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/lp/ou_press/the-adiponectin-paradox-in-the-elderly-associations-with-body-p50hkIf1U1
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- Oxford University Press
- Copyright
- Copyright © 2022 The Gerontological Society of America
- ISSN
- 1079-5006
- eISSN
- 1758-535X
- DOI
- 10.1093/gerona/gly017
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- See Article on Publisher Site
Abstract
Background: To determine if adiponectin levels are associated with weight loss, low muscle mass, and physical functioning among the elderly and to determine independent associations with incident disability and death. Methods: Included were 3,044 participants from the Health, Aging and Body Composition Study, who had whole-body dual energy 2 2 absorptiometry performed to evaluate appendicular lean mass index (ALMI, kg/m ) and fat mass index (FMI, kg/m ), computed tomography measures of thigh muscle density, weight histories, estimates of physical functioning, and adiponectin levels at enrollment. Associations between adiponectin levels and body composition, weight loss, and physical functioning were assessed in multivariable linear regression models. Associations between adiponectin and incident disability and mortality were assessed in mediation analyses, adjusting for other factors. Results: Greater adiponectin at baseline was independently associated with low FMI Z-score, lower waist circumference, low ALMI Z-score, low muscle density, a history of weight loss, and poor physical functioning (all p < .05). Greater adiponectin levels (per SD) were associated with incident disability [HR: 1.14 (1.08, 1.20), p < .001] and greater mortality [HR: 1.17 (1.10, 1.25), p < .001] in models adjusting for demographic factors, adiposity, and comorbid conditions. The association was completely attenuated and no longer significant (all p > 0.05) when adjusting for body composition, muscle density, weight loss, and physical functioning at baseline. Conclusions: Greater serum adiponectin levels are associated with historical weight loss, low skeletal muscle mass, low muscle density, and poor physical functioning. High adiponectin is associated with a greater risk of incident disability and death, but not independently of these factors. Keywords: Adiponectin, Adipokine, Mortality, Body composition. Adiponectin is an adipokine that is produced by adipocytes and patients. Accumulation of visceral fat is thought to promote TNF-α myocytes in response to caloric restriction and negative energy production in the viscera, which suppresses the transcription of the balance. It has been termed the “starvation signal,” as it increases adiponectin gene (2,3). Muscle fibers also produce adiponectin and with weight loss (1) and is generally found to be higher among thin it may act to increase skeletal muscle lipid oxidation (4). Among Published by Oxford University Press on behalf of The Gerontological Society of America 2018. This work is written by (a) US Government employee(s) and is in the public domain in the US. Downloaded from https://academic.oup.com/biomedgerontology/article/74/2/247/4846326 by DeepDyve user on 19 July 2022 248 Journals of Gerontology: MEDICAL SCIENCES, 2019, Vol. 74, No. 2 healthy young individuals, greater adiponectin levels have been Computed tomography scans of the thighs were obtained at shown to correlate with better long-term cardiovascular outcomes baseline (in Pittsburgh, 9800 Advantage from General Electric, (5,6). A direct and causal protective role of adiponectin with cardio- Milwaukee, WI; in Memphis, Somatom Plus 4 from Siemens, vascular disease has not been confirmed. Erlangen, Germany, or PQ 2000S, Marconi Medical Systems, A number of studies have demonstrated that higher adiponectin Cleveland, OH). A 10-mm-thick axial image (120 kVp, 200–250 levels are paradoxically associated with an increased risk of prema- mA) was obtained at midfemur. A line was drawn manually along ture death among chronic inflammatory conditions including chronic the deep fascial plane surrounding the thigh muscles to distinguish heart failure and end-stage renal disease (7–9). A previous study in muscle from surrounding subcutaneous adipose tissue, and the the Healthy Aging and Body Composition Study demonstrated that femur was segmented out of the muscle. Fat infiltration of muscle higher adiponectin levels were associated with an increased risk of was assessed in Hounsfield units (HU, a measure of x-ray attenu- premature death among the elderly independent of other cardiovas- ation), with lower HU reflecting more fat infiltration. This meas- cular risk factors (10). urement correlates with muscle triglyceride content determined by In general, adiponectin shows inverse associations with adverse histological oil red O staining, and the mean test–retest coefficient outcomes in healthy middle-aged populations. The opposite is of variation in a previous study was 0.51 per cent (21). This analysis observed in cohorts with prevalent cardiovascular disease, heart used the average muscle density between the two thighs. failure, or advanced age, whereas higher levels are associated with greater risk (7–9, 11). A recent study among older individuals Measurement of adiponectin demonstrated that both the highest and lowest levels are associ- Samples were drawn at the baseline visit after an overnight fast. ated with greater cardiovascular risk (12). Cachexia or sarcopenia Serum samples were frozen at −70°C and stored at McKesson related to aging, chronic inflammation, and illness may explain these BioServices, Rockville, MD. Adiponectin was assayed in 2002–2003 paradoxical epidemiological associations between adiponectin and from frozen serum samples (acquired 7 years prior). Total circulating higher mortality in these populations. In support of this hypothesis, levels of adiponectin (ng/mL) were measured in duplicate by radio- greater adiponectin levels have been observed among individuals immuno assay (RAI; Linco Research, St. Charles, MO) with an intra- with evidence of weight loss, cachexia, and poor physical function- assay coefficient of variation of 1.8%–3.6%. ing (13–18). We hypothesized that high adiponectin levels among the elderly Physical performance and disability measures are correlated with low body mass index (BMI), low fat mass and low Health ABC performance battery (22, 23) lean mass, poor muscle quality, a history of weight loss, poor physi- Details have been previously described (23). In brief, this battery cal functioning, and greater risk of incident disability and death. We includes five repeated chair stands, progressively more challeng- evaluated independent associations between adiponectin levels and ing tests of standing balance, a 6 m walk to determine usual gait body composition, physical functioning, incident disability, and mor- speed, and a narrow walk in which participants are instructed to tality in the Healthy Aging and Body Composition Study. talk between lines of colored tape 20 cm apart at their usual pace. Performance is divided by the maximum possible performance for older adults on each test to create ratio scores that are summed for Methods the four tests to obtain a continuous scale ranging from 0 to 4, with Study Setting a lower score indicating poorer function. Participants were enrolled in the Health, Aging and Body Composition (Health ABC) study, a prospective observational Long-distance corridor walk (LDCW; 400 M walk) study of 3,075 well-functioning, community-dwelling older This is a two-stage, self-paced walking test that was designed to adults aged 70–79 years. Study participants were recruited from a measure cardiorespiratory fitness longitudinally in an initially well- random sample of White and Black Medicare beneficiaries living in functioning cohort of 70 years old (24). The measure is prognostic of Pittsburgh, PA and Memphis, TN that were within a 1 hour drive greater disability and mortality (25). The first stage consisted of a 2 of the examination sites. All individuals with adiponectin levels and minutes warm-up walk, in which distance was recorded and the first whole-body x-ray absorptiometry (DXA) results available at enroll- 20 m was timed. This stage also served as a stepped-down test for per- ment were included in this analysis (N = 2,821). sons unable to walk for a longer period. The second stage consisted of a 400 m walk, which is about the distance an average health older adult can cover in 6 minutes. Participants were asked to walk 400 Measures of body composition m as quickly as possible at a pace that they can maintain. Standard Whole body dual-energy DXA was performed at both the Pittsburgh encouragement was given throughout the test and time was recorded and the Memphis field centers (Hologic 4500A, version 9.03; to the nearest second. A significant proportion of participants were Hologic, Inc., Waltham, MA, USA). In addition, bone mineral–free unable to complete the test (24 per cent) at baseline, and therefore, we ALM and fat mass were derived from the whole body scan. DXA determined associations with inability to complete the 400 m walk as quality assurance measurements were performed at both study sites a measure of mobility disability as defined previously (26). to ensure scanner reliability, and identical patient scan protocols were used for all participants. For soft tissue, the CVs were 1.0 and 2.1 per cent for whole-body lean mass and fat mass, respectively. Total fat Grip strength (27) mass index (FMI) and appendicular lean mass index (ALMI) were Isometric grip strength in (kg) was measured using a hand-held determined from whole-body DXA and converted to age-, sex-, and dynamometer (JAMAR Technologies, Inc., Hatfield, PA). Two trials race-specific Z-scores as described previously (19) using published were performed for each hand. An average of the trials performed nationally representative reference ranges from the National Health on the strongest hand was used for analyses as has previously been and Nutrition Examination Survey (NHANES) (20). described (27). Downloaded from https://academic.oup.com/biomedgerontology/article/74/2/247/4846326 by DeepDyve user on 19 July 2022 Journals of Gerontology: MEDICAL SCIENCES, 2019, Vol. 74, No. 2 249 Incident disability (28, 29) the total 3,075 who had whole-body DXA and adiponectin values We also analyzed adjudicated self-report data on incident phys- recorded. The basic characteristics of the population are presented ical disability from interviewer-administered questionnaires every in Table 1. 6 months. For incident disability, the outcome of interest was time from baseline to any self-reported disability at a subsequent visit, Factors Associated With Adiponectin Levels which was defined as severe difficulty or inability to walk 1/4 mile Associations between baseline factors and log-transformed adi- and/or climb 10 steps, needing equipment to ambulate, or having ponectin levels (per SD) are presented in Table 2. Greater FMI any difficulty performing activities of daily living (i.e. getting in and Z-score, waist circumference, ALMI Z-score, and muscle density out of bed or chairs, bathing or showering, and dressing). were all independently associated with lower adiponectin levels. Better physical functioning was also independently associated with All-cause mortality lower adiponectin levels. An increase in BMI (per 1 kg/m ) since age Time of death was determined from the adjudicated outcomes data 50 was associated with lower adiponectin levels independent of cur- set. All deaths are adjudicated by a central committee for immediate rent body composition. Per cent weight loss (5 or 10 per cent) was and underlying causes of death as determined by established criteria associated with higher adiponectin levels across all weight categories including review of death certificate, all recent hospital records, and in models adjusting for age, sex, and race (Figure 1). interview with the next of kin. Association of Adiponectin With Physical Assessment of a history of weight loss Functioning At enrollment, study participants were asked about their weight at Adiponectin was inversely associated with physical functioning as 50 years of age. This weight was converted to a BMI based on cur- measured by the Health ABC performance score, ability to complete rent height and the change in BMI from age 50 to enrollment was the 400 m walk, and grip strength independent of demographics and calculated. Three categories of per cent weight loss were assessed comorbid conditions (Table 3, Model 1). These associations were (none, 5%–10%, or ≥10%) as has been previously described (30). substantially attenuated for all three outcomes with adjustment for Nearly identical results were obtained in analyses utilizing alterna- FMI Z-score and waist circumference (Table 3, Model 2). Further tive categories of weight loss based on the change in BMI (Category adjustment for ALMI Z-score, muscle density, and a history of 2 2 1 = change ≥−1 kg/m ; Category 2 = change −1 to −3 kg/m ; Category weight loss further attenuated these associations. After adjustment 3 = change <−3 kg/m ; not shown) (31). for these factors, adiponectin remained modestly associated only with the Health ABC performance score (Table 3, Model 3), whereas Statistical analysis other associations were no longer significant. There were no signifi- Adiponectin levels were log-transformed to fit a normal distribution cant interactions by sex (all p for interactions > 0.08). and then standardized so that associations demonstrated represent the effect of one standard deviation greater level. Univariate associa- Association of Adiponectin With Incident Disability tions between adiponectin and prehypothesized factors were assessed and Death using Spearman and Pearson correlations. Factors hypothesized to Incident disability occurred in 2,296 participants among whom the be important included demographics, comorbid conditions (hyper- median time-to-event was 3.0 years. Higher adiponectin level was tension, congestive heart failure, diabetes, history of heart attack, associated with a greater risk of incident disability after adjustment and history of cancer), FMI Z-score, ALMI Z-score, muscle density, weight change since age 50, grip strength, the Health ABC perform- ance score, and completion of the LDCW. Multivariable linear regres- Table 1. Basic Characteristics of the Health ABC Study Sample, sion was utilized to identify independent associations between factors 1997–1998 identified in univariate analysis and adiponectin levels. N 2,821 Independent associations between adiponectin and muscle out- comes were also assessed using multivariable linear regression with Age 74.1 (2.87) adjustment for prehypothesized factors, including total FMI Z-score, Female 51.2% waist circumference, demographics, smoking status, and comorbid Race (% African-American) 41.6% conditions. Independent associations between adiponectin and BMI (kg/m ) 27.3 (4.72) physical functioning measures were assessed in successive models Body composition to assess the impact of adjustment for body composition. Similarly, ALMI (kg/m ) 7.65 (1.36) ALMI Z-score −0.049 (0.89) successive multivariable Cox proportional hazards models assessed FMI (kg/m ) 9.71 (3.44) the impact of adjustment for body composition on the association FMI Z-score −0.27 (0.92) between adiponectin and incident disability and overall mortality. Thigh muscle density (HU) 35.7 (6.8) In all analyses, testing for effect modification by sex was per - Mean Δ BMI since 50 +1.43 (3.70) formed by testing the significance of multiplicative interaction terms Physical functioning in multivariable models. Stratified analyses by sex are provided in Health ABC score 2.20 (0.53) Supplementary Tables 1–6. Completed LDCW, N(%) 2162 (76.6%) Grip strength (kg) 32.3 (10.5) Results Note: ALMI = Appendicular lean mass index; BMI = Body mass index; The details of the study population have been previously published. FMI = Fat mass index; Health ABC = Health Aging and Body Composition; HU = Hounsfield units; LDCW = Long-distance corridor walk. We included 2,821 individuals (1,374 men and 1,447 women) out of Downloaded from https://academic.oup.com/biomedgerontology/article/74/2/247/4846326 by DeepDyve user on 19 July 2022 250 Journals of Gerontology: MEDICAL SCIENCES, 2019, Vol. 74, No. 2 Table 2. Factors Associated With Adiponectin Levels at Baseline in Unviariate and Multivariable Analyses Adiponectin Adiponectin Per 1 SD Per 1 SD Univariate Multivariable*–R = 0.34 β (95% CI) p-Value β (95% CI) p-Value Age (per 10 y) 0.37 (0.25, 0.50) <.001 0.15 (0.036, 0.26) .01 Female 0.57 (0.51, 0.64) <.001 0.48 (0.41, 0.55) <.001 Black −0.53 (−0.60, −0.46) <.001 −0.60 (−0.66, −0.53) <.001 Hypertension −0.097 (−0.14, −0.054) <.001 −0.042 (−0.08, −0.00) .045 Diabetes −0.54 (−0.62, −0.45) <.001 −0.48 (−0.58, −0.38) <.001 Cancer 0.039 (−0.027, 0.10) .25 — — Heart attack −0.027 (−0.069, 0.014) .20 — — CHF −0.020 (−0.057, 0.017) .90 — — Current smoking −0.13 (−0.25, −0.0075) .04 — — Former smoking −0.20 (−0.27, −0.12) <.001 — — Total/abdominal adiposity — — FMI Z-score −0.26 (−0.30, −0.23) <.001 −0.21 (−0.28, −0.14) <.001 Waist circumference (cm) −0.022 (−0.025, −0.019) <.001 −0.0083 (−0.01, −0.004) .001 Muscle outcomes ALMI Z-score −0.29 (−0.33, −0.25) <.001 −0.065 (−0.11, −0.018) .007 Thigh muscle density (per SD) −0.14 (−0.17, −0.010) <.001 −0.25 (−0.29, −0.21) <.001 Weight change since 50 (kg/m ) −0.044 (−0.053, −0.034) <.001 −0.023 (−0.038, −0.014) <.001 Physical function Health ABC performance −0.098 (−0.16, −0.031) .004 −0.11 (−0.19, −0.036) .003 Grip strength (kg) −0.028 (−0.031, −0.024) <.001 — — Completed LDCW −0.048 (−0.13, 0.034) .25 — — Notes: *After stepwise deletion of nonsignificant variables (smoking and grip strength). ALMI = Appendicular lean mass index; CHF = Congestive heart failure; CI = Confidence interval; FMI = Fat Mass Index; Health ABC = Healthy Aging and Body Composition; LDCW = Long-distance Corridor Walk; SD = Standard deviation. smoking [HR 1.17 (1.10, 1.25), p < .001; Table 4, Model 1]. Similar to models evaluating associations with incident disability, the asso- ciation between adiponectin and mortality was attenuated and no longer significant in sequential models adjusting for body compos- ition, muscle density, weight loss, and physical functioning at base- line [HR 1.05 (0.97, 1.13) p = .26; Table 4, Model 3]. The predicted survival was shorter for individuals in the highest adiponectin quar- tile when adjusting for FMI Z-score and waist circumference only (Figure 2A). In contrast, there was no apparent difference in pre- dicted survival by adiponectin quartile after full adjustment for all mediators, including lean mass, muscle density, weight loss, strength, and physical functioning (Figure 2B). The association between adi- ponectin and mortality was not different between men and women (p for interaction = .46 in adjusted models). Figure 1. Adiponectin levels among patients who have lost weight across Discussion BMI categories. Values are adjusted from regression models including age, We found a significant relationship between serum levels of adi- sex, and race. ponectin and historical weight loss, low muscle mass, and low mus- for demographic factors, comorbidities, FMI Z-score, and waist cle density. Thus, the data presented here support the hypothesis circumference (Table 4, Model 1). This association was substan- that adiponectin is a biomarker of adverse body composition in the tially attenuated when further adjusting for ALMI Z-score, muscle context of aging. Weight loss and loss of muscle mass and quality density, and history of weight loss at baseline (Table 4, Model 2). with aging and chronic illness may explain previously noted epide- Adjustment for physical functioning at baseline also further attenu- miological associations observed between adiponectin, poor physical ated the already tenuous relationship (Table 4, Model 3). The asso- functioning, and death among the elderly. Thus, these data suggest ciation between adiponectin and incident disability was not different that, while adiponectin is not likely to play a causal role, it may be between men and women (p for interaction = .64 in adjusted models). an important biomarker of these processes, which themselves affect There were 1,370 deaths among whom the median time-to-event the long-term risk of disability and mortality. was 7.5 years. Greater adiponectin levels (per SD) were associated Adiponectin may represent biomarker of adverse catabolic pro- with greater mortality in models adjusting for FMI Z-scores, waist cesses related to features of frailty. Although the analyses presented circumference, comorbid conditions, demographic variables, and here do not suggest that adiponectin plays a directly causal role in Downloaded from https://academic.oup.com/biomedgerontology/article/74/2/247/4846326 by DeepDyve user on 19 July 2022 Journals of Gerontology: MEDICAL SCIENCES, 2019, Vol. 74, No. 2 251 Table 3. Correlations Between Adiponectin and Physical Functioning in Sequential Multivariable Regression Models Adjusting for Body Composition and Muscle Density Model 1 Model 2 Model 3 B (95% CI) B (95% CI) B (95% CI) Health ABC performance Adiponectin (per SD) −0.068*** −0.036** −0.030** (−0.088, −0.048) (−0.058, −0.016) (−0.051, −0.009) Grip strength Adiponectin (per SD) −0.55*** −0.27 −0.23 (−0.85, −0.24) (−0.60, −0.049) (−0.56, 0.091) OR (95% CI) OR (95% CI) OR (95% CI) Completion of LDCW Adiponectin (per SD) 0.82** 0.88* 0.90 (0.74, 0.91) (0.79, 0.99) (0.81, 1.01) Model 1: Adjusted for age, sex, black race, BMI category, diabetes, HTN, CHF, cancer, MI, smoking, FMI Z-score and waist circumference. Model 2: Model 1 plus adjustment for ALMI Z-score and muscle density. Model 3: Model 2 plus adjustment for % weight loss since age 50. ALMI = Appendicular lean mass index; BMI = Body mass index; CHF = Congestive heart failure; FMI = Fat mass index; Health ABC = Healthy Aging and Body Composition; HTN = Hypertension; LDCW = Long-distance Corridor Walk; OR = Odds ratio. *p < .05; **p < .01; ***p < .001. Table 4. Multivariable Cox Proportional Hazards Models Assessing Associations Between Adiponectin Levels and Incident Disability and Mortality Model 1 Model 2 Model 3 Incident disability HR (95% CI) HR (95% CI) HR (95% CI) Adiponectin (per SD) 1.13 (1.08, 1.19)** 1.05 (0.99, 1.12) 1.05 (0.98, 1.11) FMI Z-score 1.24 (1.16, 1.33)*** 1.11 (1.02, 1.21) 1.00 (0.90, 1.10) Waist circumference (cm) 1.01 (1.00, 1.01)*** 1.01 (1.00, 1.01)** 1.01 (1.00, 1.01) ALMI Z-score — 0.98 (0.91, 1.04) 1.10 (1.02, 1.19)* Muscle density — 0.96 (0.96, 0.97)*** 0.97 (0.96, 0.98)*** Weight loss (v. none) — 5% — 1.07 (0.90, 1.26) 0.97 (0.80, 1.16) 10% — 1.34 (1.14, 1.58)*** 1.19 (0.99, 1.42) Grip strength (kg) — — 0.98 (0.98, 0.99)*** Health ABC performance — — 0.51 (0.46, 0.57)*** Completed LDCW — — 0.73 (0.65, 0.83)*** Mortality HR (95% CI) HR (95% CI) HR (95% CI) 1.17 (1.10, 1.25)*** 1.08 (1.01, 1.16)* 1.05 (0.97, 1.13) Adiponectin (per SD) FMI Z-score 0.88 (0.80, 0.96)** 0.89 (0.79, 0.99)* 0.83 (0.72, 0.94)** Waist circumference (cm) 1.01 (1.00, 1.01)* 1.01 (1.00, 1.02)** 1.01 (1.00, 1.01) ALMI Z-score — 0.88 (0.81, 0.95)** 0.92 (0.84, 1.01) Muscle density — 0.98 (0.97, 0.99)** 0.99 (0.98, 1.00) Weight loss (v. none) — 5% — 1.38 (1.13, 1.67)** 1.19 (0.96, 1.48) 10% — 1.58 (1.32, 1.90)*** 1.34 (1.15, 1.73)** Grip strength (kg) — — 0.98 (0.97, 0.99)** Health ABC performance — — 0.66 (0.58, 0.76)*** Completed LDCW — — 0.71 (0.61, 0.82)*** All models adjusted for age, sex, black race, study site, HTN, CHF, history of any cancer, diabetes, MI, and smoking status. ALMI = Appendicular lean mass index; FMI = Fat mass index; Health ABC = Healthy Aging and Body Composition; HR = Hazard ratio; LDCW = Long- distance Corridor Walk. *p < .05; **p < .01; ***p < .001. promoting disability and premature death, the role of adiponectin as group are substantially higher than controls who may weigh less, but a biomarker and prognostic tool is clarified. Previous studies have have not lost weight (1). The current study supports the hypothesis demonstrated that adiponectin is associated strongly with weight that adiponectin levels are influenced by both weight and weight loss. loss. For example, patients undergoing bariatric surgery have dra- Among the elderly, weight loss that occurs is more likely to be unin- matic increases in adiponectin. The greater levels observed in this tentional (32–34). Therefore, adiponectin may identify unintentional Downloaded from https://academic.oup.com/biomedgerontology/article/74/2/247/4846326 by DeepDyve user on 19 July 2022 252 Journals of Gerontology: MEDICAL SCIENCES, 2019, Vol. 74, No. 2 associated with either better or more adverse outcomes in different clin- ical contexts. Limitations of the current study include the lack of longitudi- nal measures of adiponectin which might clarify the nature of the relationship weight, body composition changes, and changes in the adipokine. Adiponectin exists in a number of forms with dif- ferent physiological functions. Because this study only included total adiponectin levels, we were unable to characterize relation- ships between these different forms. In addition, other adipokines may also be important and were not assessed here. Although this study focused on an at-risk group of elderly patients, this study was unable to evaluate differences in association across the age range. Finally, although we studied a number of hypothesized confound- ers, unmeasured confounding may still be present. For example, it was out of the scope of the current analysis to evaluate the effects of medications on adiponectin. Strengths of the current study include the large sample size in an at-risk population, highly validated esti- mates of body composition, assessment of weight histories, and comprehensive assessment of physical functioning and grip strength. In summary, high adiponectin levels in the elderly are associated with incident disability and early death. However, this relationship is explained as an association between adiponectin and low mus- cle mass and quality, weight loss, and baseline physical function. Adiponectin may therefore represent a biomarker of adverse cata- bolic processes among the elderly (i.e. cachexia and sarcopenia). Supplementary Material Supplementary data are available at The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences online. Figure 2. Survival plots based on multivariable Cox proportional hazards models by adiponectin quartile for (A) partially adjusted model and (B) fully Funding adjusted model. (A) Partially adjusted for age, sex, black race, study site, HTN, CHF, history of any cancer, diabetes, MI, smoking status, FMI Z-score, and This research was supported by National Institute on Aging (NIA) waist circumference. (B) Fully adjusted: further adjusted for ALMI Z-score, Contracts (N01-AG-6-2101; N01-AG-6-2103; N01-AG-6-2106); NIA muscle density, weight change since age 50, Health ABC performance, grip grant (R01-AG028050), and National Institute of Nursing Research grant strength, and completion of the LDCW. (R01-NR012459). J.F.B. is supported by a Veterans Affairs Clinical Science Research & Development Career Development Award (IK2 CX000955). weight loss and catabolic processes associated with the development D.R.W. was supported by National Institutes of Health grant (K12HD068373). of sarcopenia or cachexia. Other studies have shown correlations between adiponectin and cachexia in chronic conditions (congest- ive heart failure, kidney disease, rheumatoid arthritis) (8, 9, 16). Acknowledgments Previous studies have also identified associations between adiponec- Dr. Baker would like to acknowledge the support of a Veterans Affairs tin and mortality in chronic conditions (7–9). Clinical Science Research & Development Career Development Award (IK2 Our study is one of few studies to evaluate associations between CX000955). The contents of this work do not represent the views of the adiponectin and physical functioning and muscle strength among the Department of the Veterans Affairs or the United States Government. This elderly. One previous study demonstrated that adiponectin tracked research was supported in part by the Intramural Research Program of the with functional decline among the elderly (18). The current study National Institutes of Health, National Institute on Aging. does not suggest a causal relationship between adiponectin and physical functioning among the elderly. However, these data do sup- Conflicts of Interest port the hypothesis that high adiponectin levels are a marker of body composition changes that may, themselves, be associated with poor The authors would like to disclose that A.B.N. is the Editor in Chief of the physical functioning. 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Journal
"The Journals of Gerontology - Series A: Biological Sciences and Medical Sciences" – Oxford University Press
Published: Jan 16, 2019
Keywords: body composition; mortality; adiponectin; older adult; physical function; disability; weight reduction