alone.

Statistical significance is not a direct measure of clinical importance. The record does not provide a threshold for a meaningful difference or a full assessment of benefits and burdens. The appropriate reading is therefore descriptive and bounded: the posted analyses indicate a group contrast in mobility outcomes, with uncertainty and reporting limitations that should remain part of the interpretation.

18. Why This Trial Matters Statistically

This trial is statistically informative because it compares two behavioral programs in a randomized parallel-group design and evaluates a functional endpoint over follow-up. The endpoint is tied to a concrete walking task with explicit completion and adjudication criteria. Such definitions matter: statistical comparisons are meaningful only when the outcome being counted is sufficiently specified.

The record also illustrates why a time-to-event result and a simple comparison of event counts should not be conflated. The sponsor’s Cox analysis incorporates event timing in a way that a basic binary comparison does not. The two approaches offer different summaries of the data, and differences between their estimates or p-values can arise because they address different statistical quantities.

Reporting both an estimated effect and a confidence interval supports interpretation beyond a significance label. The primary hazard ratio and its interval communicate a relative contrast and its precision under the reported model. The posted counts help readers connect that model-based result to the numbers of participants recorded with events in each arm.

The study also provides an example of the limits of registry reporting. The record contains a primary analysis and a secondary analysis but does not report the full analysis plan, multiplicity procedures, missing-data approach, or original design assumptions. Those omissions affect how confidently readers can assess prespecification, robustness, and the intended inferential role of each result. Statistical interpretation therefore depends both on the numerical estimates and on the completeness of the methods record.

19. 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 trial-specific details needed for a fuller assessment are not reported in the registry record. These include eligibility cutoffs and further participant characteristics, intervention adherence and exposure, the identity of the masked party, allocation-concealment procedures, and details of sites and recruitment. The brief summary describes a multicenter study, but does not provide site-level information in the posted record.

The record does not report the original sample-size justification or the trial’s design assumptions. The planning illustrations are separate calculations based on the observed effect and stated assumptions; they cannot establish what effect the trial was originally designed to detect. The record also does not report an interim-analysis plan, stopping rules, or a complete statistical analysis plan.

For the primary Cox analysis, the covariates, model specification, proportional-hazards assessment, censoring details, and analysis population are not reported. Missing-outcome handling and sensitivity analyses are likewise not described. The registry’s primary outcome timeframe gives median 2.7 years and average 2.6 years, while the brief summary describes an average of 2.7 years; the record does not explain these different descriptions.

Finally, the adverse-event record does not provide enough detail to assess attribution, event timing, repeated events, or the denominator behind every listed event-term percentage. The death field contains no reported value. These limitations concern the detail available in the registry record and should not be taken as evidence that a particular procedure or analysis was not conducted.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: The LIFE Study - Lifestyle Interventions and Independence for Elders — NCT01072500.
• Registry record last updated 2018-05-07; status last verified 2018-04.
• Results first posted 2016-04-18.
• 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.

23. Record Summary

The LIFE Study is a completed, Phase 3 randomized parallel-group trial sponsored by the University of Florida, with enrollment of 1,635 sedentary older adults. It compared a moderate-intensity physical activity program with successful-aging health education. The primary outcome was major mobility disability, defined around inability to complete a 400-meter walk. The registry reports a Cox hazard ratio of 0.82, with a 95% confidence interval from 0.69 to 0.98 and p=0.03, alongside participant event counts for both arms.

Persistent mobility disability was listed as a secondary outcome, and its reported Cox result followed the same broad direction. The record includes adverse-event counts but does not report the full analysis plan, missing-data procedures, multiplicity handling, original sample-size rationale, or several model details. Interpretation should distinguish the sponsor’s time-to-event analysis from unadjusted recalculations and keep the reported uncertainty and registry limitations in view.