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. Author manuscript; available in PMC: 2021 Dec 1.
Published in final edited form as: J Am Geriatr Soc. 2020 Sep 22;68(12):2890–2897. doi: 10.1111/jgs.16793

Non-Esterified Fatty Acids and Risks of Frailty, Disability, and Mobility Limitation in Older Adults: the Cardiovascular Health Study

Peter Ahiawodzi 1, Luc Djousse 2, Joachim H Ix 3, Jorge R Kizer 4, Russell P Tracy 5, Alice Arnold 6, Anne Newman 7, Kenneth J Mukamal 8
PMCID: PMC8285064  NIHMSID: NIHMS1721403  PMID: 32964434

Abstract

BACKGROUND:

Non-esterified fatty acids (NEFAs) play central roles in the relationship between adiposity and glucose metabolism and have been implicated in the pathogenesis of cardiovascular disease, but few studies have assessed their effects on complex geriatric syndromes like frailty that cross multiple organ systems. We sought to determine the relationships between NEFAs and incident frailty, disability, and mobility limitation in a population-based cohort of older persons.

METHODS:

We analyzed 4710 Cardiovascular Health Study (CHS) participants who underwent measurement of circulating total fasting NEFAs in 1992-3 and assessed for frailty in 1996-1997 and for disability and mobility limitation annually. We used ordinal logistic regression to model incident frailty, linear regression to model components of frailty, and Cox regression to model disability and mobility limitation in relation to baseline NEFAs. To ensure proportional hazards, we truncated follow-up at 9 years for disability and 6.5 years for mobility limitation.

RESULTS:

A total of 42 participants became frail and 510 became pre-frail over a four-year period, and we documented 1720 cases of disability and 1225 cases of mobility limitation during follow-up. NEFAs were positively associated in a dose-dependent manner with higher risks of incident frailty, disability, and mobility limitation. The adjusted odds ratios for frailty were 1.37 (95%CI=1.01-1.86, p=0.04) across extreme tertiles and 1.17 (95%CI=1.03-1.33, P=0.01) per standard deviation increment. The corresponding hazard ratios for incident disability were 1.14 (95%CI=1.01-1.30, p=0.04) and 1.11 (95%CI=1.06-1.17, P<0.0001), while those for incident mobility limitation were 1.23 (95%CI=1.06-1.43, p=0.006) and 1.15 (95%CI=1.08-1.22, P<.0001). Results were largely consistent among both men and women. Among individual components of frailty, NEFAs were significantly associated with self-reported exhaustion (β=0.07, SE=0.03, P=0.02).

CONCLUSION:

Circulating NEFAs are significantly associated with frailty, disability, and mobility limitation among older adults. These results highlight the broad spectrum of adverse health issues associated with NEFA in older adults.

INTRODUCTION

Non-esterified fatty acids (NEFAs) are carboxylic acids with carbon chains of various lengths and degrees of saturation. Their levels increase with age and are thought to have a central role in impaired glucose metabolism.1,2 Specifically, NEFAs inhibit insulin signaling in key tissues, and particularly in skeletal muscle, where they regulate insulin-mediated glucose uptake.3,4 NEFAs have also been directly associated with endothelial dysfunction5 and toxicity to several cell types in the brain.6-8 As a result, they not only influence glucose metabolism, but could play direct adverse roles in neuromuscular perfusion and function.9-11 Importantly, NEFAs can potentially be modulated by existing pharmacological therapies and are the target of ongoing pharmaceutical development.12,13

Frailty is a multidimensional geriatric syndrome characterized by reduced capacity of different physiological systems and is associated with increased risk of falls, disability, mobility limitation, hospitalizations and mortality in older adults.14 Although it is characterized by muscular weakness, slow gait, and exhaustion – all features suggesting musculoskeletal dysfunction – research remains limited on potentially modifiable metabolic causes of frailty. Our previous work15 has demonstrated that a metabolic phenotype characterized by marked insulin resistance is associated with subsequent disability and mobility limitation in older adults, suggesting that metabolic dysregulation is at least one potential pathway leading to frailty.

NEFAs are associated with higher risk of many of the most common chronic diseases of older adults, such as congestive heart failure16 and atrial fibrillation17. However, to date, we know of no cohort studies that have investigated the associations of NEFAs with geriatric syndromes like frailty, disability, and mobility loss. To address these relationships, we studied participants in the Cardiovascular Health Study (CHS), an ongoing population-based cohort study of older American adults. We hypothesized that higher NEFA levels would be directly associated with the incidence of disability, mobility limitation, and frailty.

METHODS

CHS is a prospective cohort consisting of 5,888 men and women aged ≥65 years who were randomly selected from Medicare-eligibility lists in four U.S. communities (Forsyth County, NC; Washington County, MD; Sacramento County, CA; and Pittsburgh, PA). A detailed description of methods and procedures in the CHS has previously been published.18 Briefly, persons eligible to participate were not institutionalized or wheelchair dependent, did not require a proxy for consent, were not receiving treatment for cancer, and were expected to remain in their respective regions for 3 years. From 1989 to 1990, 5,201 participants were recruited in the original cohort. Between 1992 and 1993, 687 subjects (predominantly African American) were additionally recruited. Baseline evaluation of study participants included standardized questionnaires, physical examination, anthropometric measurements, resting electrocardiography, and laboratory examinations. From 1989 through 1999, participants were followed up every 6 months, alternating between telephone calls and clinic visits; biennial telephone calls have continued since then. The institutional review board at each center approved the study, and each participant gave informed consent.

For this analysis, the 1992–93 clinic visit (i.e., the first visit that incorporated the new cohort) was used as baseline. Of the 5265 participants present at the 1992-93 clinic visit, 4715 underwent measurement of NEFA in stored specimens. Five (5) participants who did not have any record of frailty, disability, or mobility limitation assessment were excluded from the study resulting in a sample of 4710. We further excluded participants using criteria unique to each outcome measure (frailty, disability, mobility limitation), resulting in analytic datasets as shown on figure 1.

Figure 1:

Figure 1:

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Flow Diagram of Study Sample

Measurement of plasma NEFA

Plasma NEFA concentration was measured by the Wako enzymatic method at the CHS Central Laboratory at the University of Vermont. This technique relies on the acylation of CoA by the fatty acids in the presence of added acyl-CoA synthetase. Acyl-CoA produced is oxidized by added acyl-CoA oxidase with generation of hydrogen peroxide and in the presence of peroxidase permits the oxidative condensation of 3-methy-Nethyl- N(b-hydroxyethyl)-aniline with 4-aminoantipyrine to form a purple-colored adduct. The latter is then measured colorimetrically at 550 nm. The interassay CV was 3.54–8.17% (detectable range 0.0156–1.50 mEq/L).

Assessment of Frailty, Disability, and Mobility limitation

We defined frailty using Fried et al.,14 criteria, as a geriatric syndrome in which three or more of the following criteria were present: unintentional weight loss (10 pounds in past year), self-reported exhaustion, weakness (grip strength), slow walking speed, and low physical activity. Pre-frail persons were those who met 1 or 2 of the criteria, and robust persons did not have any of the criteria. For this study, frailty was modelled as an ordinal variable- robust, pre-frail, and frail. Assessment of frailty occurred at the 1992-1993 and 1996-1997 CHS visits and incident frailty was the occurrence of pre-frailty or frailty at the latter visit among the subset of participants free of any frailty at baseline.

Disability was defined as self-reported difficulty with performing any activities of daily living (ADLs), including walking around home, getting out of bed/chair, dressing, bathing, eating, and toileting. Mobility limitation was defined as reported difficulty walking up 10 steps or walking ½ mile on two consecutive contacts, or at the last contact. Both of these measures were ascertained yearly by self-report.

Other Covariates

Baseline variables were generally used for statistical adjustment. These include age, body mass index, marital status- married or non-married; race- white or non-white; years of education-, hypertension status-normotensive, pre-hypertensive, or hypertensive; diabetes status- normal (fasting glucose <100 mg/dl), prediabetes (fasting glucose between 100 and 125 mg/dl, inclusive), diabetic (fasting glucose >125 mg/dl or use of medication), alcohol intake, and adjudicated prevalent coronary heart disease (CHD), and congestive heart failure (CHF).19-21 We also adjusted for incident CVD and diabetes during follow-up in sensitivity analyses. Other biomarkers measured at the CHS Central Laboratory included albumin, cystatin-C (used to estimated glomerular filtration rate), C-reactive protein (CRP), and total white blood cell count.22 Missing covariate data was imputed from the most recent record of that variable (i.e., carried forward from baseline); a previously-described imputed dataset was used in the rare cases that even baseline values were missing.23

Statistical Analyses

To minimize the effect of outliers, we winsorized NEFAs at the top and bottom 2.5% and report results per tertile and per standard-deviation increment for robustness and ease of interpretation. We used Cox proportional hazards regression models to model the associations between per-SD increment in NEFAs and mobility limitation and incident disability in unadjusted and adjusted models. We used ordinal logistic regression to model the associations of NEFAs with frailty in 1996-1997; in this model, the odds ratio can be interpreted as the effect of the exposure to increase (or decrease) the odds of being in a higher category of frailty and evaluated the proportional odds assumption with the score test. To confirm linearity, we examined the shape of the association of NEFAs with frailty, disability, and mobility limitation using penalized cubic splines using identical covariates and model forms (i.e., ordinal logistic and Cox regression).24

We also evaluated the association between per-SD increment in NEFAs and four individual components of frailty using linear regression, with 1996-1997 values as the outcome and adjusted for baseline values (Table 3). For each analysis, only participants with available data for that component were analyzed. Weight loss, which was defined as a loss of weight of ≥10 pounds in the last year (that is, recent weight loss), was only ascertained as a binary variable in CHS, and hence we did not test change in this component as we did the other four. For exhaustion, we summed up the responses to the Likert scale for the two relevant CES-D questions —”I could not get going” and —”I felt that everything I did was an effort during last week”. The scores were then recoded for the linear regression analysis using a procedure described by Wu et al. (2018).25 Additionally, though interaction tests between gender and NEFA was not significant, we analyzed men and women separately to examine if any differences exist, given marked differences in both NEFA values and frailty between men and women. We tested the proportional hazards assumption using time-dependent covariates and truncated follow-up where violations occurred.26 Analyses were performed using SAS Version 9.3 (SAS Institute Inc. Cary, NC). This study was approved by the Institutional Review Board of Campbell University in North Carolina.

Table 3:

Analyses of the relationship between NEFA and frailty components

Frailty Component N Estimate (β) Standard Error P-Value
Gait Speed (ft/s) 2975 −0.03 0.02 0.17
Grip Strength (kg) 2888 −0.02 0.10 0.87
Self-Reported Exhaustion 3236 0.07 0.03 0.02
*Activity (kcal) 3315 −33.7 23.61 0.15
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Each model of frailty component adjusted for adjusted for Age, gender, BMI, race, education, marital status, alcohol use, diabetes status, CHF, CHD, hypertension, white blood cell count, albumin, C-Reactive Protein, glomerular filtration rate (cystatin).

*

Activity was winsorized at 97.5% (5940 kcal).

RESULTS

Table-1 shows the demographic characteristics of participants according to NEFA tertiles. As expected, NEFA tended to be higher with older age, heavier BMI, and among women. Table-2 shows the associations of NEFAs with incident frailty and pre-frailty in an ordinal logistic regression model. NEFAs were positively associated in a dose-dependent manner with higher risks of incident frailty, disability, and mobility limitation. The adjusted odds ratios for frailty were 1.37 (95%CI=1.01-1.86, p=0.04) across extreme tertiles and 1.17 (95%CI=1.03-1.33, P=0.01) per standard deviation increment; for comparison, the coefficient for a single year of age in the same models were both 1.09. The corresponding hazard ratios for incident disability were 1.14 (95%CI=1.01-1.30, p=0.04) across extreme tertiles and 1.11 (95%CI=1.06-1.17, P<0.0001) per standard deviation increment; for comparison the coefficient for a single year of age in the same models were both 1.06. Those for incident mobility limitation were 1.23 (95%CI=1.06-1.43, p=0.006) across extreme tertiles and 1.15 (95%CI=1.08-1.22, P<.0001) per standard deviation increment; for comparison, the hazard ratio for a single year of age in the same models were both 1.07. Further analyses controlling for time-varying CHD, CHF, and diabetes status, produced the same estimates. Figure 2 demonstrates the dose-dependent, graded associations of NEFAs with ADL difficulty and mobility limitation; in both analyses, we observed no evidence of non-linearity (p=0.19 for ADL difficulty, and 0.52 for mobility limitation) and a significant linear trend (p<0.0001 for both ADL difficulty and mobility limitation). NEFAs were similarly associated with frailty with a significant linear trend (p=0.02) and no evidence of non-linearity (p=0.62).

Table 1:

Demographic Characteristics of CHS Participants According to NEFA Tertiles

NEFA TERTILES ( mEq/L)
VARIABLE <0.395
N=1571		 0.395-0.556
N=1569		 >0.556
N=1570		 P-Value
Age, Years (SD) 74.2 (4.9) 75.0 (5.3) 75.4 (5.5) <.0001
Gender, Male (%) 925 (47.1) 627 (31.9) 413 (21.0) <.0001
Race, White (%) 1312 (33.7) 1307 (33.6) 1275 (32.7) 0.17
Marital Status, Married (%) 1172 (37.1) 1059 (33.5) 931 (29.4) <.0001
Body-Mass Index (kg/m2) 26.3 (4.1) 27.0 (4.8) 27.3 (5.3) <.0001
Alcohol Use (drinks/week) 2.1 (5.2) 1.9 (5.5) 2.2 (5.6) 0.46
Education (years) 14.4 (4.8) 14.0 (4.7) 13.6 (4.6) <.0001
Hypertension (%) 570 (29.1) 625 (31.9) 764 (39.0) <.0001
Diabetes (%) 192 (26.6) 222 (30.7) 309 (42.7) <.0001
CHD (%) 386 (37.8) 326 (31.9) 310 (30.3) 0.003
CHF (%) 94 (33.3) 95 (33.7) 93 (33.0) 0.99
White Blood Cell Count (/mm3) 6.2 (4.4) 6.3 (2.6) 6.6 (2.1) 0.0003
Albumin (gm/dl) 3.88 (0.3) 3.91 (0.3) 3.96 (0.3) <.0001
C-Reactive Protein (mg/L) 4.6 (9.0) 5.6 (10.3) 6.0 (9.7) 0.0003
Estimated Glomerular filtration rate ( mL/min/1.73m2) 72.1 (18.3) 72.4 (19.0) 73.0 (19.2) 0.40
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Table 2:

Odds ratio and hazard ratio estimates and 95% confidence intervals for incident disability and mobility limitation as a function of NEFA

MODEL ** OR/HR (95% confidence intervals)
Unadjusted P-Value Adjusted* P-Value
FRAILTY Cases/N
Tertile 1 149/447 1.00 1.00
Tertile 2 208/449 1.70 (1.30 – 2.22) 0.0001 1.42 (1.07 – 1.89) 0.01
Tertile 3 195/413 1.79 (1.36 – 2.35) <.0001 1.37 (1.01 – 1.86) 0.04
P for Linear Trend <.0001 0.04
Per SD increment of NEFA 1.28 (1.14 – 1.43) <.0001 1.17 (1.03 – 1.33) 0.01
ADL LIMITATION Cases/N
Tertile 1 729/1357 1.00 1.00
Tertile 2 759/1358 1.12 (0.99 – 1.26) 0.06 1.01 (0.89 – 1.14) 0.89
Tertile 3 832/1354 1.36 (1.21 – 1.53) <.0001 1.14 (1.01 – 1.30) 0.04
P for Linear Trend <.0001 0.04
Per SD increment of NEFA 1.17 (1.12 – 1.23) <.0001 1.11 (1.06 – 1.17) <0.0001
MOBILITY LIMITATION Cases/N
Tertile 1 768/1096 1.00 1.00
Tertile 2 786/1088 1.16 (1.01 – 1.34) 0.04 1.01 (0.88 – 1.18) 0.85
Tertile 3 816/1100 1.57 (1.37 – 1.80) <.0001 1.23 (1.06 – 1.43) 0.006
P for Linear Trend <.0001 0.005
Per SD increment of NEFA 1.24 (1.17 – 1.31) <.0001 1.15 (1.08 – 1.22) <.0001
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*

Adjusted for age, gender, BMI, race, education, marital status, alcohol use, diabetes status, CHF, CHD, hypertension, white blood cell count, albumin, C-reactive protein, estimated glomerular filtration rate (cystatin).

**

OR (Odds Ratio) was estimated for frailty in ordinal logistic regression models; HR (Hazard Ratio) was estimated for ADL and Mobility Limitations. N=Number at risk; SD=Standard Deviation

Figure 2. Adjusted Relationship between NEFAs and Incident ADL Difficulty and Mobility Limitation.

Figure 2.

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Results derived from a penalized cubic spline Cox Proportional Hazards model with 4 knots, with dependent variables as time to ADL difficulty (Panel A; Orange Color) and time to Mobility Limitation (Panel B; Blue Color). Covariates include age, sex, race, body mass index, years of education, marital status, hypertension status, diabetes status, prevalent CVD, alcohol intake, white blood, cell count, Creactive protein, albumin, and cystatin-C estimated glomerular filtration rate. The reference value was set to the median NEFA concentration; shown by dotted line. Grey shading indicates the 95% confidence interval.

To determine which components of frailty were most susceptible to NEFAs, we evaluated the association between NEFAs and the various components of frailty using linear regression models (i.e., in their natural units, rather than as binary components as summed in the frailty score). NEFAs were significantly associated with exhaustion. Exhaustion increased by 0.07 units per SD of NEFA increment (standard error=0.03; p=0.02); for comparison the coefficient for a single year of age in the same model was 0.01. The associations of NEFAs with gait speed, grip strength, and physical activity were not statistically significant [Table 3], although trends in the expected direction were most apparent for physical activity and gait speed.

Additionally, we performed gender-stratified analyses for the associations between NEFAs, frailty, ADLs, and mobility limitation. The associations were consistently stronger among women, although the differences by sex were modest [Supplementary Table S1].

DISCUSSION

In this cohort of older Americans, NEFAs significantly increased the risk for frailty, disability, and mobility limitation, three of the most impactful geriatric syndromes. Among the components of frailty, exhaustion was particularly adversely associated with NEFAs. These results persisted in models that accounted for a wide variety of determinants of NEFA levels.

To our knowledge, circulating NEFAs have not previously been associated with any of the outcomes studied here, all of which reflect declines in physical capacity in aging adults. Redistribution of body fat away from subcutaneous stores to other storage sites including muscle and viscera occurs during aging.27 This leads to an increase in circulating NEFAs as visceral adipose tissue is less efficient in storing fatty acid. Raised circulating NEFAs enhance insulin resistance leading to elevated blood glucose concentrations and risk for type 2 diabetes, impaired endothelial cell function, increased inflammatory markers, and all-cause and cardiovascular mortality.5,28,29 Frailty itself is a syndrome of physiological decline in late life and characterized by mobility impairment. Mobility impairment in turn leads to sedentary behavior and muscle loss, which puts the individual at further risk of disability. A social-ecological perspective by Yeom et al30 outlined risk factors such as intrapersonal risk (advanced age, low socioeconomic status, comorbidity, lack of motivation), lifestyle factors (sedentary lifestyle, smoking, obesity), and physiological factors (vitamin D deficiency, inflammation, poor nutritional status), although not all of these factors have been conclusively linked to frailty. We hypothesize that NEFAs may be a biological link connecting many of these social-ecological factors to frailty, disability, and mobility limitation. Specifically, Table 1 illustrates that NEFAs tend to be higher in association with several of these factors, including age, education, inflammation, diabetes, CHF, CHD, and hypertension. Because NEFAs appear to alter glucose use and mitochondrial function in muscle tissue,31 they are plausible candidate downstream mediators for many of these social, ecological, and clinical factors.

Our results suggest that modification of NEFAs could conceivably help to slow the progression of disability and mobility limitation in older adults, and research on potential determinants of NEFAs bears this suggestion out. In a longitudinal study of 1234 older men from the British Regional Heart Study, Parsons et al, (2018)32 found that healthier diet quality and dietary patterns, which appear to lower NEFA levels, are associated with lower risk of mobility limitation.33 Bishop and Wang (2018)34 found that food insecurity is associated with prevalence of mobility limitations among 5986 respondents from the 2012-2014 Health and Retirement Study and 2013 Health Care and Nutrition Study. It is reasonable to speculate that social and economic factors like food insecurity promote less healthy dietary options that contribute to higher levels of circulating NEFAs.

Other interventions aimed at improving mobility in older adults may also be helpful. Since physical activity correlates inversely with NEFA level35 and decreases NEFAs in diabetic adults36, increasing activity among older adults could reduce NEFA levels and improve functioning. Kabiri et al (2018)37 found that a 554-step-per-day increase in activity could reduce functional status limitations by 5.9%.

The scientific literature is not conclusive on which component (slow gait speed, low physical activity, weight loss, exhaustion, and weakness) imposes the greatest risk of frailty nor of long-term prognosis. However, gait speed has often been found to be strongly predictive of frailty and disability.38-40 Therefore, we expected that NEFAs would be associated with gait speed just as we found for frailty. On the contrary, our results indicate that among the components of frailty, NEFAs affected self-reported exhaustion or fatigue most clearly, although a nonsignificant trend in the expected direction was present for gait speed. Potentially relevant to the underlying biological explanation for our findings is that exhaustion is a key symptom of mitochondrial dysfunction.41 One potential pathway linking NEFAs and mitochondrial dysfunction is oxidative stress. Chronic elevation in circulating NEFA levels is characterized by increased reactive oxygen species (ROS) and reactive nitrogen species (RNS) production.42 Studies have shown that ROS lead to impaired insulin response by inducing IRS serine/threonine phosphorylation, decreased GLUT4 gene transcription, and decreased mitochondrial activity.43 ROS, especially, in the skeletal muscle has been implicated in aging-related diseases, malignant transformation, atherosclerosis, neurodegenerative diseases, obesity, diabetes, and metabolic syndrome.44-49 NEFAs can also directly induce mitochondrial dysfunction in the skeletal muscle, characterized by reduced ATP synthesis and mitochondrial polarization.50 NEFA-induced oxidative stress also contributes to impair insulin signaling by increased uncoupling protein-2 (UCP-2) activity, resulting in heat generation that does not contribute to ATP production.51,52 Hence, exhaustion could be the result of metabolic dysfunction in which insufficient intracellular energy is produced.53 Mitochondrial impairment therefore, is an important potential explanation for an effect of NEFAs on frailty and decline in muscle function and exhaustion in older adults.54 In light of this finding, the particular association of NEFAs with self-reported exhaustion warrants future follow-up, as it suggests that NEFAs adversely affects a core component of this geriatric syndrome.

Our study has several strengths. First, CHS provides high-quality data, with high rates of participant follow-up and formal event adjudication. Indeed, the concept of frailty was first quantified in CHS. Second, we used a sample of over 2000 participants, which is particularly large for studies of NEFA. Third, we adjusted for a comprehensive list of variables that could potentially confound the associations that we studied. Fourth, we analyzed NEFAs on a continuous scale, as splines, and as tertiles with consistent results. Fifth, we were able to examine three linked but independent endpoints – frailty, disability and mobility limitation – with consistent findings across all three.

Our study is not without limitations. First, since this is the first study of its kind, it is not possible to make direct comparisons our results and those of previous investigations. Nonetheless, we drew conclusions from related studies, and our findings are consistent with the biology of the outcomes studied. Second, our results are necessarily correlative, and we cannot ascribe causation to the relationships that we observed at this time. Studies that experimentally manipulate NEFAs for years at a time would be necessary for that. Third, we only had a single measurement of NEFAs, introducing null-biased misclassification based on day-to-day variability, and repeated measures would likely have yielded even stronger associations. Finally, our results apply directly only to older adults, although this is the age group for whom frailty is most salient, and we cannot directly extrapolate to younger adults or to race/ethnic groups like Asian- or Latino-Americans who were not well represented in CHS.

CONCLUSIONS

Our findings suggest that higher serum levels of NEFAs were significantly associated with increased likelihood of frailty, ADL difficulty, and mobility limitation. Frailty, disability, and mobility limitation are major problems for older adults, characterized by declines in many physiological systems and poor quality of life. In this cohort of older adults, NEFAs were significantly associated with these key geriatric outcomes. Interventions to reduce circulating levels of NEFAs may be important in the prevention of frailty, disability and mobility limitation in older adults and warrant future study.

Supplementary Material

tS1

Supplementary Table S1: Odds ratio and hazard ratio estimates and 95% confidence intervals for incident mobility limitation and frailty as a function of NEFA, by Gender

ACKNOWLEDGMENTS

Sponsor’s Role

This research was funded by contracts HHSN268201200036C, HHSN268200800007C, HHSN268201800001C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, and grants U01HL080295 and U01HL130114 from the National Heart, Lung, and Blood Institute (NHLBI), with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided by R01AG053325 and R01AG023629 from the National Institute on Aging (NIA). A full list of principal CHS investigators and institutions can be found at CHS-NHLBI.org.

Footnotes

Conflict of Interest

None of the authors have any conflict of interest to disclose

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

tS1

Supplementary Table S1: Odds ratio and hazard ratio estimates and 95% confidence intervals for incident mobility limitation and frailty as a function of NEFA, by Gender

NIHMS1721403-supplement-tS1.pdf (96.4KB, pdf)

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