Abstract
BACKGROUND
Walking independently is basic to human functioning. The Lifestyle Interventions and Independence for Elders (LIFE) studies were developed to assess whether initiating physical activity could prevent major mobility disability (MMD) in sedentary older adults.
METHODS
We review the development and selected findings of the LIFE studies from 2000 through 2019, including the planning phase, the LIFE‐Pilot Study, and the LIFE Study.
RESULTS
The planning phase and the LIFE‐Pilot provided key information for the successful implementation of the LIFE Study. The LIFE Study, involving 1635 participants randomized at eight sites throughout the United States, showed that compared with health education, the physical activity program reduced the risk of the primary outcome of MMD (inability to walk 400 m: hazard ratio = 0.82; 95% confidence interval = 0.69‐0.98; P = .03), and that the intervention was cost‐effective. There were no significant effects on cognitive outcomes, cardiovascular events, or serious fall injuries. In addition, the LIFE studies provided relevant findings on a broad range of other outcomes, including health, frailty, behavioral outcomes, biomarkers, and imaging. To date, the LIFE studies have generated a legacy of 109 peer‐reviewed publications, 19 ancillary studies, and 38 independently funded grants and clinical trials, and advanced the development of 59 early career scientists. Data and biological samples of the LIFE Study are now publicly available from a repository sponsored by the National Institute on Aging (https://urldefense.proofpoint.com/v2/url?u=https-3A__agingresearchbiobank.nia.nih.gov&d=DwMFAg&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=ZX4a6hcfLVk9tpCPmkSujQ&m=iTPARxl_LBOimJoAcWK4efKQBWBHszm-g4mUN_o5-bc&s=SrlCccrcYCFSyWnnprcB3rJXT3W3FkGkW0XmdJITNhE&e=).
CONCLUSIONS
The LIFE studies generated a wealth of important scientific findings and accelerated research in geriatrics and gerontology, benefiting the research community, trainees, clinicians, policy makers, and the general public. J Am Geriatr Soc 68:872–881, 2020
Keywords: aging, mobility disability, multicenter trialphysical activity
Abstract
See related editorial by https://doi.org/10.1111/jgs.16374. in this issue.
Walking independently is basic to human functioning. Those who are unable to walk without help are at higher risk of acute and chronic health conditions, disability, hospital admission, institutionalization, and mortality.1, 2 Being able to walk a quarter of a mile, or 400 m, is of pivotal importance for preserving an independent and a high quality of life.3, 4 Epidemiologic studies and smaller clinical trials have shown that engaging in physical activity is associated with several health and functional benefits. However, at the time the Lifestyle Interventions and Independence for Elders (LIFE) Study was planned, it was uncertain whether initiating regular physical activity might avert the risk of major mobility disability (MMD; inability to walk 400 m).
1. DEVELOPMENT OF THE LIFE STUDIES
The LIFE studies started in year 2000 based on the recognition that there was no conclusive evidence from clinical trials demonstrating that the risk of mobility disability, a major problem for older persons, could be reduced (Figure 1). In 2001, the team received a grant (R21AG19353) to plan a definitive trial with intensive preliminary work involving expert discussions, planning meetings, secondary data analyses of existing cohort studies, and pilot studies,5 including a study that demonstrated the feasibility of recruiting the target population.6
At the end of the planning phase, structured regular physical activity was the most promising intervention to reduce the risk of mobility disability and a pilot study was needed to refine key aspects to ensure the full success of a main larger clinical trial. In the LIFE‐Pilot Study, a total of 424 sedentary older persons who were at risk for disability were randomized at four clinical sites to a structured moderate‐intensity physical activity intervention compared with a health education intervention and were followed for 1 to 1.5 years (average = 1.2 years) (U01AG022376, 2003‐2009).7 After its conclusion, the LIFE‐Pilot Study8 provided key information and resources for planning the LIFE Study, including the following:
Demonstrated that the primary outcome of MMD, defined as inability to walk 400 m at usual pace, was valid8 and statistically efficient9;
Developed the primary outcome adjudication procedures for participants not able to come to the clinic;
Refined the target population who is at risk of MMD;
Estimated the incidence of MMD in the health education control group to estimate the sample size for the LIFE Study8;
Showed that older persons who are sedentary, have impaired physical function, and are at high risk of disability can be successfully recruited, can be retained, and will adhere to a structured physical activity program10;
Developed a successful physical activity intervention and a medical safety protocol to reinitiate activity after illness events8;
Demonstrated the acceptability and feasibility of the attention control group through a “Successful Aging” health education program;
Established the internal validity of the intervention by demonstrating its benefits on statistically significant and clinically meaningful improvements of the Short Physical Performance Battery (SPPB) and the 400‐m walking speed, which were both prespecified outcomes (Table 1)8, 11; and
Established the multicenter structure and quality control procedures for LIFE.
Table 1.
Outcomes | Unit | Baseline | Follow‐Up Time Point, mo | PA | HE | P Value |
---|---|---|---|---|---|---|
400‐m walk self‐efficacy | Score | 73.3 | 6 | 77.8 | 67.6 | <.001 |
400‐m walk self‐efficacy | Score | 73.3 | 12 | 73.5 | 67.2 | .005 |
Satisfaction with physical functioning | Score | 0.3 | 6 | 1.1 | 0.6 | .001 |
Satisfaction with physical functioning | Score | 0.3 | 12 | 0.9 | 0.6 | .006 |
Sedentary time | Min | 647 | 6 | 630 | 639 | <.001 |
IL‐6 biomarkera | pg/mL | 2.54 | 6 | 2.60 | 2.84 | .02 |
IL‐6 biomarkera | pg/mL | 2.54 | 12 | 2.48 | 2.69 | .02 |
SPPBa | Score | 7.5 | 6 | 8.7 | 8.0 | <.001 |
SPPBa | Score | 7.5 | 12 | 8.5 | 7.9 | <.001 |
400‐m walk speeda | m/s | 0.86 | 6 | 0.87 | 0.84 | <.001 |
400‐m walk speeda | m/s | 0.86 | 12 | 0.85 | 0.82 | <.001 |
Cognitive function | Mean global composite z score | 24 | −0.052 | −0.081 | .40 | |
Hippocampal volume, left (n = 24) | Voxels | PA = 3.57HE = 3.46 | 24 | 3.83 | 3.60 | .026 |
Abbreviations: HE, health education; IL, interleukin; PA, physical activity; SPPB, Short Physical Performance Battery.
Lifestyle Interventions and Independence for Elders‐Pilot.
Based on the successes achieved with the LIFE‐Pilot, the LIFE Study, which was investigator initiated, was funded in September 2009 (U01AG022376; Figure 1). The LIFE Study was a phase 3 randomized clinical trial to determine whether a structured moderate‐intensity physical activity program is more effective than health education in preventing the onset of MMD, defined as inability to walk 400 m. Secondary outcomes included cognitive function; serious fall injuries; persistent MMD; the combined outcome of MMD or death; and cost‐effectiveness. Tertiary outcomes included the combined outcome of mild cognitive impairment or dementia, a composite measure of the cognitive assessment battery, physical performance within prespecified subgroups, and cardiovascular events.
Recruitment began in February 2010 and ended in December 2011, 2 months ahead of schedule. Study participants were recruited from urban, suburban, and rural areas at eight clinical centers in the United States. Participants were sedentary men and women, aged 70 to 89 years, who had an SPPB score of less than 10, but were able to walk 400 m. We randomized 1635 participants, who were followed through December 2013, for an average of 2.6 years (range = 2‐4 years).12 As in the pilot study,7 the two LIFE Study interventions included a structured, moderate‐intensity physical activity program (n = 818) involving aerobic, resistance, and flexibility training (twice per week center based and 3‐4 times per week home based) and a health education program (n = 817) with workshops/lectures on topics relevant to older adults and upper extremity stretching.13
Here we summarize selected findings from the LIFE studies on a broad range of outcomes, including major health, frailty, cost‐effectiveness, behavioral, biomarkers, and imaging. Finally, we outline the legacy of the LIFE studies.
2. MAJOR HEALTH OUTCOMES
The LIFE Study showed that, compared with the health education program, the physical activity program:
Reduced the risk of the primary outcome of first occurrence of MMD (hazard ratio [HR] = 0.82; 95% confidence interval [CI] = 0.69‐0.98; P = .03), of persistent MMD (HR = 0.72; 95% CI = 0.57‐0.91; P = .006), and of the combined outcome of MMD or death (HR = 0.82; 95% CI = 0.70‐0.97; P = .02; Figures 2 and 3)14; the benefit of physical activity on MMD was particularly evident among participants who were more physically impaired at baseline, with an SPPB score of less than 8 (HR = 0.75; 95% CI = 0.60‐0.94; Figure 2)14;
Was associated with nonsignificantly higher serious adverse events (risk ratio [RR] = 1.08; 95% CI = 0.98‐1.20;
Reduced the MMD burden over an extended period of time, yielding an RR of 0.75 (95% CI = 0.64‐0.89; Figure 3)15;
Did not produce significant effects on global or domain‐specific cognitive function (Table 1),16 the combined outcome of mild cognitive impairment or dementia (Figure 3),16 cardiovascular events (Figure 3),17 or serious fall injuries (Figure 3)18; power to detect only large effects may partially explain these results; and
One year after cessation of the interventions, the two groups reported similar levels of physical activity, suggesting that a continued behavioral intervention is needed to sustain higher levels of physical activity.19 National Institutes of Health (NIH) applications to further extend follow‐up of the LIFE cohort did not achieve a fundable score.
3. FRAILTY
In the LIFE‐Pilot, the physical activity intervention reduced the 12‐month prevalence of frailty compared with health education (10.0% [95% CI = 6.5% to 15.1%] vs 19.1% [95% CI = 13.9%‐15.6%]; P = .01),20 when frailty was defined with the Fried criteria.21 Among these frailty criteria, sedentary behavior was the one most affected by the intervention. Similar results were found in the larger LIFE Study (A. Trombetti, 2017, unpublished data). The Fried criteria may not be appropriate for the frailty outcome in LIFE because they include self‐reported low physical activity. When frailty was defined according to the Study of Fractures criteria,22 which do not include low physical activity, the effect of physical activity on frailty in the LIFE Study was not statistically significant (Table 1).23
4. COST‐EFFECTIVENESS
Over 2.6 years of follow‐up, the average LIFE intervention cost per participant was $3302 for the physical activity group and $1001 for the health education group.24 Compared to health education, physical activity accrued incremental cost‐effectiveness ratios of $42 376 per MMD prevented and $49 167 per quality‐adjusted life year (QALY) gained. These costs per QALY gained are comparable to those found in other studies for many commonly recommended medical treatments, such as, for example, similar to the inflation‐adjusted (35%) figure of $42 541/QALY found in the Diabetes Prevention Program study.24
5. BEHAVIORAL OUTCOMES
In the LIFE‐Pilot, participants randomized to the physical activity intervention improved self‐efficacy for a 400‐m walk and satisfaction with physical functioning (Table 1).25
Disproportionate amounts of sedentary time, independent of the total amount of physical activity engaged in, are associated with a broad range of adverse health outcomes. In the LIFE Study, compared with health education, the physical activity intervention was associated with a small, but statistically significant, reduction in sedentary time measured by accelerometry.26 However, at 6 months of follow‐up, the group difference was only 9 min/d (630 vs 639 minutes; P = .002), suggesting that specific interventions are needed to achieve major reductions in sedentary behaviors (Table 1).
6. BIOMARKERS
In the LIFE‐Pilot, compared with health education, physical activity resulted in lower plasma interleukin‐6 (2.48 vs 2.69 pg/mL; P = .02; Table 1).27 This effect was more evident in participants with an SPPB score of less than 8 (2.44 vs 3.06 pg/mL; P = .005).
In the LIFE‐Pilot, the endogenous peptide apelin was positively correlated with SPPB score increases with physical activity (r 2 = 0.34; P = .0001).28
A replication and meta‐analysis of the LIFE‐Pilot, LIFE, and the Health, Aging, and Body Composition cohort identified several mitochondrial DNA (mtDNA) variants that are associated with variation in walking speed.29 Another analysis of the LIFE‐Pilot and LIFE studies identified mtDNA‐encoded variants that are associated with variations in systolic and mean arterial pressure.30
7. IMAGING
In a subset of the LIFE‐Pilot (n = 42), the physical activity intervention almost completely averted the midthigh skeletal muscle intermuscle fat infiltration that occurred in the health education group after 12 months (Table 1).31 In another LIFE‐Pilot subgroup (n = 27) who underwent functional magnetic resonance imaging 2 years after completion of the interventions, participants who were randomized to physical activity and who reported greater physical activity had higher brain activation within regions important for processing speed compared with those randomized to health education who remained sedentary.32
In a LIFE Study subset (n = 24), the physical activity group had a significantly larger left hippocampal volume compared with the health education group (3.83 vs 3.60 voxels; P = .026) after 2 years of intervention (Table 1).33
8. CHALLENGES
The implementation of the LIFE studies faced several challenges in developing a definitive study for the prevention of mobility disability. Below is an outline of the main factors that investigators had to resolve to successfully implement the LIFE Study.
8.1. Selection of Clinical Sites
The key criteria for selecting the study sites were (1) a track record of successfully recruiting from the community and retaining older persons who are at risk of disability; (2) a track record of delivering physical activity interventions; (3) expertise in randomized clinical trials, geriatric outcomes, exercise physiology, and behavioral interventions; (4) resources to conduct the physical activity walking interventions and the assessments; and (5) ability to work in a multidisciplinary team environment.
8.2. Primary Outcome
Early on, we faced the decision of whether to use a self‐reported mobility disability outcome or an objective outcome. We decided that for a study this large and important we could make a much stronger case to the general medical community and the public if we had an objective, standardized outcome. The National Institute on Aging (NIA) also advocated for an objectively measured outcome for a multicenter study of that size.
The choice of the primary outcome to operationalize mobility disability represented a major challenge. MMD,13, 14 defined as inability to walk 0.25 miles or 400 m, was measured in the LIFE‐Pilot and was our preferred primary outcome for the main trial. MMD is of major public health significance. Ability to walk 0.25 miles is measured in the US census34 and in most epidemiologic surveys.35 The MMD outcome, based on the 400‐m walk test, is a feasible, objective, reliable,5 well‐validated, and important clinical and public health outcome in older people,2, 13, 14 which we successfully implemented in the LIFE‐Pilot and LIFE.36, 37 We have shown it to be a more efficient outcome for clinical trials than self‐reported disability or the SPPB.9 Public health agencies use ability to walk 0.25 miles or 400 m to define need and policy impact of interventions.35 Finally, people reporting the inability to walk 400 m incur higher healthcare costs of $4000 per person per year, compared with those not reporting inability to walk 400 m.2, 35, 38, 39, 40 MMD was operationalized as the inability to complete a 400‐m walk test within 15 minutes without sitting or help of another person or walker.13 Completing the walk in greater than 15 minutes would be in an extremely slow pace (<0.45 m/s), which is of little utility in daily life.41 A higher cut point (30 or 60 minutes) makes the assessment impractical and would not add to the clinical significance of the outcome. The time to walk 400 m and the ability to complete the test provided data to test effects of the interventions resulting from both attenuation of decline and increase in walking speed. We hypothesized that, compared with health education, the physical activity intervention will reduce the risk of reaching the MMD outcome.
When the 400‐m walk test could not be administered, particularly when participants could only be evaluated in the clinic or in their homes, we took a conservative approach to adjudicating MMD based on objective inability to walk 4 m in 10 seconds or less, or self‐, proxy‐, or medical record–reported inability to walk across a room. We developed a detailed manual of procedures to define specific criteria for meeting this end point with high specificity. In LIFE, only 13.8% of MMD cases were determined by these alternative measures.
The 6‐minute walk test (6MWT)42, 43, 44, 45 was considered as an alternative outcome.45, 46, 47, 48 The 6MWT asks participants to cover as much ground as possible in 6 minutes, and it estimates VO2max, an important component of mobility. The 400‐m walk and the 6MWT are highly inversely correlated. Those who complete a “fast pace” 6 minutes and “fast pace” 400‐m test complete them in approximately the same amount of time/distance.49 Both tests are related to VO2max.49 Both tests have well‐defined metrics for meaningful change.11, 44 The 6MWT has several safety exclusions,43 while there are no exclusions for attempting the 400‐m walk at usual pace in people who are ambulatory. In both cases, noncompletion will occur. To address noncompletion (not attending visit, home bound), we included a 4‐m walk test, which can be conducted during a home visit and used for MMD adjudication.2, 11 We favored the 400‐m walk test for its established relationship to mobility disability as a dichotomous outcome, the public health relevance, and the well‐developed protocols to adjudicate MMD by committee, which are not available for the 6MWT, and its established metrics for meaningful change.
We calculated the power for effect sizes ranging from 20% to 25% relative effects on MMD. Based on perceived clinical importance and public health relevance, it was important to have reasonable power to detect a relative effect size in this range. A sensitivity analysis was performed to adjust relative effect sizes for potential drop in/dropout and nonadherence. Ultimately, a total sample size of 1600 participants was planned, recruited, and followed for an average of 2.6 years.
8.3. Study Population
We targeted a population at high risk of disability who is often excluded from large multicenter trials. That raised important issues regarding retention and adherence, specifically because of frequent health problems and hospitalizations. A higher adherence would likely result in greater benefits of physical activity. We devised plans to perform follow‐up visits at home or institution for participants who could not come to the clinic. A protocol was put in place to reengage the physical activity intervention in case of intercurrent illness that may have compromised adherence. In case of suspension of the intervention, the physical activity goals were reevaluated based on participant's illness and physical condition on reentry into the intervention.
8.4. Physical Activity Intervention
We wanted to maximize the public health impact of the LIFE Study. Thus, we chose a physical activity intervention that did not require any special equipment, such as treadmills or weight machines. The physical activity was a simple intervention involving walking, ankle weights, balance exercises, and stretching, which could be implemented virtually anywhere.
8.5. Funding
Obtaining funding for the main LIFE Study took 9 years (from 2000 to 2009) of negotiations with various funding agencies, primarily the NIH, production of preliminary data by means of secondary data analyses in existing databases, production of pilot data, multiple presentations at the NIA and the National Heart, Lung, and Blood Institute, and multiple formal grant submissions. Funding applications directed to industry and professional societies were unfruitful. Ultimately, high‐quality preliminary data and persistence of the entire LIFE team were key factors that resulted in successful funding.
8.6. Lessons Learned
A highly cohesive, committed, and collaborative multidisciplinary team, along with the close guidance of the NIH project office, were key elements necessary for the development of this project over the long‐term. The LIFE studies required the expertise of national leaders in a broad range of disciplines, including epidemiology, clinical trials, biostatistics, geriatrics, cardiology, neurology, behavioral sciences, biology, exercise physiology, and cost‐effectiveness analyses. It was necessary for all to work in a coordinated team to achieve a common goal.
To ensure the coordinated functioning of the project, we organized several committees (Supplementary Material S1), which mainly met by conference call on a monthly basis.
The overall recruitment in the LIFE studies ahead of the planned time lines and benchmarks was the result of careful planning and preliminary modeling of inclusion/exclusion criteria from epidemiologic databases. The expected incidence rate of the MMD primary outcome was also the result of modeling the selection of the population at risk from epidemiologic studies, which resulted in the expected statistical power and significant results of the trial on the primary outcome.
9. LEGACY OF THE LIFE STUDIES
The LIFE studies have involved over 870 scientists, staff members, and trainees at 18 institutions throughout the United States (Supplementary Material S1). To date, these studies have generated a legacy of 109 peer‐reviewed publications, including widely circulated general medicine and specialty journals, such as JAMA, JAMA Cardiology, Annals of Internal Medicine, Archives of Internal Medicine, Nature Medicine, BMC Medicine, Journals of Gerontology, and the Journal of the American Geriatrics Society (Supplementary Table S1). A total of 19 ancillary studies took advantage of the data, biological samples, and resources of the LIFE studies (Table 2). At least 38 independently funded grants and clinical trials capitalized on the LIFE studies (Supplementary Table S2) by sharing preliminary data and study materials, including protocols, manuals of operations and procedures, recruitment materials, retention materials, biological samples, and other resources. These studies include, among others, the ENabling Reduction of Low‐grade Inflammation in SEniors study to assess the effects on fish oil and losartan on mobility50; the SPRINT‐T trial in Europe to assess the effects on the LIFE interventions and diet on MMD51; and the coordinating center for the MOTRPAC consortium to assess the molecular transducers of physical activity.52 The LIFE studies facilitated the careers of 59 early career scientists (Supplementary Table S3) through publications, secondary analyses, ancillary studies, independent grants, and direct participation in the operations and experience at the LIFE Study sites. Today, many of these former early career scientists hold major leadership roles. The data and biological samples of the LIFE Study are now publicly available from a repository sponsored by the NIA (https://urldefense.proofpoint.com/v2/url?u=https-3A__agingresearchbiobank.nia.nih.gov&d=DwMFAg&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=ZX4a6hcfLVk9tpCPmkSujQ&m=iTPARxl_LBOimJoAcWK4efKQBWBHszm-g4mUN_o5-bc&s=SrlCccrcYCFSyWnnprcB3rJXT3W3FkGkW0XmdJITNhE&e=).
Table 2.
Principal Investigator (Institution) | Title | Funding Source | Study |
---|---|---|---|
Thomas Buford, PhD (University of Florida) | Effects of a one‐year physical activity program (LIFE‐P) on serum C‐terminal agrin fragment (CAF) concentrations57 | NeurotuneAG (Switzerland) | LIFE‐P |
Christopher deFilippi, MD (University of Maryland) | Impact of moderate physical activity on cardiac specific biomarkers of stress and injury: support for modifying early heart failure phenotypes58 | Roche Diagnostics Corporation | LIFE‐P |
Vonetta Dotson, PhD (University of Florida) | Physical activity and depressive symptoms in LIFE‐P: effects of genetic polymorphisms59 |
NIA U01AG022376‐07S1 |
LIFE‐P |
Cedric Dray, PhD (INSERM) | The effects of exercise on apelin28 | INSERM (France) | LIFE‐P |
Tina J. Ellis Brinkley, PhD (Wake Forest University) | Genetic polymorphisms in the renin‐angiotensin system and changes in physical function with exercise training60 | Wake Forest OAIC and GCRC | LIFE‐P |
Bret Goodpaster, PhD (University of Pittsburgh) | Effects of exercise body composition in the elderly: the LIFE study (DXA body comp)61 | NIA contract | LIFE‐P |
Bret Goodpaster, PhD (University of Pittsburgh) | Effects of exercise on muscle strength and quality in the elderly: the LIFE study31 | University of Pittsburgh | LIFE‐P |
Denise Houston, PhD, RD (Wake Forest University) | Role of vitamin D status and VDR polymorphisms on physical function62 | NIA K01AG030506 | LIFE‐P |
Jeffrey Katula, PhD (Wake Forest University) | Complex mobility and executive function63 | Wake Forest University | LIFE |
Christine Liu, MD, MS (Tufts University) | The impact of chronic kidney disease on the effectiveness of physical activity in older adults64 | Tufts University | LIFE and LIFE‐P |
Todd Manini, PhD (University of Florida) | mtDNA modifiers of the effect of exercise on cardiopulmonary and walking function in elders29 | NIH/NHLBI R01HL121023 | LIFE and LIFE‐P |
Barbara Nicklas, PhD (Wake Forest University) | Exercise and inflammatory risk factors for disability27 | NIH R01AG027529 | LIFE‐P |
Barbara Nicklas, PhD, and Xuewen Wang, PhD (Wake Forest University) | Effects of exercise training on prevalence of metabolic syndrome in the elderly65 | American Heart Association | LIFE‐P |
Anne Newman, MD, MPH (University of Pittsburgh) | Napping and sleep practices of older adults: relationship to sleep duration and quality66 | University of Pittsburgh | LIFE‐P |
Jack Rejeski, PhD (Wake Forest University) | Quantifying physical activity in the physical activity intervention using accelerometry67 | Wake Forest University | LIFE |
Caterina Rosano, MD, MPH (University of Pittsburgh) | Cerebral blood flow, structural brain characteristics, neuronal activation, and 2‐year response to physical activity intervention in the LIFE participants33 | NIA contract; Pittsburgh OAIC | LIFE |
Caterina Rosano, MD, MPH (University of Pittsburgh) | A pilot study to measure the association between functional brain MRI activation and motor performance in the LIFE participants32 | NIA contract | LIFE‐P |
Andrea Rosso, PhD, MPH (University of Pittsburgh) | Dopamine‐related genes, physical activity adherence, and cognitive outcomes68 | University of Pittsburgh | LIFE |
Joshua Brown, PharmD, PhD (University of Florida) | LIFE's legacy: secondary data linkage to evaluate the long‐term effects of the LIFE trial69 | University of Florida OAIC | LIFE |
Abbreviations: GCRC, General Clinical Research Center; LIFE, Lifestyle Interventions and Independence for Elders; LIFE‐P, LIFE‐Pilot; NHLBI, National Heart, Lung, and Blood Institute; NIA, National Institute on Aging; NIH, National Institutes of Health; OAIC, Older Americans Independence Center.
The results of the LIFE studies contributed to several public health recommendations for physical activity in older adults, including the US Department of Health and Human Services Physical Activity Guidelines for Americans,53 the Asia‐Pacific Clinical Practice Guidelines for the Management of Frailty,54 and the Physical Activity Guidelines Advisory Committee guidelines.55 The LIFE studies added to the scientific evidence, as indicated by high citation of the main articles8, 14 (625 and 738 citations, respectively, reported by Google Scholar on November 18, 2019), which likely have had an effect on the US population physical activity practices. The Centers for Disease Control and Prevention recently reported that the proportion of adults meeting minimum aerobic physical activity guideline (moderate intensity for ≥150 min/wk, vigorous intensity for ≥75 min/wk, or an equivalent combination) increased from 49.9% in 2013 (before the publication of the LIFE Study results) to 54.1% in 2017.56
Should we plan the LIFE Study today, we would likely focus on recruiting participants with an SPPB score of less than 8, as virtually all the physical activity benefit was accrued in this lower functioning group. We would also measure lower extremity strength and body composition.
10. CONCLUSION
The LIFE studies support the view that thorough planning, secondary analyses of data from existing studies, extensive pilot testing, and persistence are of pivotal importance to secure the success of a large multicenter phase 3 clinical trial. The LIFE studies have shown that older persons who are at high risk of disability and are traditionally excluded from large clinical trials can be successfully recruited, can be retained, and will adhere to behavioral interventions and physical and cognitive assessment protocols. The LIFE Study has demonstrated that a structured physical activity program is more effective than health education for preventing MMD. The LIFE studies and their related outcomes have generated a wealth of scientific findings and resources in geriatrics and gerontology to benefit the research community, trainees, clinicians, policy makers, and the general public. Large multicenter trials are needed to address important health questions in older adults. The LIFE Study provides an example of how not only the critical questions can be answered, but also of a major positive impact on early‐stage scientists, on development of new innovative ideas, and on economy.
Supporting information
Acknowledgments
Financial Disclosure
The Lifestyle Interventions and Independence for Elders studies were funded by National Institutes of Health (NIH) grant U01AG22376 and partially supported by the Claude D. Pepper Older Americans Independence Centers at the University of Florida (1 P30 AG028740), Wake Forest University (1 P30 AG21332), Tufts University (1P30AG031679), University of Pittsburgh (P30AG024827), and Yale University (P30AG021342) and the NIH/National Center for Research Resources Clinical and Translational Science Awards at Stanford University (UL1 RR025744), University of Florida (U54RR025208), and Yale University (UL1 TR000142). Tufts University was also supported by the Boston Rehabilitation Outcomes Center (1R24HD065688‐01A1). Dr Gill is the recipient of an Academic Leadership Award (K07AG043587) from the National Institute on Aging.
Conflict of Interest
The authors do not have any other conflicts of interest to disclose.
Author Contributions
Drafting of the manuscript: Marco Pahor, MD.
Sponsor's Role
The National Institutes of Health sponsor was a voting member (1 vote of 12 votes) of the Lifestyle Interventions and Independence for Elders Steering Committee, which approved the design and conduct of the study; collection, management, analysis; and interpretation of the data.
Critical Revision of the Manuscript for Important Intellectual Content
Marco Pahor, MD; Jack M. Guralnik, MD, PhD; Stephen D. Anton, PhD; Walter T. Ambrosius, PhD; Steven N. Blair, PED; Timothy S. Church, MD, PhD, MPH; Mark A. Espeland, PhD; Roger A. Fielding, PhD; Thomas M. Gill, MD; Nancy W. Glynn, PhD; Erik J. Groessl, PhD; Abby C. King, PhD; Stephen B. Kritchevsky, PhD; Todd M. Manini, PhD; Mary M. McDermott, MD; Michael E. Miller, PhD; Anne B. Newman, MD, MPH; Jeff D. Williamson, MD, MHS.
See related editorial by https://doi.org/10.1111/jgs.16374. in this issue.
REFERENCES
- 1. Branch LG, Jette AM. A prospective study of long‐term care institutionalization among the aged. Am J Public Health. 1982;72:1373‐1379. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Newman AB, Simonsick EM, Naydeck EM, et al. Association of long‐distance corridor walk performance with mortality, cardiovascular disease, mobility limitation, and disability. JAMA. 2006;295:2018‐2026. [DOI] [PubMed] [Google Scholar]
- 3. Katz S, Ford AB, Moskowitz RW, Jackson BA, Jaffe MW. Studies of illness in the aged: the index of ADL: a standardized measure of biological and psychosocial function. JAMA. 1963;185:94‐99. [DOI] [PubMed] [Google Scholar]
- 4. Rosow I, Breslau N. A Guttman health scale for the aged. J Gerontol. 1966;21:556‐559. [DOI] [PubMed] [Google Scholar]
- 5. Rolland YM, Cesari M, Miller ME, Penninx BWJH, Atkinson H, Pahor M. Reliability of the 400‐meter usual pace walk test as an assessment of mobility limitation in older adults. J Am Geriatr Soc. 2004;52:972‐976. [DOI] [PubMed] [Google Scholar]
- 6. Guralnik JM, Leveille SG, Volpato S, Marx MS, Cohen MJ. Targeting high risk older adults into exercise programs for disability prevention. J Aging Phys Act. 2003;11:219‐228. [Google Scholar]
- 7. Rejeski WJ, Fielding RA, Blair SN, et al. The lifestyle interventions and independence for elders (LIFE) pilot study: design and methods. Contemp Clin Trials. 2005;26:141‐154. [DOI] [PubMed] [Google Scholar]
- 8. Pahor M, Blair SN, Espeland M, et al. Effects of a physical activity intervention on measures of physical performance: results of the lifestyle interventions and independence for elders pilot (LIFE‐P) study. J Gerontol A Biol Sci Med Sci. 2006;61:1157‐1165. [DOI] [PubMed] [Google Scholar]
- 9. Espeland MA, Gill TM, Guralnik JM, et al. Designing clinical trials of intervention for mobility disability: results from the lifestyle interventions and independence for elders (LIFE) pilot trial. J Gerontol A Biol Sci Med Sci. 2007;62:1237‐1243. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Katula JA, Kritchevsky SB, Guralnik JM, et al. Lifestyle interventions and independence for elders pilot study: recruitment and baseline characteristics. J Am Geriatr Soc. 2007;55:674‐683. [DOI] [PubMed] [Google Scholar]
- 11. Kwon S, Perera S, Pahor M, et al. What is a meaningful change in physical performance? findings from a clinical trial in older adults (the LIFE‐P study). J Nutr Health Aging. 2009;13:538‐544. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Marsh AP, Lovato LC, Glynn NW, et al. Lifestyle interventions and independence for elders study: recruitment and baseline characteristics. J Gerontol A Biol Sci Med Sci. 2013;68:1549‐1558. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Fielding RA, Rejeski WJ, Blair SN, et al. The lifestyle interventions and independence for elders (LIFE) study: design and Methods. J Gerontol A Biol Sci Med Sci. 2011;66:1226‐1237. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Pahor M, Guralnik JM, Ambrosius WT, et al. Effect of structured physical activity on prevention of major mobility disability in older adults: the LIFE study randomized clinical trial. JAMA. 2014;311:2387‐2396. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Gill TM, Guralnik JM, Pahor M, et al. Effect of structured physical activity on overall burden and transitions between states of major mobility disability in older persons: secondary analysis of a randomized, controlled trial. Ann Intern Med. 2016;165:833‐840. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Sink KM, Espeland MA, Castro CM, et al. Effect of a 24‐month physical activity intervention vs health education on cognitive outcomes in sedentary older adults: the LIFE randomized trial. JAMA. 2015;314:781‐790. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Newman AB, Dodson JA, Church TS, et al. Cardiovascular events in a physical activity intervention compared with a successful aging intervention: the LIFE study randomized trial. JAMA Cardiol. 2016;1:568‐574. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Gill TM, Pahor M, Guralnik JM, et al. Effect of structured physical activity on prevention of serious fall injuries in adults aged 70‐89: randomized clinical trial (LIFE study). BMJ. 2016;352:i245. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Henderson RM, Miller ME, Fielding RA, et al. Maintenance of physical function 1 year after exercise intervention in at‐risk older adults: follow‐up from the LIFE study. J Gerontol A Biol Sci Med Sci. 2018;73:688‐694. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Cesari M, Vellas B, Hsu FC, et al. A physical activity intervention to treat the frailty syndrome in older persons‐results from the LIFE‐P study. J Gerontol A Biol Sci Med Sci. 2015;70:216‐222. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Fried LP, Tangen CM, Walston J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001;56:M146‐M156. [DOI] [PubMed] [Google Scholar]
- 22. Ensrud KE, Ewing SK, Taylor BC, et al. Comparison of 2 frailty indexes for prediction of falls, disability, fractures, and death in older women. Arch Intern Med. 2008;168:382‐389. [DOI] [PubMed] [Google Scholar]
- 23. Trombetti A, Hars M, Hsu FC, et al. Effect of physical activity on frailty: secondary analysis of a randomized controlled trial. Ann Intern Med. 2018; 168(5):309‐316. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Groessl EJ, Kaplan RM, Castro Sweet CM, et al. Cost‐effectiveness of the LIFE physical activity intervention for older adults at increased risk for mobility disability. J Gerontol A Biol Sci Med Sci. 2016;71:656‐662. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Rejeski WJ, King AC, Katula JA, et al. Physical activity in prefrail older adults: confidence and satisfaction related to physical function. J Gerontol B Psychol Sci Soc Sci. 2008;63:19‐26. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26. Wanigatunga AA, Ambrosius WT, Rejeski WJ, et al. Association between structured physical activity and sedentary time in older adults. JAMA. 2017;318:297‐299. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. Nicklas BJ, Hsu FC, Brinkley TJ, et al. Exercise training and plasma C‐reactive protein and interleukin‐6 in elderly people. J Am Geriatr Soc. 2008;56:2045‐2052. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Vinel C, Lukjanenko L, Batut A, et al. The exerkine apelin reverses age‐associated sarcopenia. Nat Med. 2018;24:1360‐1371. [DOI] [PubMed] [Google Scholar]
- 29. Manini TM, Buford TW, Kairalla JA, et al. Meta‐analysis identifies mitochondrial DNA sequence variants associated with walking speed. GeroScience. 2018;40:497‐511. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30. Buford TW, Manini TM, Kairalla JA, et al. Mitochondrial DNA sequence variants associated with blood pressure among 2 cohorts of older adults. J Am Heart Assoc. 2018;7:e010009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31. Goodpaster BH, PJ WBK, et al. Effects of physical activity on strength and skeletal muscle fat infiltration in older adults: a randomized controlled trial. J Appl Physiol. 2008;105:1498‐1503. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32. Rosano C, Venkatraman VK, Guralnik J, et al. Psychomotor speed and functional brain MRI 2 years after completing a physical activity treatment. J Gerontol A Biol Sci Med Sci. 2010;65:639‐647. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33. Rosano C, Guralnik J, Pahor M, et al. Hippocampal response to a 24‐month physical activity intervention in sedentary older adults. Am J Geriatr Psychiatry. 2017;25:209‐217. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34. Brault MW. Americans With Disabilities: 2010 ‐ Household Economic Studies. Current Population Reports: US Census Bureau ‐ US Department of Commerce ‐ Economics and Statistics Administration, 2012, 70‐131. [Google Scholar]
- 35. Hardy SE, Kang Y, Studenski SA, Degenholtz HB. Ability to walk 1/4 mile predicts subsequent disability, mortality, and health care costs. J Gen Intern Med. 2011;26:130‐135. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36. Lonergan ET, Krevans JR. A national agenda for research on aging. N Engl J Med. 1991;324:1825‐1828. [DOI] [PubMed] [Google Scholar]
- 37. Guralnik JM, LaCroix AZ, Abbott RD, et al. Maintaining mobility in late life, I: demographic characteristics and chronic conditions. Am J Epidemiol. 1993;137:845‐857. [DOI] [PubMed] [Google Scholar]
- 38. Hoffman JM, Ciol MA, Huynh M, Chan L. Estimating transition probabilities in mobility and total costs for Medicare beneficiaries. Arch Phys Med Rehabil. 2010;91:1849‐1855. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39. Hardy SE, Perera S, Roumani YF, Chandler JM, Studenski SA. Improvement in usual gait speed predicts better survival in older adults. J Am Geriatr Soc. 2007;55:1727‐1734. [DOI] [PubMed] [Google Scholar]
- 40. Hoffman JM, Shumway‐Cook A, Yorkston KM, Ciol MA, Dudgeon BJ, Chan L. Association of mobility limitations with health care satisfaction and use of preventive care: a survey of Medicare beneficiaries. Arch Phys Med Rehabil. 2007;88:583‐588. [DOI] [PubMed] [Google Scholar]
- 41. Hoxie RE, Rubenstein LZ. Are older pedestrians allowed enough time to cross intersections safely? J Am Geriatr Soc. 1994;42:241‐244. [DOI] [PubMed] [Google Scholar]
- 42. Guyatt GH, Osoba D, Wu AW, Wyrwich KW, Norman GR. Methods to explain the clinical significance of health status measures. Mayo Clin Proc. 2002;77:371‐383. [DOI] [PubMed] [Google Scholar]
- 43. ATS Committee on Proficiency Standards for Clinical Pulmonary Function Laboratories . ATS statement: guidelines for the six‐minute walk test. Am J Respir Crit Care Med. 2002;166:111‐117. [DOI] [PubMed] [Google Scholar]
- 44. Perera S, Mody SH, Woodman RC, Studenski SA. Meaningful change and responsiveness in common physical performance measures in older adults. J Am Geriatr Soc. 2006;54:743‐749. [DOI] [PubMed] [Google Scholar]
- 45. McDermott MM, Guralnik JM, Criqui MH, Liu K, Kibbe MR, Ferrucci L. Six‐minute walk is a better outcome measure than treadmill walking tests in therapeutic trials of patients with peripheral artery disease. Circulation. 2014;130:61‐68. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46. Snyder PJ, Ellenberg SS, Cunningham GR, et al. The testosterone trials: seven coordinated trials of testosterone treatment in elderly men. Clin Trials. 2014;11:362‐375. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47. Tse HN, Raiteri L, Wong KY, et al. High‐dose N‐acetylcysteine in stable COPD: the 1‐year, double‐blind, randomized, placebo‐controlled HIACE study. Chest. 2013;144:106‐118. [DOI] [PubMed] [Google Scholar]
- 48. Kitzman DW, Hundley WG, Brubaker PH, et al. A randomized double‐blind trial of enalapril in older patients with heart failure and preserved ejection fraction: effects on exercise tolerance and arterial distensibility. Circ Heart Fail. 2010;3:477‐485. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49. Simonsick EM, Montgomery PS, Newman AB, Bauer DC, Harris T. Measuring fitness in healthy older adults: the health ABC long distance corridor walk. J Am Geriatr Soc. 2001;49:1544‐1548. [DOI] [PubMed] [Google Scholar]
- 50. Pahor M, Anton SD, Beavers DP, et al. Effect of losartan and fish oil on plasma IL‐6 and mobility in older persons: the ENRGISE pilot randomized clinical trial. J Gerontol A Biol Sci Med Sci. 2019;74(10):1612‐1619. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51. Marzetti E, Calvani R, Landi F, et al. Innovative medicines initiative: the SPRINT project. J Frailty Aging. 2015;4:207‐208. [DOI] [PubMed] [Google Scholar]
- 52. MoTrPAC. Molecular Transducers of Physical Activity ; 2019. https://www.motrpac.org/. Accessed February 17, 2020.
- 53. Physical Activity Guidelines for Americans. In: Services USDoHaH, ed. Washington, DC: U.S. Department of Health and Human Services; 2018. [Google Scholar]
- 54. Dent E, Lien C, Lim WS, et al. The Asia‐Pacific clinical practice guidelines for the management of frailty. J Am Med Dir Assoc. 2017;18:564‐575. [DOI] [PubMed] [Google Scholar]
- 55. Physical Activity Guidelines Advisory Committee PAGAC . 2018 Physical Activity Guidelines Advisory Committee Scientific Report. Washington, DC: U.S. Department of Health and Human Services; 2018. [Google Scholar]
- 56. CDC . Centers for Disease Control and Prevention ‐ Trends in Meeting the 2008 Physical Activity Guidelines, 2008—2017. https://www.cdc.gov/physicalactivity/downloads/trends-in-the-prevalence-of-physical-activity-508.pdf. Accessed July 16, 2019. 2019.
- 57. Bondoc I, Cochrane SK, Church TS, et al. Effects of a one‐year physical activity program on serum C‐terminal agrin fragment (CAF) concentrations among mobility‐limited older adults. J Nutr Health Aging. 2015;19:922‐927. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58. de Filippi CR, de Lemos JA, Newman AB, et al. Impact of moderate physical activity on the longitudinal trajectory of a cardiac specific biomarker of injury: results from a randomized pilot study of exercise intervention. Am Heart J. 2016;179:151‐156. [DOI] [PubMed] [Google Scholar]
- 59. Dotson VM, Hsu FC, Langaee TY, et al. Genetic moderators of the impact of physical activity on depressive symptoms. J Frailty Aging. 2016;5:6‐14. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 60. Buford TW, Hsu FC, Brinkley TE, et al. Genetic influence on exercise‐induced changes in physical function among mobility‐limited older adults. Physiol Genomics. 2014;46(5):149‐158. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 61. Liu CK, Leng X, Hsu FC, et al. The impact of sarcopenia on a physical activity intervention: the lifestyle interventions and independence for elders pilot study (LIFE‐P). J Nutr Health Aging. 2014;18:59‐64. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 62. Houston DK, Tooze JA, Hausman DB, et al. Change in 25‐hydroxyvitamin D and physical performance in older adults. J Gerontol A Biol Sci Med Sci. 2011;66:430‐436. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 63. Wanigatunga AA, Manini TM, Cook DR, et al. Community‐based activity and sedentary patterns are associated with cognitive performance in mobility‐limited older adults. Front Aging Neurosci. 2018;10:341. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 64. Liu CK, Milton J, Hsu FC, et al. The effect of chronic kidney disease on a physical activity intervention: impact on physical function, adherence, and safety. J Clin Nephrol Ren Care. 2017;3(1):21. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 65. Wang X, Hsu FC, Isom S, et al. Effects of a 12‐month physical activity intervention on prevalence of metabolic syndrome in elderly men and women. J Gerontol A Biol Sci Med Sci. 2012;67:417‐424. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 66. Vaz Fragoso CA, Miller ME, Fielding RA, et al. Sleep‐wake disturbances in sedentary community‐dwelling elderly adults with functional limitations. J Am Geriatr Soc. 2014;62:1064‐1072. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 67. Fanning J, Rejeski WJ, Chen SH, et al. A case for promoting movement medicine: preventing disability in the LIFE randomized controlled trial. J Gerontol A Biol Sci Med Sci. 2019;74:1821‐1827. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 68. Rosso AL, Metti AL, Glynn NW, et al. Dopamine‐related genotypes and physical activity change during an intervention: the lifestyle interventions and independence for elders study. J Am Geriatr Soc. 2018;66:1172‐1179. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 69. Brown JD, Smith SM, Strotmeyer ES, et al. Comparative effects of ACE inhibitors and ARBs on response to a physical activity intervention in older adults: results from lifestyle interventions for elders (LIFE) study. J Gerontol A Biol Sci Med Sci. 2019;pii:glz120. 10.1093/gerona/glz120. [Epub ahead of print]. [DOI] [PMC free article] [PubMed] [Google Scholar]
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