Sarcopenic Obesity Predicts Instrumental Activities of Daily Living Disability in the Elderly Richard N. Baumgartner,* Sharon J. Wayne,* Debra L. Waters,* Ian Janssen,† Dympna Gallagher,‡ and John E. Morley§
Abstract BAUMGARTNER, RICHARD N., SHARON J. WAYNE, DEBRA L. WATERS, IAN JANSSEN, DYMPNA GALLAGHER, AND JOHN E. MORLEY. Sarcopenic obesity predicts instrumental activities of daily living disability in the elderly. Obes Res. 2004;12:1995–2004. Objective: To determine the association of sarcopenic obesity with the onset of Instrumental Activities of Daily Living (IADL) disability in a cohort of 451 elderly men and women followed for up to 8 years. Research Methods and Procedures: Sarcopenic obesity was defined at study baseline as appendicular skeletal muscle mass divided by stature squared ⬍7.26 kg/m2 in men and 5.45 kg/m2 in women and percentage body fat greater than the 60th percentile of the study sample (28% body fat in men and 40% in women). Incident disability was defined as a loss of two or more points from baseline score on the IADL. Subjects with disability at baseline (scores ⬍ 8) were excluded. Cox proportional hazards analysis was used to determine the association of baseline sarcopenic obesity with onset of IADL disability, controlling for potential confounders. Results: Subjects with sarcopenic obesity at baseline were two to three times more likely to report onset of IADL
Received for review December 24, 2003. Accepted in final form September 28, 2004. The costs of publication of this article were defrayed, in part, by the payment of page charges. This article must, therefore, be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. *Aging and Genetic Epidemiology Program, Division of Epidemiology and Preventive Medicine, Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, New Mexico; †Department of Community Health and Epidemiology and School of Physical and Health Education, Queen’s University, Kingston, Ontario, Canada; ‡Obesity Research Center, St. Luke’s-Roosevelt Hospital and Columbia University, New York, New York; and §Geriatric Research and Education Center, St. Louis University VAMC, St. Louis, Missouri. Address correspondence to R. N. Baumgartner, AGE, Surge 215, 2701 Frontier Place, University of New Mexico School of Medicine, Albuquerque, NM 87131. E-mail:
[email protected] Copyright © 2004 NAASO
disability during follow-up than lean sarcopenic or nonsarcopenic obese subjects and those with normal body composition. The relative risk for incident disability in sarcopenic obese subjects was 2.63 (95% confidence interval, 1.19 to 5.85), adjusting for age, sex, physical activity level, length of follow-up, and prevalent morbidity. Discussion: This is the first study, to our knowledge, to indicate that sarcopenic obesity is independently associated with and precedes the onset of IADL disability in the community-dwelling elderly. The etiology of sarcopenic obesity is unknown but may include a combination of decreases in anabolic signals and obesity-associated increases in catabolic signals in old age. Key words: sarcopenic obesity, sarcopenia, obesity, Instrumental Activities of Daily Living disability, aging
Introduction The prevalence of sarcopenia, or a relative deficiency of skeletal muscle mass and strength, increases rapidly after 65 years of age and is significantly associated with functional limitation and physical disability, independent of body fatness, in community-dwelling elderly (1– 6). Estimates of prevalences have varied widely across studies because of differences in criteria for defining sarcopenia and sample characteristics, such as age, sex, ethnicity, socioeconomic status, health status, and body size. The strengths of associations reported have also varied because of differences in methods of measuring functional limitation and disability outcomes and the measurement and statistical control of confounders. With the exception of Janssen et al. (4), who analyzed data from NHANES III, most study samples have been small or not strictly population-based, making results difficult to generalize. Finally, all studies to date have been cross-sectional, leaving open the question of whether sarcopenia and/or obesity precedes or follows the onset of disability. OBESITY RESEARCH Vol. 12 No. 12 December 2004
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Obesity has also been reported to be associated with disability (7,8). Most studies, however, have used BMI, which may systematically misclassify many elderly (9,10). Some studies based on estimates of fat mass and fat-free mass (FFM)1 have reported that increased fat mass is more strongly associated with Instrumental Activities of Daily Living (IADL) disability than low FFM (11–13). Although FFM is highly correlated with muscle mass, the percentage of FFM that is appendicular skeletal muscle varies among individuals and declines with aging (14 –17). Thus, FFM may be a less sensitive measure of sarcopenia than estimates of muscle mass. Differences among studies in age and ethnic composition and prevalence of overweight and obesity may also influence results for the relative strengths of the associations of fat vs. lean body composition with disability. In any case, the various studies, taken together, suggest that both sarcopenia and obesity are associated with disability in community-dwelling elderly. In a previous analysis of cross-sectional data from two separate studies, the population-based New Mexico Elder Health Survey (NMEHS) and the volunteer-cohort New Mexico Aging Process Study (NMAPS), we found that the combination of sarcopenia and obesity, or “sarcopenic obesity,” was more strongly associated with disability than either body composition type alone (18,19). For example, in the population-based NMEHS, the odds ratio for two or more self-reported physical disabilities on the IADL was 8.72 for sarcopenic obesity in men compared with 3.78 for “pure” sarcopenia and 1.34 for obesity, controlling for age, ethnicity (Hispanic vs. non-Hispanic white), smoking, physical activity, alcohol intake, and comorbidity. The corresponding odds ratios in women were 11.98, 2.96, and 2.15, respectively. Similar results were obtained in analyses of data from the NMAPS (18). Sarcopenic obesity was defined in these analyses as having a score on the relative skeletal muscle mass index (appendicular skeletal muscle divided by stature squared) more than ⫺2 SD below the sex-specific mean for a young adult reference population and percentage body fat greater than the sex- and age-specific median. These criteria were recognized to be somewhat arbitrary; however, their application revealed the joint effect of sarcopenia and excess body fatness on IADL disability. To date, we are aware of only two studies that have attempted to replicate these findings for sarcopenic obesity. Sternfeld et al. (13) reported a protective association for a high lean/fat ratio, an index that is inversely correlated with our definition of sarcopenic obesity, thereby providing indirect support. In contrast, Davison et al. (20) cross-classified 2917 men and women ⱖ70 years of age in the NHANES III sample by predicted muscle mass and body
1 Nonstandard abbreviations: FFM, fat-free mass; IADL, Instrumental Activities of Daily Living; NMEHS, New Mexico Elder Health Survey; NMAPS, New Mexico Aging Process Study; NCEP ATPIII, ___; IL-6, interleukin 6; IGF-1, insulin-like growth factor 1.
1996
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fat, using criteria similar to, but not identical to, ours and found no significant associations between sarcopenic obesity and functional limitation. In this study, we used longitudinal data from the NMAPS cohort to test the hypothesis that sarcopenic obesity precedes, and therefore predicts, the onset of IADL disability in community-dwelling elderly who have no disability at baseline. This is the first study that we are aware of to use longitudinal data to determine the direction of the association between body composition and IADL disability in a sample of community-dwelling elderly.
Research Methods and Procedures Subjects The subjects were members of the NMAPS, an ongoing longitudinal cohort study of aging that began in 1980. This study is described in detail in other publications (21). Ninety percent of the participants are non-Hispanic white, 8% are Hispanic, and ⬃2% are nonwhite (black, Asian, or American Indian). To qualify for entry, subjects had to be 60 years of age or older, free of major medical conditions, and living independently in the Albuquerque, NM area. Enrollment criteria were designed to exclude subjects from entry who had significant illness that would preclude their ability to participate in a long-term longitudinal study, such as recent myocardial infarction, significant peripheral vascular disease, insulin-dependent diabetes, hepatic disease, history of internal cancer requiring surgery, radiation therapy, or chemotherapy in the past 10 years, a positive test for hepatitis, and untreated hypertension (systolic blood pressure ⬎ 180 mm Hg; diastolic blood pressure ⬎ 100 mm Hg). Participants were not required to maintain good health to continue in the study. The NMAPS is a “dynamic cohort” in which dropouts and deaths are replaced annually to keep the active cohort at an average of ⬃400 subjects per year. As a result, the number of subjects included in a longitudinal analysis may vary and is generally greater than the number of active participants in any 1 year, because individuals with different baseline years can contribute data. The dropout rate over the 20 years of the NMAPS has averaged ⬃3.6% per year, which is very good for a longitudinal study of elderly people who may be expected to drop out more often because of morbidity, IADL disability, and other causes than younger subjects. Serious morbidity, other than dementia, has been the main cause for dropout from the study (35%), followed by movement from the Albuquerque area (27%). Participants were seen annually for a thorough examination that included a blood draw, measures of body composition, a physical examination by a nurse practitioner, measures of functional and cognitive status, and nutritional assessment. Annual assessments of cognitive and physical functional status, balance and gait, and falls began in 1991, and body composition measurements (other than anthro-
Sarcopenic Obesity and Incident IADL Disability, Baumgartner et al.
pometry) were initiated in 1993. A Lunar DPX DXA (GE/ Lunar Radiation Corp., Madison, WI) was used to measure body composition, including bone mineral content and area bone mineral density, total soft tissue mass, percent body fat, lean soft tissue mass, and appendicular skeletal muscle mass from standard whole body scans (20 to 40 minutes depending on body thickness). The total dose for a whole body scan is ⬍1 Sv. Appendicular skeletal muscle was defined as the sum of the lean soft tissue masses for the arms and legs adjusted for nonmuscle components, following the method of Heymsfield et al. (22). The technical errors of estimates of muscle mass are ⫾3% and ⫾2.5% for the arm and leg, respectively; the precision of percentage body fat is ⫾1.5%. Definition of Sarcopenic Obesity Cut-points to define sarcopenic obesity were based on our previous work (1,18). For the present analyses, subjects were classified as sarcopenic if their relative skeletal muscle mass was ⬍2 SD below the mean of a sample of 229 healthy young (18 to 40 years) adults. For men, this cutpoint was 7.26 kg/m2; for women, it was 5.45 kg/m2. Subjects were classified as obese if their percentage body fat was above the 60th percentile of the study sample. For men, this cut-point was 28% body fat; for women, it was 40% body fat. Based on the combination of sarcopenia and obesity cut-points, subjects were further classified into four groups: sarcopenic obese, sarcopenic nonobese, nonsarcopenic obese, and nonsarcopenic/nonobese. Measurement of Incident IADL disability The IADL questionnaire asks subjects how much help they need to perform nine tasks considered important for independent living: using the telephone, accessing transportation, getting groceries, making meals, doing housework, doing handyman work, doing laundry, taking medications, and managing money (23). There are three possible responses to each of the nine questions: need no help to perform this task, need some help to perform this task, and unable to do this task. Subjects were given one point for each task they reported being able to do without help and zero points for any tasks they were unable to do or needed help in doing. Answers were summed for the nine responses; the maximum score of nine indicated the subject could perform all nine tasks without help, and the minimum score of zero indicated the subject could perform no tasks without at least some help. The current analysis was limited to subjects who had a baseline IADL score of eight or nine, indicating that they were functioning at a high level at the beginning of followup. Subjects were followed for up to 8 years (1993 to 2001) for a drop in function, which was defined as a loss of two or more points from baseline score. Subjects were included in analyses if they had at least one additional IADL score measured after baseline.
Potential Confounders Physical activity was assessed using a modification of the self-administered Health Insurance Plan instrument as described by Pereira et al. (24). The scores on this scale range from 0 to 65, with higher scores indicating greater activity. We have previously shown that physical activity scores on this instrument are correlated with body composition (25). Prevalent diseases were ascertained using a health history questionnaire administered at study entry. Incident diseases were obtained by self-report at each annual visit and verified against medical records. Centralized obesity and the metabolic syndrome are also potent risk factors for IADL disability and could confound associations with sarcopenic obesity (26,27). Consequently, we also created a variable classifying the presence of metabolic syndrome based on National Cholesterol Education Panel, Adult Treatment Panel III criteria (28). Briefly, a participant was considered to have the syndrome if they met three or more of the following criteria: waist circumference ⬎102 cm in men and ⬎88 cm in women; serum triglycerides ⱖ150 mg/dL (1.69 mM); high-density lipoproteincholesterol ⬍40 mg/dL (1.04 mM) in men and ⬍50 mg/dL (1.29 mM) in women; blood pressure ⱖ130/85 mm Hg; and fasting glucose ⱖ110 mg/dL (ⱖ 6.1 mM). Statistical Methods All statistical analyses were conducted using the Statistical Analysis System (SAS Institute, Cary, NC). 2 tests for proportions and t tests or Wilcoxon rank-sum tests for means were used to compare body composition and drop in IADL groups for baseline and follow-up characteristics. Cox proportional hazards analysis was used to determine the association of sarcopenic obesity with decline in functional status while controlling for potential confounding variables, including age, sex, self-reported physical activity, and morbidity. Because incident IADL disability was recorded at annual intervals, tied event times could occur. As a result, we used a variation of the Cox model that takes into consideration tied events caused by the use of a discrete, rather than continuous, time-scale (SAS Ties ⫽ Discrete option). The underlying mathematics can be found in Therneau and Grambsch (29). We did not stratify the sample for race or ethnicity because the numbers of nonwhite and Hispanic minorities were too few for meaningful analysis.
Results Five hundred thirty-six subjects had at least two IADL scores between 1993 and 2001. Of these, 68 were excluded because their baseline score was less than eight. Another 17 subjects were excluded because they had no body composition data in the year they had their first IADL score measured. This left a final sample size of 451. Twenty-six subjects (5.8%) were classified as sarcopenic obese at baseline. During the 8-year follow-up period, 77 OBESITY RESEARCH Vol. 12 No. 12 December 2004
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Table 1. Subject characteristics by sarcopenic obesity status
By outcome Percent with IADL drop Mean (SD) time to IADL drop in years Demographics Percent male Mean (SD) age in years at baseline Mean (SD) activity score at baseline Mean (SD) follow-up time in years Prevalent conditions Cardiovascular disease Hypertension Arthritis/rheumatism Type 2 diabetes Metabolic syndrome† Incident conditions Stroke Type 2 diabetes Heart attack Congestive heart failure Cancer (excludes basal cell) Hip fracture Any fracture Deaths
Sarcopenic obese (N ⴝ 26)
Sarcopenic nonobese (N ⴝ 82)
Nonsarcopenic obese (N ⴝ 146)
Nonsarcopenic nonobese (N ⴝ 197)
p*
38.5% 1.5 (1.1)
14.6% 2.3 (2.0)
15.1% 2.1 (1.7)
16.8% 2.4 (1.8)
0.027 0.588
61.5% 73.9 (6.6) 18.1 (4.9) 4.5 (2.5)
46.3% 74.0 (6.8) 19.8 (5.7) 4.3 (2.4)
34.2% 71.8 (5.9) 17.9 (5.9) 5.5 (2.4)
34.0% 72.7 (6.3) 20.3 (6.5) 4.7 (2.6)
0.013 0.083 0.006 0.001
11.5% 26.9% 65.4% 7.7% 19.2%
18.3% 17.1% 47.6% 1.2% 3.7%
8.2% 36.3% 50.7% 1.4% 37.5%
13.7% 20.8% 54.3% 1.0% 10.7%
0.159 0.003 0.394 0.076 ⬍0.0001
3.8% 0.0% 7.7% 7.7% 7.7% 3.8% 11.5% 7.6%
1.2% 1.2% 3.7% 1.2% 8.5% 0.0% 7.3% 13.4%
2.7% 2.1% 2.7% 0.7% 5.5% 0.0% 10.3% 6.2%
2.5% 1.5% 3.6% 1.0% 4.6% 0.5% 13.7% 10.7%
0.717 0.927 0.567 0.093 0.507 0.145 0.460 0.290
*p Value for difference between sarcopenic obesity groups in percents (2) or means (ANOVA). †Metabolic syndrome defined by NCEP ATPIII criteria.
subjects (17%) experienced a drop in functional status. Table 1 shows that those who were sarcopenic obese at baseline were significantly more likely to develop a loss in functional status than those who were not (p ⬍ 0.03). Time to drop in IADL was also shorter in the sarcopenic obese group (1.5 years) compared with the other groups (2.1 to 2.4 years). A significantly greater percentage (61.5%) of sarcopenic obese subjects was male. Sarcopenic obese and sarcopenic nonobese groups tended to be slightly older (⬃2 years on average) than nonsarcopenic groups. Mean baseline physical activity score was significantly higher in the nonobese than obese groups, regardless of sarcopenia (p ⫽ 0.006). The obese groups were significantly more likely to have prevalent hypertension at baseline than the nonobese groups, regardless of sarcopenia (p ⫽ 0.003). There were nonsignificant trends for an increased incidence of congestive heart failure and hip fracture in the sarcopenic obese compared with the other groups. Only 1.6% (n ⫽ 7) of the 1998
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participants had diagnosed type 2 diabetes at baseline, and only seven incident cases were ascertained during followup. Although the prevalence of type 2 diabetes was somewhat higher in the sarcopenic obese group (7.7%) than the other groups (1.0% to 1.4%), this difference was not statistically significant because of the small number of cases. Moreover, none of the incident cases of type 2 diabetes occurred within the sarcopenic obese group. Overall, the prevalence of the metabolic syndrome was 17.5% in men and 19.1% in women. The prevalence was highest in the nonsarcopenic obese group (37.5%), followed by the sarcopenic obese group (19.2%), and normal group (10.7%), and was lowest in the sarcopenic nonobese group (3.7%). There was no difference among the groups for any of the other prevalent or incident morbidity conditions. A total of 43 deaths occurred during the follow-up period; however, these were not more likely to occur in the sarcopenic obese group (2/26, ⬃8%) than in the other groups (41/426, ⬃9%).
Sarcopenic Obesity and Incident IADL Disability, Baumgartner et al.
Table 2. Subject characteristics by drop in IADL
Demographics Percent male Mean age in years at baseline Mean activity score at baseline Mean follow-up time in years Prevalent conditions Cardiovascular disease Hypertension Arthritis/rheumatism Type 2 diabetes Metabolic syndrome† Incident conditions Stroke Type 2 diabetes Heart attack Congestive heart failure Cancer (excludes basal cell) Hip fracture Any fracture Deaths
IADL drop (N ⴝ 77)
No drop in IADL (N ⴝ 374)
p*
45.5% 78.0 (6.3) 15.8 (4.8) 5.0 (2.3)
36.6% 71.6 (5.7) 20.1 (6.2) 4.9 (2.6)
0.134 ⬍0.0001 ⬍0.0001 0.850
16.9% 36.4% 63.6% 3.9% 19.7%
11.8% 23.3% 50.3% 1.1% 18.3%
0.218 0.016 0.032 0.068 0.766
2.6% 0.0% 1.3% 1.3% 5.2% 0.0% 13.0% 28.6%
2.4% 1.9% 4.0% 1.3% 6.7% 0.5% 10.9% 5.6%
0.921 0.226 0.241 0.979 0.628 0.610 0.520 ⬍0.001
*p Value for difference between sarcopenic obesity groups in percents (2) or means (ANOVA). †Metabolic syndrome defined by NCEP ATPIII criteria.
In Table 2, subjects with a drop in IADL score are compared with those with no drop for baseline and follow-up characteristics. A two-point drop in score, reflecting an increase in self-reported IADL disability, was significantly associated with older age and lower physical activity (p ⬍ 0.0001). Prevalent hypertension and arthritis/rheumatism were significantly higher (p ⬍ 0.05) in the IADL drop compared with the nondrop group. The prevalence of type 2 diabetes was slightly, but not significantly, higher in the IADL drop group (3.9%) compared with the nondrop group (1.1%). There was no significant difference between groups for the prevalence of the metabolic syndrome (19.7% vs. 18.3%). There was no association between drop in IADL score and sex or any of the incident conditions listed in Table 2. A significantly greater percentage of participants with a drop in IADL score, however, died during follow-up (28.6%) compared with those without a drop in IADL (5.6%). In a multivariate proportional hazards model simultaneously contrasting sarcopenic obese, sarcopenic nonobese, and nonsarcopenic obese groups, with the nonsarcopenic nonobese group as the referent category, the hazard ratio
for drop in IADL score was 2.91 (95% confidence interval, 1.36 to 6.21) for the sarcopenic obese group. Hazard ratios for sarcopenic nonobese and nonsarcopenic obese groups were not significantly different from 1.0. Figure 1 shows age-adjusted Kaplan-Meier survival curves contrasting the four body composition groups, in which the markedly shorter time to drop in IADL in the sarcopenic obese group is clearly evident. As a result, the other three groups were combined in the final analyses. Table 3 shows the results of proportional hazards analyses evaluating the effect of sarcopenic obesity on time to drop in IADL score. The unadjusted hazard ratio of 3.17 (95% confidence interval, 1.55 to 6.49) indicates a rate of decline that was three times higher in sarcopenic obese subjects compared with those who were not sarcopenic obese at baseline. Adjustment for age, sex, physical activity score, follow-up time, prevalent hypertension, and arthritis/ rheumatism reduced the hazard ratio to 2.63 (95% confidence interval, 1.19 to 5.85). Cardiovascular disease was not included in the model because it was not associated with either body composition type or incident IADL disability. Sarcopenic obesity remained significantly associated with OBESITY RESEARCH Vol. 12 No. 12 December 2004
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founded with age, sex, physical activity, or major prevalent morbidity.
Discussion
Figure 1: Kaplan-Meier survival curve for time to drop in IADL by body composition type. Adjusted for age at baseline. NS, NO: nonsarcopenic, nonobese; S, NO: sarcopenic, nonobese; NS, O: nonsarcopenic, obese; S, O: sarcopenic, obese.
drop in IADL score (hazard ratio ⫽ 2.48; 95% confidence interval, 1.13 to 5.47) after additional inclusion in the multivariate model of metabolic syndrome (data not shown in Table 3), which did not have a significant independent association with incident IADL disability (hazard ratio ⫽ 0.99; 95% confidence interval, 0.53 to 1.84). There was an increased risk of incident IADL disability for prevalent type 2 diabetes, but the CI was wide because of the small number of cases, and the association was not statistically significant (hazard ratio ⫽ 1.83; 95% confidence interval, 0.32 to 10.57). The inclusion of type 2 diabetes in the model did not further affect the hazard ratio for sarcopenic obesity (data not shown in Table 3). In summary, the sarcopenic obese group had a statistically significant 2.5- to 3.0-fold increased risk compared with the other body composition groups for new self-reported IADL disability. In multivariate analysis, this risk was not substantially con-
This is the first study, to our knowledge, to report that sarcopenic obesity precedes and predicts the onset of IADL disability in a sample of community-dwelling elderly. Our data suggest that nondisabled elderly with sarcopenic obesity are ⬃2.5 times more likely to report subsequent IADL disability over a 7-year follow-up than individuals without sarcopenic obesity, regardless of age, sex, level of habitual physical activity, and morbidity. “Pure” sarcopenia— or sarcopenic nonobesity—and obesity without sarcopenia were not significantly associated with the onset of IADL disability in this study, which contrasts somewhat with reports from previous cross-sectional studies for significant positive associations. There are several limitations of this study that should be recognized. First, the study cohort was small, and sarcopenic obesity was rare, limiting the statistical power to detect associations. The small sample size also limited our ability to analyze potentially confounding associations with incident morbidity. Although our data suggest that the association of sarcopenic obesity with incident IADL disability is independent of major prevalent comorbidities, it remains possible that this association is confounded by underlying, “preclinical” morbidity. Second, the method used to define sarcopenic obesity was relatively arbitrary; there are still no standardized definitions of sarcopenia or obesity, in terms of percentage body fat, for communitydwelling elderly. Third, the NMAPS cohort is not strictly population-based: it is composed of volunteers and the entry criteria exclude those with serious diseases. Thus, our results may not be generalizable to a broader population. On the other hand, the low prevalence and incidence of type 2 diabetes in the NMAPS cohort remove this significant obesity-related cause of IADL disability as a confounder of the effects of sarcopenic obesity in this study.
Table 3. Hazard ratios and 95% confidence intervals for proportional hazards models evaluating the effect of sarcopenic obesity and relevant covariates on time to drop in functional status Unadjusted model 关hazard ratio (95% CI)兴 Sarcopenic obesity Age in years Gender (men ⫽ 1) Activity score Follow-up time in years Prevalent hypertension Prevalent arthritis/rheumatism
2000
3.17 (1.55, 6.49)
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Intermediate model 关hazard ratio (95% CI)兴 2.52 1.13 1.38 0.90 0.83
(1.15, (1.08, (0.83, (0.86, (0.73,
5.51) 1.18) 2.28) 0.95) 0.95)
Full model 关hazard ratio (95% CI)兴 2.63 1.14 1.43 0.91 0.84 1.80 1.13
(1.19, (1.09, (0.85, (0.87, (0.74, (1.06, (0.66,
5.85) 1.19) 2.40) 0.96) 0.96) 3.06) 1.92)
Sarcopenic Obesity and Incident IADL Disability, Baumgartner et al.
We were among the first to develop and apply methods to measure the prevalence of sarcopenia and identify risk factors and sequelae in epidemiological studies (1). We defined sarcopenia as having a value greater than ⫺2 SD below the mean of a young adult reference population for appendicular skeletal muscle mass (measured using DXA) divided by stature squared. Several investigators have subsequently used this index or a similar one based on total muscle mass divided by stature squared to estimate prevalences of sarcopenia and associations with disability (2,3,5,6). However, other researchers have used different indices, including total muscle mass as a percentage of body weight, FFM/stature2, FFM/fat mass ratio, and muscle mass adjusted statistically for height and fat mass (4,13,30,31). Thus, there is still no consensus for any standardized definition of sarcopenia. Recently, Janssen et al. (32) used receiver-operating characteristic curve analysis to identify optimal cut-off values for predicting physical IADL disability from total muscle mass divided by stature squared for 4449 older (⬎60 years) participants in NHANES III. The optimal cut-points associated with high physical IADL disability risk were 5.75 and 8.50 kg/m2 in women and men, respectively. Whereas we did not choose to apply these cut-points in this paper, it should be noted that they are closely similar to the previously defined ones that were used (1). The same issue applies to the definition of “obesity” in the elderly; there is as yet no consensus as to its definition. Several investigators have noted that percentage body fat is systematically higher for any BMI in elderly compared with young adults (9,10,33). Thus, conventional cut-off values for defining overweight and obesity from BMI misclassify many elderly and underestimate true prevalences of excess body fatness, resulting in biased estimates of risk for various outcomes associated with obesity. Gallagher et al. (33) determined percentage body fat values corresponding to BMI values of 25 and 30 kg/m2 in a large sample of 2639 men and women 20 to 79 years of age. A BMI ⬎30 kg/m2 corresponded to a percentage body fat of ⬎43% in white women and ⬎31% in white men 60 to 79 years of age. The cut-points used in the present study were only slightly lower (40% and 28% in women and men, respectively). Thus, our criteria for classifying both “sarcopenia” and “obesity” in this study are supported by other work. To date, few studies of sarcopenia and sarcopenic obesity have been conducted in population-based samples. With regard to this study, the “representativeness” of the NMAPS can be judged by comparison with the population-based study we conducted between 1993 and 1996 in the Albuquerque area: the NMEHS (1). In 1993, the “baseline year” for body composition studies, 17.5% of active NMAPS participants had coronary heart or cardiovascular disease, 32.2% had hypertension, 72.5% had osteoarthritis, and 14.7% had cancer (other than skin cancer diagnosed subse-
quent to entry). The corresponding prevalences among nonHispanic whites in the NMEHS were as follows: coronary heart or cardiovascular disease, 18.2%; hypertension, 32.1%, arthritis, 66.3%; history of cancer, 19.0%. The prevalence of sarcopenic obesity is also similar in the NMAPS (5.8%) compared with the NMEHS (5%). On the other hand, the prevalence of three or more self-reported IADL disabilities is lower in the NAMPS (9.8%) than in the population-based NMEHS (22%). Whereas these results support our previously reported finding in two separate cross-sectional studies that sarcopenic obesity is more strongly associated with IADL disability than either obesity or sarcopenia (18), it is important to note apparently contradictory evidence. Davison et al. (20) reported no significant association using data from NHANES III for 2917 men and women ⱖ70 years of age. Sarcopenia and obesity were defined using criteria similar, but not identical, to this study; however, the outcome was functional limitation rather than IADL disability. Functional limitation was defined as having difficulty with at least three of the following self-reported items: walking onequarter mile; walking up 10 steps without resting; carrying 10 lbs; stooping, crouching, or kneeling; and standing up from an armless chair. The authors noted that an important limitation of their study may have been that percentage body fat and muscle mass were predicted using published anthropometric prediction equations (1,34), rather than measured using DXA, which could have attenuated the associations. However, Janssen et al. (32) applied the same prediction equation to estimate muscle mass in NHANES III and reported significant associations between low relative muscle mass, defined as muscle mass divided by stature squared, and IADL disability, when adjusting for body fat, age, race, smoking, alcohol, and comorbidity. This raises another important issue: disparities among studies for associations may also depend on the definition of the outcomes, i.e., IADL disability as distinct from functional limitation and the methods used to measure these. In our previous cross-sectional studies, we found that sarcopenic obesity was also significantly associated with abnormalities in performance-based tests of balance and gait and reported falls in the past year (18). Type 2 diabetes has been shown to be an important risk factor for disability in some large cross-sectional studies (26,27); thus, there was concern that it could be a significant confounder of the association between sarcopenic obesity and disability in this study. Few participants in the NMAPS cohort had prevalent, diagnosed type 2 diabetes at baseline, and the incidence of this disease was low. Although a nonsignificant, increased risk for incident disability was found for type 2 diabetes, this association was not confounded with the risk for sarcopenic obesity. Taken together, these observations strongly suggest that the association of sarcopenic obesity with incident disability is OBESITY RESEARCH Vol. 12 No. 12 December 2004
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independent of type 2 diabetes. Our analyses indicate that the association of sarcopenic obesity with incident IADL disability is also independent of the metabolic syndrome. Whereas the prevalence of metabolic syndrome was higher in the sarcopenic obese group (19.2%) compared with the “normal” and sarcopenic nonobese groups (10.7% and 3.7%, respectively), the prevalence was highest in the nonsarcopenic obese group (37.5%), indicating that the metabolic syndrome does not substantially overlap with our definition of sarcopenic obesity. Physical activity scores were significantly lower in both sarcopenic obese and nonsarcopenic obese groups (⬃18) than in sarcopenic nonobese or “normal” groups (⬃20) and were substantially lower in participants with a drop in IADL score (⬃16) than in those with no drop (⬃20). Physical activity, however, was not significantly associated with incident IADL disability independent of sarcopenic obesity in the multivariate model. This suggests that both reduced physical activity and incident IADL disability may be consequences of sarcopenic obesity. The etiology of sarcopenia remains poorly understood, and the causes of sarcopenic obesity are unknown (19). From a physiological standpoint, it is intuitive that an individual with excess adiposity and low muscle mass would have more difficulty accomplishing many physical activities than an obese individual with adequate muscle mass, because muscle strength would be insufficient for body weight. In younger adults, muscle mass is generally increased in obesity, which is assumed to be an anatomical response to the stress imposed by increased body weight. Bone mineral density is similarly increased in obesity. Forbes (35) showed that changes in body weight generally involve proportional changes in fat mass and FFM. On average, ⬃30% of any change in weight, gain or loss, is comprised of FFM, mainly muscle. Certain exceptions are recognized to this “rule,” including cachexia and old age. We previously reported data showing that disproportionate changes in fat mass and FFM occur over time in elderly persons (36). FFM can decrease without significant weight change, implying a simultaneous and offsetting increase in fat mass. Thus, it would seem that the physiological relationships linking fat mass and FFM can be modified in some elderly with advancing age, resulting in sarcopenic obesity. Roubenoff (37) has proposed a hypothetical model in which age-related gains in body fat and losses in muscle mass act synergistically over time to produce sarcopenic obesity and associated IADL disability and morbidity. The keys to this hypothetical process are the recent recognition that proinflammatory cytokines, such as interleukin 6 (IL6), increase with age and that adipose tissue is an active endocrine organ that participates in the regulation of appetite, carbohydrate, and fat metabolism through the secretion of certain cytokines, including leptin and tumor necrosis factor ␣, as well as IL-6. The secretion of these hormone2002
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like proinflammatory cytokines is increased in obesity, which is now considered to resemble a kind of subclinical chronic inflammatory state. It has long been recognized that proinflammatory cytokines, tumor necrosis factor ␣ and IL-6 in particular, are associated with muscle wasting in cachexia through stimulation of protein degradation through the ubiquitin–proteosome pathway. Roubenoff has proposed that chronic low levels of these cytokines caused by age-associated increases in adiposity may result in an enhancement of the more subtle, gradual loss of muscle that characterizes sarcopenia (37). Thus, sarcopenia may be accelerated in individuals with long-standing obesity and its associated chronic inflammatory status, resulting in sarcopenic obesity in old age. Data from several studies also support the hypothesis that sarcopenia is associated with age-related decreases in anabolic signals, principally testosterone and insulin-like growth factor 1 (IGF-1) (25,38 – 40). We previously noted that sarcopenic obese men in the NMAPS had significantly lower serum total testosterone and IGF-1 levels than other body composition types, including sarcopenic nonobese men (18). Unfortunately, these associations were not significant in women; thus, the role of these anabolic hormones in sarcopenic obesity in women is less clear. Recently, Kenney et al. (6) reported that sarcopenia was associated with serum testosterone levels in women and that prevalences of sarcopenia were similar in women taking vs. not taking hormone replacement therapy, suggesting no association with estrogen. Payette et al. (40) recently reported that a 2-year loss of FFM was associated with serum IGF-1 in men and with IL-6 production in women, 72 to 92 years of age at baseline. Taken together, these data suggest that sarcopenic obesity may result from the combination of decreases in anabolic signals and obesity-associated increases in catabolic signals in old age, with possible sex differences in the relative influences of these signals. In summary, sarcopenic obesity in old age is more strongly associated with IADL disability than either sarcopenia or obesity per se in the NMAPS. These findings need to be replicated in other, larger cohort studies with suitable data for body composition, IADL disability, and functional status. Further research is needed on the etiology of sarcopenic obesity as a late-life body composition disorder that is most strongly predictive of disability in old age.
Acknowledgments This work was supported by NIH Grants R01 AG10149 and AG02049. References 1. Baumgartner RN, Koehler KM, Gallagher D, et al. Epidemiology of sarcopenia among the elderly in New Mexico. Am J Epidemiol. 1998;147:755– 63.
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2. Melton LJ, Khosla S, Crowson CS, O’Connor MK, O’Fallon WM, Riggs BL. Epidemiology of sarcopenia. J Am Geriatr Soc. 2000;48:625–30. 3. Tanko LB, Movsesyan L, Mouritzen U, Christiansen C, Svendsen OL. Appendicular lean tissue mass and the prevalence of sarcopenia among healthy women. Metabolism. 2002; 51:69 –74. 4. Janssen I, Heymsfield SB, Ross R. Low relative skeletal muscle mass (sarcopenia) in older persons is associated with functional impairment and physical IADL disability. J Am Geriatr Soc. 2002;50:889 –96. 5. Iannuzzi-Sucich M, Prestwood K, Kenny A. Prevalence of sarcopenia and predictors of skeletal muscle mass in healthy, older men and women. J Gerontol. 2002;57:M772–7. 6. Kenney A, Dawson L, Kleppinger A, Iannuzzi-Sucich M, Judge JO. Prevalence of sarcopenia and predictors of skeletal muscle mass in nonobese women who are long-term users of estrogen-replacement therapy. J Gerontol. 2003;58:436 – 40. 7. Jensen GL, Friedmann JM. Obesity is associated with functional decline in community-dwelling rural older persons. J Am Geriatr Soc. 2002;50:918 –23. 8. Friedman JM, Elasy T, Jensen GL. The relationship between body mass index and self-reported functional limitation among older adults: a gender difference. J Am Geriatr Soc. 2001;49:398 – 403. 9. Baumgartner RN, Heymsfield SB, Roche AF. Human body composition and chronic disease. Obes Res. 1995;3:73–96. 10. Gallagher D, Visser M, Sepulveda D, Pierson RN, Harris T, Heymsfield SB. How useful is body mass index for comparison of body fatness across age, sex, and ethnic groups? Am J Epidemiol. 1996;143:228 –39. 11. Visser M, Langlois J, Guralnik JM, et al. High body fatness, but not low fat-free mass, predicts IADL disability in older men and women: the Cardiovascular Health Study. Am J Clin Nutr. 1998;68:584 –90. 12. Visser M, Harris TB, Langlois J, et al. Body fat and skeletal muscle mass in relation to physical IADL disability in very old men and women of the Framingham Heart Study. J Gerontol. 1998;53:M214 –21. 13. Sternfeld B, Ngo L, Satariano WA, Tager IB. Associations of body composition with physical performance and selfreported functional limitation in elderly men and women. Am J Epidemiol. 2002;156:110 –21. 14. Gallagher D, Visser M, deMeersman RE, et al. Appendicular skeletal muscle mass: effects of age, gender, and ethnicity. J Appl Physiol. 1997;83:229 –39. 15. Janssen I, Heymsfield SB, Wang ZM, Ross R. Skeletal muscle mass and distribution in 468 men and women aged 18 – 88 yr. J Appl Physiol. 2000;89:81– 8. 16. Wang ZM, Heo M, Lee RC, Kotler DP, Withers RT, Heymsfield SB. Muscularity in adult humans: proportion of adipose tissue-free body mass as skeletal muscle. Am J Human Biol. 2001;13:612–9. 17. Kyle UG, Genton L, Hans D, Karsegard L, Slosman DO, Pichard C. Age-related differences in fat-free mass; skeletal muscle; body cell mass and fat mass between 18 and 94 years. Eur J Clin Nutr. 2001;55:663–72. 18. Baumgartner RN. Body composition in healthy aging. Ann N Y Acad Sci. 2000;904:437– 48.
19. Morley JE, Baumgartner RN, Roubenoff R, Mayer J, Nair KS. Sarcopenia. J Lab Clin Med. 2001;137:231– 43. 20. Davison KK, Ford ES, Cogswell ME, Dietz WH. Percentage of body fat and body mass index are associated with mobility limitations in people aged 70 and older from NHANES III. J Am Geriatr Soc. 2002;50:1802–9. 21. Garry PJ, Owen GM, Eldridge TO. The New Mexico Aging Process Study. Albuquerque, NM: University of New Mexico Press; 1997. 22. Heymsfield SB, Smith R, Aulet M, et al. Appendicular skeletal muscle mass—measurement by dual photon absorptiometry. Am J Clin Nutr. 1990;52:214 – 8. 23. Lawton MP, Brody EM. Assessment of older people—self maintaining and instrumental activities of daily living. Gerontologist. 1969;9:179 – 83. 24. Pereira MA, Fitzgerald SJ, Gregg EW, et al. A collection of physical activity questionnaires for health related research. Med Sci Sports Exerc 1997;29:S39 – 40. 25. Baumgartner RN, Waters DL, Gallagher D, Morley JE, Garry PJ. Predictors of skeletal muscle mass in elderly men and women. Mech Ageing Dev. 1999;107:123–36. 26. Gregg E, Mangione C, Cauley J, et al. Diabetes and incidence of physical IADL disability and functional decline among older women. Diabetes. 2000;49:A192. 27. Maty SC, Fried LP, Volpato S, Williamson J, Brancati FL, Blaum CS. Patterns of IADL disability related to diabetes mellitus in older women. J Gerontol. 2004;59:148 –53. 28. Ford ES, Giles WH, Dietz WH. Prevalence of the metabolic syndrome among US adults: findings from the Third National Health and Nutrition Examination Survey. JAMA. 2002;287: 356 –9. 29. Therneau TM, Grambsch PM. Modeling Survival Data: Extending the Cox Model. New York: Springer-Verlag; 2000. 30. Castillo EM, Goodman-Gruen D, Kritz-Silverstein D, Morton DJ, Wingard DL, Barrett-Connor E. Sarcopenia in elderly men and women—the Rancho Bernardo Study. Am J Prev Med. 2003;25:226 –31. 31. Newman AB, Visser M, Kupelian V, et al. Defining sarcopenia in older adults: a comparison of two approaches. The Health Aging and Body Composition study. J Am Geriatr Soc. 2002;50:S68 –S68. 32. Janssen I, Baumgartner RN, Ross R, Rosenberg IH, Roubenoff R. Skeletal muscle cutpoints associated with elevated physical IADL disability risk in older men and women. Am J Epidemiol. 2004;159:413–21. 33. Gallagher D, Heymsfield SB, Heo M, Jebb SA, Murgatroyd PR, Sakamoto Y. Healthy percentage body fat ranges: an approach for developing guidelines based on body mass index. Am J Clin Nutr. 2000;72:694 –701. 34. Janssen I, Heymsfield SB, Baumgartner RN, Ross R. Estimation of skeletal muscle mass by bioelectrical impedance analysis. J Appl Physiol. 2000;89:465–71. 35. Forbes GB. Longitudinal changes in adult fat-free mass: influence of body weight. Am J Clin Nutr. 1999;70:1025–31. 36. Gallagher D, Ruts E, Visser M, et al. Weight stability masks sarcopenia in elderly men and women. Am J Physiol. 2000; 279:E366 –75. 37. Roubenoff R. Catabolism of aging: is it an inflammatory process? Curr Opin Clin Nutr Metab Care. 2003;6:295–9. OBESITY RESEARCH Vol. 12 No. 12 December 2004
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Sarcopenic Obesity and Incident IADL Disability, Baumgartner et al.
38. van den Beld AW, de Jong FH, Grobbee DE, Pols HAP, Lamberts SWJ. Measures of bioavailable serum testosterone and estradiol and their relationships with muscle strength, bone density, and body composition in elderly men. J Clin Endocrinol Metab. 2000;85:3276 – 82. 39. Wittert GA, Chapman IM, Haren MT, Mackintosh S, Coates P, Morley JE. Oral testosterone supplementation
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increases muscle and decreases fat mass in healthy elderly males with low-normal gonadal status. J Gerontol. 2003; 58:618 –25. 40. Payette H, Roubenoff R, Jacques PF, et al. Insulin-like growth factor-1 and interleukin 6 predict sarcopenia in very old community-living men and women: the Framingham Heart Study. J Am Geriatr Soc. 2003;51:1237– 43.