Aging results in a progressive decline in physical function, leading to the loss of physical independence, an increased probability of falls, and reduced quality of life (1–3). Maintaining function is as important as prolonging life expectancy in older adults (4). Considering the expected rise in the elderly population (5), preserving physical function is a significant public health concern. Despite the potential public health impact, few interventions exist to slow the decline in physical function.
Fish oil (FO)—also known as long-chain omega-3 polyunsaturated fatty acids—is the most widely used natural dietary supplement in the United States (6) and has been the focus of a substantial amount of health research in the past three decades (7–11). Dietary intake of FO has a multitude of potential biological mechanisms related to lowering inflammation (12), increasing muscle protein synthesis (13,14), and improving muscle quality (15), which are closely related to the loss of physical function in older adults. As such, dietary fish intake or FO supplementation could preserve or enhance physical function in older adults. In general, the literature evaluating FO supplementation and physical function in older adults has shown encouraging results: For example, a majority of observational studies in this area have shown favorable associations between FO supplementation and physical function (16–18). Longer-duration randomized controlled trials (RCT; 6 months) also have shown a beneficial effect of omega-3 supplementation on walking speed (19), muscle strength (20), and muscle volume (20) in nonphysically impaired older adults. Meanwhile, trials with short supplementation duration (<6 months) have failed to show any benefits on physical function or performance (21,22), suggesting that a more sustained regimen may be necessary to see measurable effects.
Although physical activity (PA) is known to improve physical function in older adults, there is significant variability in responses (23,24). Coupling PA with FO supplementation may result in an augmented effect on biological pathways, resulting in a larger effect on physical function. Notably, a 5-month RCT of omega-3 supplementation has shown a potentiating effect when combined with exercise compared with exercise alone in older adults without physical limitations (15). The purpose of this article was to test the hypothesis that long-term FO supplementation is associated with a reduced risk of major mobility disability (MMD). A second purpose was to evaluate if long-term FO supplementation modifies the association of a PA intervention with respect to MMD, persistent mobility disability (PMD), and physical functional outcomes (23) in low-to-moderately functioning older adults.
METHODS
The Lifestyle Interventions and Independence for Elders (LIFE) study was a multicenter, single-blind, randomized trial (1:1 allocation ratio) conducted across eight US field centers to assess the effect of PA on mobility disability incidence in older adults (23). A total of 1635 participants were randomized to a PA group or health education (HE) group and followed for an average period of 2.6 yr. The study was approved by the institutional review board at each center and was conducted between February 2010 and December 2013. All participants provided written informed consent.
The current study is a secondary analysis of the LIFE study. The trial design, recruitment, study protocol, and primary outcome have been previously described (23,25,26). Inclusion criteria included men and women age 70–89 yr who were sedentary (self-reported <20 min·wk−1 of regular physical exercise in the past month and reporting <125 min·wk−1 of moderate-intensity PA) and had physical limitations defined by a Short Physical Performance Battery score of 9 or less (of 12 points). In addition, participants had to be able to walk 400 m within 15 min without sitting, leaning, or the help of another person or walker; had to be cognitively intact (measured by Modified Mini-Mental State Examination (3MSE) with a score of no more than 1.5 SD below education- and race-specific norms).
A detailed description of the LIFE study intervention has been published previously (25). The structured PA intervention included attendance at two center-based visits per week and home-based activity three to four times per week for the duration of the study. Briefly, the PA sessions involved walking up to 40 min at moderate intensity to reach a goal of 150 min·wk−1, 10 min of primarily lower extremity strength training by using ankle weights (two sets of 10 repetitions), and 10 min of balance training and flexibility exercises. Participants were asked to walk at an intensity of 13 (activity perception “somewhat hard”), and lower extremity strengthening exercises were performed at an intensity of 15 to 16. The total duration of the PA intervention lasted 30–60 min, depending on the participant’s level of fitness. The HE group attended weekly workshops that included non-PA topics related to older adults, such as preventive services and screenings, finding credible health information, and so forth.
Assessment of FO intake
At the baseline and 12-month assessment visits, participants were asked to bring in prescription medications, nonprescription medications, and supplements taken in the previous 2 wk in their original containers with labels. Study staff confirmed medication possession and administration, which they then recorded on a specific form. Participants were taking an FO supplement if they satisfied the following criteria at baseline: taking a medication classified as “fish oil,” taking a drug with “fish” or “omega” in the drug name, or taking Lovaza, Vascepa, or Omacor. For the current analysis, the study sample was stratified into two groups according to FO supplementation (FO users vs nonusers) assessed at baseline.
The baseline assessments also included self-reported demographic and contact information including race and ethnicity reported according to the National Institutes of Health requirements, medical and hospitalization history, cognitive function, body mass, and height. These measures are described in detail elsewhere (26).
Disability outcomes
The primary outcome—incident MMD—was defined as the inability to walk 400 m within 15 min without sitting and without the help of another person or walker (23,25). Participants were asked to walk 400 m at their usual pace, without overexerting, on a 20-m course for 10 laps (40 m per lap). Participants were allowed to use a cane and stop for up to 1 min for fatigue or related symptoms and then continue the test. Participants were evaluated every 6 months throughout the study duration. PMD was also quantified as a secondary outcome, defined as two consecutive MMD events or MMD followed by death.
Physical function outcomes
Secondary outcomes included the Short Performance Physical Battery (SPPB) (27,28), grip strength, and 400-m walk speed (29). SPPB is a composite score of balance, usual gait speed, and chair stands and summarized as scores ranging from 0 (worst performers) to 12 (best performers). Grip strength was assessed using the Jammar handgrip dynamometer. Two attempts were provided, and the higher value for the dominant hand was used for analysis. SPPB and 400-m walk speed were assessed at baseline and every 6 months during follow-up. Grip strength was assessed at baseline and at 12 months. All assessments were conducted by assessors who were masked to intervention arm assignment.
Adherence
Intervention adherence was calculated as the percentage of sessions attended by participants, after excluding medical leave. PA was assessed using Community Healthy Activities Model Program for Seniors (CHAMPS) questionnaire (30) and by accelerometry (GT3X; ActiGraph Inc., Pensacola, FL). For CHAMPS, the time per week doing walking activities and strength training activities were combined and collected every 6 months. Accelerometry was measured by having participants wear an accelerometer on the hip for 7 consecutive days at baseline and 6, 12, and 24 months after randomization.
Statistical analysis
This was a post hoc analysis to examine potential effect modification of FO and PA on physical function outcomes. Continuous variables were expressed as mean (SD), and categorical variables were presented as frequencies and percentages. A Cox proportional hazard model was used to test the association of FO use on MMD and PMD using covariate adjusted models that did not include interaction terms. In another model, the significance of the interaction of FO by intervention arm was evaluated; individual associations of FO use by intervention arm were tested with contrasts. Event times were defined as the time from randomization in the parent study until the initial ascertainment of MMD. Censoring was defined as the time of the last assessment, as described previously (23). Kaplan–Meier plots were created to display group-specific survival curves. Clinical site and sex were used as stratifying factors in the Cox models as in the parent study. Two adjusted models were used: model 1 included intervention arm and age (linear); model 2 added race/ethnicity, body mass index (BMI), college education, history of cardiovascular disease, chronic pulmonary disease, diabetes, social participation score (31), and 3MSE score. For the social participation score, a continuous score ranging from 0 to >9 h·wk−1 to reflect the total number of minutes of social participation per typical week was created by adding both formal and informal interactions (frequency and duration) as previously described (31). Formal interactions include attending organized group functions, such as senior center, volunteer work, and church, whereas informal interactions include visitation with friends and family (other than those who share habitation).
A similar analytic approach was taken for the physical function outcomes and intervention adherence by accelerometry and CHAMPS. A series of mixed-model analysis of covariance was used to investigate the average effect of FO across all follow-up visits in the following continuous variables: 400-m gait speed, grip strength, and SPPB scores. Least squares means were obtained, and contrasts were used to estimate the average effects over the follow-up period. All models used a compound symmetry matrix. Model covariates described previously and a covariate for baseline value of the outcome were also included.
Four sensitivity analyses were performed to evaluate the robustness of results for the disability outcomes: 1) modeled FO status from baseline to 12 months using a time-varying Cox proportional hazard model to evaluate chronic use of FO on mobility disability, 2) controlled for the “healthy user bias” by including vitamin C or multivitamin use as a covariate, 3) compared multivitamin/vitamin C users with multivitamin/vitamin C nonusers among FO nonusers, and 4) conducted propensity score analysis with adjustment for covariates to further control for selection bias and residual confounding. All tests of significance were two-sided, and significance was established at the 5% level. Statistical analyses were performed in SAS 9.4 software.
RESULTS
Between February 2010 and December 2011, 1635 sedentary men and women age 70 to 89 yr who had physical limitations were randomized to either PA or HE, as previously described (23). The mean age was 78.9 yr, 67.2% were women, 17.6% were African American, and the mean follow-up for any contact was 2.6 yr (median, 2.7 yr; interquartile range, 2.3–3.1 yr). Of the 1635, 456 used FO supplements, whereas 1177 were nonusers and 2 were missing. Most (71%) of the users were taking dosages greater than 800 mg. The demographic and baseline characteristics for the FO users and nonusers are summarized in Table 1. The baseline characteristics by FO use and intervention arm are given in Supplemental Digital Content 1 (Table, Supplemental Digital Content 1, Baseline characteristics participants by fish oil use and treatment arm, https://links.lww.com/MSS/B797). FO users were more likely to be female, white, and college educated, and were equally distributed across intervention arms. We noted no major baseline differences in age, BMI, physical function (SPPB, 400-m walk speed, grip strength), PA (walking/weight training minutes), or self-reported conditions/comorbidities between the arms. The analytic sample for model 2 included 1597 participants (2% missing; 2 missing FO data and 38 missing one or more covariates; Table, Supplemental Digital Content 2, Distribution of missing data for outcome, exposure, and confounders, https://links.lww.com/MSS/B798).
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TABLE 1: Baseline participant characteristics by FO use.
FO users experienced a lower incidence of MMD compared with nonusers (Figs. 1 and 2A). Kaplan–Meier curves separated by intervention arms for incident MMD are shown in Figure 2B. Incident MMD was experienced by 131 (28.7%) FO users and 405 (34.4%) nonusers (model 2: HR, 0.78; 95% confidence interval (CI), 0.64–0.96). Similar results were observed with PMD; PMD was experienced by 67 (14.7%) FO users and 215 (18.3%) nonusers (model 2: HR, 0.79; 95% CI, 0.60–1.05; Fig. 1). Interactions between intervention arm and FO use for MMD and PMD is illustrated in Figure 3. For incident MMD risk, the interaction between intervention arm and FO use was not significant (P = 0.19). For PMD, there was a significant interaction (P = 0.002); however, FO users showed no associations as a result of the PA intervention (HR, 1.36; 95% CI, 0.83–2.23), whereas nonusers showed a significant reduction (HR, 0.61; 95% CI, 0.46–0.81) in PMD as a result of the PA intervention.
FIGURE 1: Association of FO on the onset of MMD and PMD. Model 1 included intervention arm and age. Model 2 included model 1 plus race, BMI, college education, social participation score, history of cardiovascular disease, chronic pulmonary disease, diabetes, and 3MSE score. Clinical site and sex were used as stratifying factors in the models. HR values plotted on log scale. P values given for model 2. Incidence rate per 1000 person-years.
FIGURE 2: Kaplan–Meier Curves for MMD. A, Kaplan–Meier curves for incident MMD. B, Kaplan–Meier curves separated by intervention arms for incident MMD.
FIGURE 3: Interaction effect of FO and PA on mobility disability. Model 1 included intervention arm–FO and age. Model 2 included model 1 plus race, BMI, college education, social participation score, history of cardiovascular disease, chronic pulmonary disease, diabetes, and 3MSE score. Clinical site and sex were used as stratifying factors in the models. HR values plotted on log scale. P values given for model 2. Incidence rate per 1000 person-years.
Differences in physical performance outcomes (SPPB, 400-m walk speed, and grip strength) between FO users and nonusers and effect modification by intervention arm are shown in Table 2. In general, FO users showed better physical performance response than did nonusers, although the differences were not statistically significant. FO users had an attenuated nonsignificant association on physical performance due to the PA intervention. For example, nonusers had an increase or preservation in grip strength associated with the PA intervention relative to FO users (P = 0.04 and 0.10 in models 1 and 2, respectively).
TABLE 2: SPBB score, 400-m walk speed, grip strength by PA intervention, and FO use.a
Sensitivity analysis
Four sensitivity analyses were conducted for the mobility disability outcomes: Time-varying analysis of FO users at baseline and 12 months (HR, 0.78; 95% CI, 0.64–0.96) showed similar MMD risk reduction in chronic FO users (Table, Supplemental Digital Content 3, Time-varying analysis for FO users, https://links.lww.com/MSS/B799). Adding vitamin C as a covariate (HR, 0.80; 95% CI, 0.65–0.99) did not alter the significant main results (Table, Supplemental Digital Content 4, Sensitivity analysis with multivitamin/vitamin C use as a covariate in model 2, https://links.lww.com/MSS/B800). Also, analysis of multivitamin/vitamin C users versus nonusers in FO nonusers showed nonsignificant (HR, 0.96; 95% CI, 0.79–1.16) findings (Table, Supplemental Digital Content 5, Sensitivity analysis with multivitamin/vitamin C use in FO nonusers, https://links.lww.com/MSS/B801). Finally, propensity score analysis showed similar results (HR, 0.80; 95% CI, 0.64–0.99) as shown in Table 3.
TABLE 3: Propensity score analysis of disability outcomes.
Physical activity intervention attendance and adherence
For PA class attendance, FO users attended 63.5% (95% CI, 60.1%–66.9%) and nonusers attended 63.2% (95% CI, 61.0%–65.4%) of the sessions (Table, Supplemental Digital Content 6, Attendance by intervention and FO status, https://links.lww.com/MSS/B802). Minutes of activity based on accelerometry and CHAMPS questionnaire are shown in Supplemental Digital Content 7 (Table, Supplemental Digital Content 7, Physical activity at 24 months, https://links.lww.com/MSS/B803). The adjusted mean differences between the FO users and nonusers at 24 months did not reach statistical significance (9.19 min; 95% CI, −8.97 to 27.35 min) for CHAMPS questionnaire and for hip-worn accelerometers (8.43 min; 95% CI, −12.02 to 28.88 min).
DISCUSSION
We hypothesized that long-term FO supplementation would be associated with a reduced risk of MMD when combined with a PA intervention. The salient findings of this secondary analysis were as follows: 1) long-term FO supplementation was associated with a 22% relative risk reduction in the primary outcome of incident MMD compared with nonusers, and 2) however, FO users experienced no benefit of a structured PA program on the incidence of MMD or persistent MD risk.
Overall, these results suggest favorable associations of FO supplementation on MMD in low to moderate functioning older adults across a 2-yr period. The secondary outcomes showed a similar trend favoring the individuals supplementing with FO. Although the evidence from RCTs is mixed, our results for the main effect of FO are consistent with some of the long-duration RCTs aimed at improving physical function with FO, albeit in healthy older adults (20). (19). Although two other randomized trials showed no change in performance, they tended to be of shorter duration (<6 months) and with smaller sample sizes (21,22). Recently, the ENRGISE Pilot Study showed that FO supplementation for a duration of 1 yr was not effective at improving gait speed (32). It could be speculated that the effects of FO on MMD found in the current study may result from the longer duration of the study and the supplementation duration.
For the association of supplementation on PA-related MMD, no interaction was observed for the incidence of MMD, but there was evidence of a modifying association for the secondary outcome of PMD. The qualitative interaction suggesting a diminishing association of FO with PA for PMD lacks a clear biological rationale. It should be noted that the interaction is largely driven by the significant effect size in the nonusers. Furthermore, the small number of events for PMD compared with MMD resulting in a wide CI makes it harder to interpret the interaction effect. Overall, the interactions suggested that FO did not augment the beneficial association when combined with PA. In contrast, Rodacki et al. (15) showed an enhanced effect of FO when combined with strength training in healthy elderly women (15). The enhanced effect of FO supplementation on exercise in Rodacki et al. (15) was observed for maximal torque and rate of torque for the lower limbs and chair stand. However, no effects were observed with 6-min walk performance. We speculate that the incongruence could be due to several study-related differences: First, the current study involved moderate-intensity walking, flexibility, balance exercises, and strength exercises using ankle weights that prevented high loading of the muscle. Rodacki et al. (15) focused on strength training exercises alone, using strength machines at 80% of maximal strength. These differences suggest that FO supplementation may have a preferential effect on physical performance when coupled with high muscle loading. Second, the population used in both studies should also be noted; the current study enrolled only older adults with moderate to low physical function, whereas Rodacki et al. (15) enrolled healthy older women who reported no physical limitations. Lastly, the current study had a long follow-up of 2 yr, whereas Rodacki et al. (15) intervened for a shorter duration of 3–5 months.
Although not the focus of the current study, the FO-associated reduction in mobility disability could be explained by a number of potential biological mechanisms: First, omega-3 fatty acids have shown to reduce age-related proinflammatory markers such as C-reactive protein, interleukin 6, and tumor necrosis factor α (12). Chronic low-grade inflammation is an independent risk factor for disability and mobility impairment (33,34). Second, omega-3 fatty acids have been shown to stimulate the rate of muscle protein synthesis and muscle anabolic signaling during hyperinsulinemia–hyperaminoacidemia in both young and older adults (13,14), independent of reductions in plasma inflammatory markers. Third, an improvement in muscle quality via changes in neuromuscular function and reduced intramuscular fat infiltration (20) has also been observed (15).
Strengths and limitations
The strengths of the article include conducting the analysis in a multicenter trial in vulnerable older adults followed for a long duration. To our knowledge, the LIFE study is the largest and longest randomized clinical trial on PA in elderly. FO supplementation was assessed based on medication inventories as opposed to self-reports. Medical inventories are valid when compared with pharmacy records, with a sensitivity, specificity, and positive predictive values >95% (35). In addition, supplementation was examined in the context of modifying the effect of a PA intervention using objective performance measures of mobility disability and physical function that are well validated and clinically important in older adults (36). The current study has several limitations. First, this analysis was not prespecified and was not powered to detect intervention differences in response to PA between FO groups. Second, although we adjusted for a number of covariates and conducted several sensitivity analyses that supported our main findings, we cannot discount a selection bias where individuals supplementing with FO were healthier at baseline. Third, adherence to FO was not ascertained and a dose–response relationship could not be assessed because of the lack of heterogeneity in supplement dosages.
Conclusions and implications
Currently, PA is the only known strategy to prevent or delay mobility disability in older adults. That being said, the effect of PA on functional outcomes is variable. Pharmacological approaches using growth hormone and testosterone have reported little beneficial effects on physical function and come with possible side effects (37,38). On the other hand, FO is widely used and generally regarded as safe, inexpensive, and widely available. In this study, FO was associated with a lower risk of MMD in low functioning adults but did not enhance the benefit of PA on risk of MMD. Collectively, the results of the current study, along with the favorable profile of the supplement, suggest a promising role for FO in preserving physical function or delaying disability in older adults with or without PA. However, these results are hypothesis generating and should be confirmed in preplanned randomized trials.
The Lifestyle Interventions and Independence for Elders (LIFE) study is funded by a National Institutes of Health (NIH)/National Institute on Aging Cooperative Agreement No. UO1 AG22376 and a supplement from the National Heart, Lung and Blood Institute 3U01AG022376-05A2S, and sponsored in part by the Intramural Research Program, National Institute on Aging, NIH.
The research is 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), the University of Pittsburgh (P30 AG024827), and Yale University (P30AG021342), and the NIH/National Center for Research Resources Clinical and Translational Science Award at Stanford University (UL1 RR025744),
Tufts University is also supported by the Boston Rehabilitation Outcomes Center (1R24HD065688-01A1). LIFE investigators are also partially supported by the following: Dr. Thomas Gill (Yale University) is the recipient of an Academic Leadership Award (K07AG3587) from the National Institute on Aging; Dr. Carlos Fragoso (Spirometry Reading Center, Yale University) is the recipient of a Career Development Award from the Department of Veterans Affairs; Dr. Roger Fielding (Tufts University) is partially supported by the US Department of Agriculture, under agreement No. 58-1950-0-014.
Any opinions, findings, conclusion, or recommendations expressed in this publication are those of the authors and do not necessarily reflect the view of the US Department of Agriculture.
The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. The results of this study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation. The results of the present study do not constitute endorsement by the American College of Sports Medicine.
D. G. is the Chief Scientific Officer at Blue Star Nutraceuticals. D. G. proposed the study concept when he was a postdoctoral fellow at the University of Florida. No other disclosures are reported.
Administrative Coordinating Center, University of Florida, Gainesville, FL
Marco Pahor, MD—Principal Investigator of the LIFE Study
Jack M. Guralnik, MD, PhD—Co-Investigator of the LIFE Study (University of Maryland School of Medicine, Baltimore, MD)
Christiaan Leeuwenburgh, PhD
Connie Caudle
Lauren Crump, MPH
Latonia Holmes
Jocelyn Lee, PhD
Ching-ju Lu, MPH
Data Management, Analysis and Quality Control Center, Wake Forest University, Winston Salem, NC
Michael E. Miller, PhD—DMAQC Principal Investigator
Mark A. Espeland, PhD—DMAQC Co-Investigator
Walter T. Ambrosius, PhD
William Applegate, MD
Daniel P. Beavers, PhD, MS
Robert P. Byington, PhD, MPH, FAHA
Delilah Cook, CCRP
Curt D. Furberg, MD, PhD
Lea N. Harvin, BS
Leora Henkin, MPH, Med
John Hepler, MA
Fang-Chi Hsu, PhD
Laura Lovato, MS
Wesley Roberson, BSBA
Julia Rushing, BSPH, MStat
Scott Rushing, BS
Cynthia L. Stowe, MPM
Michael P. Walkup, MS
Don Hire, BS
W. Jack Rejeski, PhD
Jeffrey A. Katula, PhD, MA
Peter H. Brubaker, PhD
Shannon L. Mihalko, PhD
Janine M. Jennings, PhD
Shyh-Huei Chen, PhD
June J. Pierce, AB
Haiyeng Chen, PhD
National Institutes of Health, Bethesda, MD
Evan C. Hadley, MD (National Institute on Aging)
Sergei Romashkan, MD, PhD (National Institute on Aging)
Kushang V. Patel, PhD (National Institute on Aging)
National Heart, Lung and Blood Institute, Bethesda, MD
Denise Bonds, MD, MPH
Field Centers
Northwestern University, Chicago, IL
Mary M. McDermott, MD—Field Center Principal Investigator
Bonnie Spring, PhD—Field Center Co-Investigator
Joshua Hauser, MD—Field Center Co-Investigator
Diana Kerwin, MD—Field Center Co-Investigator
Kathryn Domanchuk, BS
Rex Graff, MS
Alvito Rego, MA
Pennington Biomedical Research Center, Baton Rouge, LA
Timothy S. Church, MD, PhD, MPH—Field Center Principal Investigator
Steven N. Blair, PED (University of South Carolina)
Valerie H. Myers, PhD
Ron Monce, PA-C
Nathan E. Britt, NP
Melissa Nauta Harris, BS
Ami Parks McGucken, MPA, BS
Ruben Rodarte, MBA, MS, BS
Heidi K. Millet, MPA, BS
Catrine Tudor-Locke, PhD, FACSM
Ben P. Butitta, BS
Sheletta G. Donatto, MS, RD, LDN, CDE
Shannon H. Cocreham, BS
Stanford University, Palo Alto, CA
Abby C. King, PhD—Field Center Principal Investigator
Cynthia M. Castro, PhD William L. Haskell, PhD
Randall S. Stafford, MD, PhD Leslie A. Pruitt, PhD
Kathy Berra, MSN, NP-C, FAAN
Veronica Yank, MD
Tufts University, Boston, MA
Roger A. Fielding, PhD—Field Center Principal Investigator
Miriam E. Nelson, PhD—Field Center Co-Investigator
Sara C. Folta, PhD—Field Center Co-Investigator
Edward M. Phillips, MD
Christine K. Liu, MD
Erica C. McDavitt, MS
Kieran F. Reid, PhD, MPH
Dylan R. Kirn, BS
Evan P. Pasha, BS
Won S. Kim, BS
Vince E. Beard, BS
Eleni X. Tsiroyannis, BS
Cynthia Hau, BS, MPH
University of Florida, Gainesville, FL
Todd M. Manini, PhD—Field Center Principal Investigator
Marco Pahor, MD—Field Center Co-Investigator
Stephen D. Anton, PhD
Susan Nayfield, MD
Thomas W. Buford, PhD
Michael Marsiske, PhD
Bhanuprasad D. Sandesara, MD
Jeffrey D. Knaggs, BS
Megan S. Lorow, BS
William C. Marena, MT, CCRC
Irina Korytov, MD
Holly L. Morris, MSN, RN, CCRC (Brooks Rehabilitation Clinical Research Center, Jacksonville, FL)
Margo Fitch, PT (Brooks Rehabilitation Clinical Research Center, Jacksonville, FL)
Floris F. Singletary, MS, CCC-SLP (Brooks Rehabilitation Clinical Research Center, Jacksonville, FL)
Jackie Causer, BSH, RN (Brooks Rehabilitation Clinical Research Center, Jacksonville, FL)
Katie A. Radcliff, MA (Brooks Rehabilitation Clinical Research Center, Jacksonville, FL)
University of Pittsburgh, Pittsburgh, PA
Anne B. Newman, MD, MPH—Field Center Principal Investigator
Stephanie A. Studenski, MD, MPH—Field Center Co-Investigator
Bret H. Goodpaster, PhD
Nancy W. Glynn, PhD
Oscar Lopez, MD
Neelesh K. Nadkarni, MD, PhD
Kathy Williams, RN, BSEd, MHSA
Mark A. Newman, PhD
George Grove, MS
Janet T. Bonk, MPH, RN
Jennifer Rush, MPH
Piera Kost, BA (deceased)
Diane G. Ives, MPH
Wake Forest University, Winston Salem, NC
Stephen B. Kritchevsky, Ph.D.—Field Center Principal Investigator
Anthony P. Marsh, PhD—Field Center Co-Investigator
Tina E. Brinkley, PhD
Jamehl S. Demons, MD
Kaycee M. Sink, MD, MAS
Kimberly Kennedy, BA, CCRC
Rachel Shertzer-Skinner, MA, CCRC
Abbie Wrights, MS
Rose Fries, RN, CCRC
Deborah Barr, MA, RHEd, CHES
Yale University, New Haven, CT
Thomas M. Gill, MD—Field Center Principal Investigator
Robert S. Axtell, PhD, FACSM—Field Center Co-Investigator (Southern Connecticut State University, Exercise Science Department)
Susan S. Kashaf, MD, MPH (VA Connecticut Healthcare System)
Nathalie de Rekeneire, MD, MS
Joanne M. McGloin, MDiv, MS, MBA
Karen C. Wu, RN
Denise M. Shepard, RN, MBA
Barbara Fennelly, MA, RN
Lynne P. Iannone, MS, CCRP
Raeleen Mautner, PhD
Theresa Sweeney Barnett, MS, APRN
Sean N. Halpin, MA
Matthew J. Brennan, MA
Julie A. Bugaj, MS
Maria A. Zenoni, MS
Bridget M. Mignosa, AS
Cognition Coordinating Center, Wake Forest University, Winston Salem, NC
Jeff Williamson, MD, MHS—Center Principal Investigator
Kaycee M Sink, MD, MAS—Center Co-Investigator
Hugh C. Hendrie, MB, ChB, DSc (Indiana University)
Stephen R. Rapp, PhD
Joe Verghese, MB, BS (Albert Einstein College of Medicine of Yeshiva University)
Nancy Woolard
Mark Espeland, PhD
Janine Jennings, PhD
Valerie K. Wilson, MD
Electrocardiogram Reading Center, University of Florida, Gainesville, FL
Carl J. Pepine MD, MACC
Mario Ariet, PhD
Eileen Handberg, PhD, ARNP
Daniel Deluca, BS
James Hill, MD, MS, FACC
Anita Szady, MD
Spirometry Reading Center, Yale University, New Haven, CT
Geoffrey L. Chupp, MD
Gail M. Flynn, RCP, CRFT
Thomas M. Gill, MD
John L. Hankinson, PhD (Hankinson Consulting, Inc.)
Carlos A. Vaz Fragoso, MD
Cost-Effectiveness Analysis Center
Erik J. Groessl, PhD (University of California, San Diego and VA San Diego Healthcare System)
Robert M. Kaplan, PhD (Office of Behavioral and Social Sciences Research, National Institutes of Health)
REFERENCES
1. Fried LP, Guralnik JM. Disability in older adults: evidence regarding significance, etiology, and risk.
J Am Geriatr Soc. 1997;45(1):92–100.
2. Janssen I, Heymsfield SB, Ross R. Low relative skeletal muscle mass (sarcopenia) in older persons is associated with functional impairment and physical disability.
J Am Geriatr Soc. 2002;50(5):889–96.
3. Bergen G, Stevens MR, Burns ER. Falls and fall injuries among adults aged ≥65 years—United States, 2014.
MMWR Morb Mortal Wkly Rep. 2016;65:993–8.
4. Katz S, Branch LG, Branson MH, Papsidero JA, Beck JC, Greer DS. Active life expectancy.
N Engl J Med. 1983;309(20):1218–24.
5. Werner C.
The Older Population. [Internet] [cited 10 Apr 2019]. Available from:
http://www.census.gov/prod/cen2010/briefs/c2010br-09.pdf.
6. Clarke TC, Black LI, Stussman BJ, Barnes PM, Nahin RL. Trends in the use of complementary health approaches among adults: United states, 2002–2012.
Natl Health Stat Rep. 2015;10(79):1–16.
7. Mocking R, Harmsen I, Assies J, Koeter M, Ruhe H, Schene A. Meta-analysis and meta-regression of
omega-3 polyunsaturated fatty acid supplementation for major depressive disorder.
Transl Psychiatry. 2017;6(3):e756.
8. Mozaffarian D, Wu JH.
Omega-3 fatty acids and cardiovascular disease: effects on risk factors, molecular pathways, and clinical events.
J Am Coll Cardiol. 2011;58(20):2047–67.
9. Chowdhury R, Warnakula S, Kunutsor S, et al. Association of dietary, circulating, and supplement fatty acids with coronary risk: a systematic review and meta-analysis.
Ann Intern Med. 2014;160(6):398–406.
10. Pradhan AD, Manson JE. Update on the vitamin D and
omegA-3 trial (VITAL).
J Steroid Biochem Mol Biol. 2016;155:252–6.
11. Jiao J, Li Q, Chu J, Zeng W, Yang M, Zhu S. Effect of n-3 PUFA supplementation on cognitive function throughout the life span from infancy to old age: a systematic review and meta-analysis of randomized controlled trials.
Am J Clin Nutr. 2014;100(6):1422–36.
12. Li K, Huang T, Zheng J, Wu K, Li D. Effect of marine-derived n-3 polyunsaturated fatty acids on C-reactive protein, interleukin 6 and tumor necrosis factor alpha: a meta-analysis.
PLoS One. 2014;9(2):e88103.
13. Smith GI, Atherton P, Reeds DN, et al. Dietary
omega-3 fatty acid supplementation increases the rate of muscle protein synthesis in older adults: a randomized controlled trial.
Am J Clin Nutr. 2011;93(2):402–12.
14. Smith G, Atherton P, Reeds D, et al.
Omega-3 polyunsaturated fatty acids augment the muscle protein anabolic response to hyperinsulinaemia-hyperaminoacidaemia in healthy young and middle-aged men and women.
Clin Sci (Lond). 2011;121(6):267–78.
15. Rodacki CL, Rodacki AL, Pereira G, et al. Fish-oil supplementation enhances the effects of strength training in
elderly women.
Am J Clin Nutr. 2012;95(2):428–36.
16. Frison E, Boirie Y, Peuchant E, Tabue-Teguo M, Barberger-Gateau P, Feart C. Plasma fatty acid biomarkers are associated with gait speed in community-dwelling older adults: the Three-City-Bordeaux Study.
Clin Nutr. 2017;36(2):416–22.
17. Reinders I, Murphy R, Song X, et al. Polyunsaturated fatty acids in relation to incident mobility disability and decline in gait speed; the Age, Gene/Environment Susceptibility-Reykjavik Study.
Eur J Clin Nutr. 2015;69(4):489–93.
18. Rousseau JH, Kleppinger A, Kenny AM. Self-reported dietary intake of
omega-3 fatty acids and association with bone and lower extremity function.
J Am Geriatr Soc. 2009;57(10):1781–8.
19. Hutchins-Wiese HL, Kleppinger A, Annis K, et al. The impact of supplemental n-3 long chain polyunsaturated fatty acids and dietary antioxidants on physical performance in postmenopausal women.
J Nutr Health Aging. 2013;17(1):76–80.
20. Smith GI, Julliand S, Reeds DN, Sinacore DR, Klein S, Mittendorfer B. Fish oil-derived n-3 PUFA therapy increases muscle mass and function in healthy older adults.
Am J Clin Nutr. 2015;102(1):115–22.
21. Logan SL, Spriet LL.
Omega-3 fatty acid supplementation for 12 weeks increases resting and
exercise metabolic rate in healthy community-dwelling older females.
PLoS One. 2015;10(12):e0144828.
22. Da Boit M, Sibson R, Sivasubramaniam S, et al. Sex differences in the effect of fish-oil supplementation on the adaptive response to resistance
exercise training in older people: a randomized controlled trial.
Am J Clin Nutr. 2017 Jan;105(1):151–8.
23. 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(23):2387–96.
24. Chmelo EA, Crotts CI, Newman JC, et al. Heterogeneity of
physical function responses to
exercise training in older adults.
J Am Geriatr Soc. 2015;63(3):462–9.
25. Fielding RA, Rejeski WJ, Blair S, et al. The lifestyle interventions and independence for elders study: design and methods.
J Gerontol A Biol Sci Med Sci. 2011;66(11):1226.
26. 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(12):1549–58.
27. Guralnik JM, Ferrucci L, Simonsick EM, Salive ME, Wallace RB. Lower-extremity function in persons over the age of 70 years as a predictor of subsequent disability.
N Engl J Med. 1995;332(9):556–61.
28. Guralnik JM, Simonsick EM, Ferrucci L, et al. A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission.
J Gerontol. 1994;49(2):M85–94.
29. Rolland YM, Cesari M, Miller ME, Penninx BW, Atkinson HH, Pahor M. Reliability of the 400-m usual-pace walk test as an assessment of mobility limitation in older adults.
J Am Geriatr Soc. 2004;52(6):972–6.
30. Stewart AL, Mills KM, King AC, Haskell WL, Gillis D, Ritter PL. CHAMPS physical activity questionnaire for older adults: outcomes for interventions.
Med Sci Sports Exerc. 2001;33(7):1126–41.
31. Corbett DB, Rejeski WJ, Tudor-Locke C, et al. Social participation modifies the effect of a structured physical activity program on major mobility disability among older adults: results from the LIFE study.
J Gerontol B Psychol Sci Soc Sci. 2017;73(8):1501–13.
32. 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. 2018;73(12):1–8.
33. Penninx BW, Kritchevsky SB, Newman AB, et al. Inflammatory markers and incident mobility limitation in the
elderly.
J Am Geriatr Soc. 2004;52(7):1105–13.
34. Cesari M, Penninx BW, Pahor M, et al. Inflammatory markers and physical performance in older persons: the InCHIANTI study.
J Gerontol A Biol Sci Med Sci. 2004;59(3):242–8.
35. Drieling RL, LaCroix AZ, Beresford SA, Boudreau DM, Kooperberg C, Heckbert SR. Validity of self-reported medication use compared with pharmacy records in a cohort of older women: findings from the Women’s Health Initiative.
Am J Epidemiol. 2016;184(3):233–8.
36. Newman AB, Simonsick EM, Naydeck BL, et al. Association of long-distance corridor walk performance with mortality, cardiovascular disease, mobility limitation, and disability.
JAMA. 2006;295(17):2018–26.
37. Vigen R, O’Donnell CI, Barón AE, et al. Association of testosterone therapy with mortality, myocardial infarction, and stroke in men with low testosterone levels.
JAMA. 2013;310(17):1829–36.
38. Liu H, Bravata DM, Olkin I, et al. Systematic review: the safety and efficacy of growth hormone in the healthy
elderly.
Ann Intern Med. 2007;146(2):104–15.
