Is the Metabolic Syndrome, With or Without Diabetes, Associated With Progressive Disability in Older Mexican Americans?

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1 Journal of Gerontology: MEDICAL SCIENCES 2007, Vol. 62A, No. 7, Copyright 2007 by The Gerontological Society of America Is the Metabolic Syndrome, With or Without Diabetes, Associated With Progressive Disability in Older Mexican Americans? Caroline S. Blaum, 1 Nancy A. West, 2 and Mary N. Haan 2 1 University of Michigan Medical School and Ann Arbor Department of Veterans Affairs Medical Center GRECC, and 2 University of Michigan School of Public Health, Ann Arbor. Background. The metabolic syndrome (MetS) is highly prevalent in the growing U.S. Latino population. We hypothesize that MetS, with or without diabetes, is associated with progressive disability in older Mexican Americans. Methods. Data from Mexican Americans years old participating in the Sacramento Area Latino Study on Aging (SALSA) were analyzed from baseline through 3 years (3 years of follow-up). Disability was assessed by self-reported limitations in activities of daily living (ADLs), instrumental ADLs (IADLs), and mobility/strength tasks. MetS (46% of sample) was defined by National Cholesterol Education Program (NCEP) Adult Treatment Panel III criteria. Diabetes (DM, 33%) was defined by fasting blood sugar. 125 mg/dl, physician diagnosis, and/or medication use. Four metabolic groups were defined: MetS with diabetes (MetSþDMþ, n ¼ 402); MetS without diabetes (MetSþDM, n ¼ 330); diabetes without MetS (MetS DMþ, n ¼ 125); and neither (MetS DM, n ¼ 749). Generalized estimating equation (GEE) regression models were used to evaluate the effect of metabolic group on physical limitations and disability changes over time. Results. Diabetes, with or without MetS, was associated with a higher percent rate of increase over 3 years in ADL and IADL disability than was no diabetes, even after controlling for demographics, body mass index (BMI), and incident disease. The mean ADL score had a 35% higher rate of increase (higher ¼ more impairment) for the MetSþDMþ group and 68% higher for the MetS DMþ group. Results for IADL were similar. The baseline MetS, without or with diabetes, was associated with a significantly higher rate of increase in mobility/strength limitations (8% and 36.5%, respectively). Conclusions. In older Mexican Americans, MetS is associated with progressive limitations in mobility and strength. Preventing progressive mobility/strength limitations may require assessing and treating these impairments in people with MetS regardless of the presence of diabetes. However, preventing the progression of MetS without to MetS with diabetes may be important to limit the progression of ADL and IADL disability found in people with MetS and diabetes. THE metabolic syndrome (MetS), a cluster of cardiovascular risk factors associated with insulin resistance, obesity, and dyslipidemia (1,2), is highly prevalent in the rapidly growing Latino population of the United States, especially older Latinos (3). The current definition of the MetS, detailed in the 2001 National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel [ATP] III) (4), includes the presence of three or more of the following: abdominal obesity, hypertriglyceridemia, low high-density lipoprotein (HDL) cholesterol, high blood pressure, and high fasting glucose (including impaired fasting glucose and diabetes). Recent nationally representative data have shown that the agespecific prevalence of the MetS in Mexican Americans, at 32%, is the highest among the major ethnic groups in the United States (1). Recently the usefulness of MetS as a concept has been questioned (5,6), partly because its definition is imprecise. For example, some persons with MetS have type 2 diabetes, but others have impaired glucose tolerance and are known to have high risk for diabetes (7). Some people with diabetes do not have the metabolic syndrome; some of these people have type 2 diabetes, but some do not. (Generally, type 2 diabetes and diabetes (abbreviated as DM) are used interchangeably in this paper, except when referring to people with diabetes but not the metabolic syndrome.) Factor analysis has shown that different physiological domains are subsumed under the MetS rubric (8), which may or may not have a similar underlying genetic or physiological basis. Finally, the clinical usefulness of MetS is controversial (6,9). Whether or not MetS proves useful for clinical or research purposes, individuals identified as having MetS are at risk for atherosclerotic diseases and either have, or have high risk for, type 2 diabetes (7). MetS has also been shown to be associated with increased risk for cardiovascular deaths (10,11), strokes (12), and cardiovascular disease (13 15), and, in those with peripheral vascular disease but not type 2 diabetes, impaired physical function (16). In addition to its vascular complications, type 2 diabetes is also well known to be associated with disability (17). This diabetes-related disability, which is evident over a broad spectrum of disability measures, is not entirely explained by atherosclerotic complications of diabetes and appears also to be related to microvascular complications and other, less well understood, effects of diabetes (18), perhaps even hyperglycemia itself (19). Among older Latinos, diabetes has been shown to be associated with worsening functional disability and cognitive decline over 766

2 MetS AND DISABILITY IN LATINOS years even after controlling for atherosclerotic complications and comorbidities (20). It is not known whether MetS is also associated with increased risk of disability, and few studies of disability in diabetes have specifically evaluated the role of MetS. In Latinos, the MetS, with or without type 2 diabetes, is present in 1/3 (or more) of the population, and its incidence and prevalence have been shown to be increasing (21,22). Therefore, it is important to understand the relationship of MetS to physical impairment and disability in Latinos, and how that relationship is affected by diabetes, obesity, and atherosclerotic diseases which often coexist with MetS. The goal of this research is to evaluate MetS in a cohort of older Mexican Americans to determine if the MetS, with or without diabetes, is associated with progression of functional impairment and disability over time. We used data from the Sacramento Area Latino Study on Aging (SALSA) (23), an ongoing cohort study of 1789 Latinos aged 60 years and older, which was designed to study health in older Latinos. METHODS Study Population and Recruitment Study participants were residents of the Sacramento Metropolitan Statistical Area and surrounding counties, both urban and rural. People eligible to participate were 60 years old or older in 1998 and self-designated as Latino. The multistage sampling methodology has been explained in detail and was published previously (23). Briefly, the sampling frame for SALSA involved identifying 1990 census tracts in the target area and updating them with 1998 census information to account for population changes. Census tracts where the percentage of eligible people was at least 5% were selected for the target population. Participants were contacted by mail, by phone, and finally, by door-todoor neighborhood enumeration. The overall response rate in persons contacted was 85%. At baseline ( ), 1789 people were enrolled in the study. Approximately 22% of the total eligible population of the Sacramento Metropolitan Statistical Area and surrounding counties was recruited, and the sample was highly representative of older Hispanic residents in the target area. The analytic sample for our study includes all study participants with variables available to characterize MetS and diabetes status who were self-respondents (n ¼ 1606/1789, 89.7%). SALSA was designed as a longitudinal panel study. Baseline data collection occurred in The first, second, and third follow-up visits occurred in 2000, 2001, and Our analysis uses data from baseline through year 3 (2002). Variables and Their Measurement All field staff were bilingual in Spanish and English, and participants were interviewed in their language of choice. All data collection for variables used in this study was done in the participants homes. Baseline data included a structured interview, directed physical assessment, and results of fasting laboratory tests. Information from the structured interview was also collected at the first, second, and third follow-up visits, and our analyses use longitudinal information from these interviews. Participants were asked questions about lifestyle, functioning and disability, medical diagnoses and medications, depressive symptoms, cognitive functioning, and acculturation. The targeted physical evaluation (only baseline used for our study) included blood pressure, weight, height, and waist-to-hip ratio. At baseline, fasting blood samples were collected for glucose, insulin, and lipids. The dependent variables were measures of function, grouped in three ways: ADLs (activities of daily living); IADLs (instrumental activities of daily living); and mobility/ strength tasks (tasks requiring mobility and/or strength). There were 7 ADL items (walking across a small room, bathing, brushing hair/teeth, eating, dressing, moving from bed to chair, using the toilet), 5 IADL items (using telephone, managing money, doing all cooking alone, doing heavy housework alone, shopping), 10 mobility/strength items (pulling/pushing large object, stooping/crouching/ kneeling, lifting/carrying 10 lb, reaching arms above shoulders, getting up from stooping position, standing up from a chair, walking 1 flight of stairs, walking up 10 stairs, writing/handling small objects, walking ¼ mile). All 22 items were measured on a 4-point scale: 0 ¼ no difficulty to 3 ¼ severe difficulty or unable. Composite variables were constructed creating an ADL score range of 0 21; an IADL score range of 0 15; and a mobility/strength score range of The presence of MetS at baseline was measured using the ATP III definition, which is having at least three of the following: waist circumference. 102 cm in men and. 88 cm in women; fasting serum triglycerides 150 mg/dl; HDL cholesterol levels, 40 mg/dl in men and, 50 mg/ dl in women; blood pressure of 130/85 mmhg; fasting serum glucose level of 110 mg/dl. Type 2 diabetes was ascertained by determining use of a diabetic medication, self-report of a physician s diagnosis, or fasting glucose of 126 ml/dl. Hypertension was considered to be present if the person was taking antihypertensive medications or if blood pressure was 130/85 mmhg without medications. Chronic diseases were ascertained by self-report of a physician s diagnosis at baseline and at follow-up interviews. Intermittent claudication was measured by the presence of symptoms. Education was measured as years of formal schooling. The Center for Epidemiologic Studies Depression Scale (CESD; 24) was used to assess depressive symptoms. Statistical Approach The sample was divided into four mutually exclusive metabolic groups: no MetS and no diabetes (DM) (MetS DM, n ¼ 749); with MetS, no DM (MetSþDM, n ¼ 330); no MetS, with DM (MetS DMþ, n ¼ 125); or both MetS and DM (MetSþDMþ, n ¼ 402). These groups were compared with respect to baseline characteristics including demographics, comorbid conditions (myocardial infarction, stroke, heart failure, intermittent claudication, arthritis of the knee or hip, depressive symptoms), and MetS components. Items used to develop the dependent composite variables

3 768 BLAUM ET AL. (ADL, IADL, mobility/strength tasks) were examined by factor analysis to determine patterns, and results were consistent with the generally considered item classification that was used, as detailed above. The mean scores for these three composite dependent variables were plotted at baseline and for 3 follow-up years for each metabolic group. Each of these composite outcome variables was a finite set of non-negative integer values not normally distributed, so all were analyzed as ordinal measures. The three distributions were highly right-skewed, had a high frequency of scores of 0, and had a variance much greater than the mean. For the multivariate evaluation of each outcome, the negative binomial model (25) provided an improved fit to the data compared to the Poisson regression model and facilitated the use of generalized estimating equations (GEE) methodology of parameter estimation for correlated discrete longitudinal data. GEE requires data missing completely at random (26), so we evaluated the missing data mechanism. At baseline, 173 people (9.7%) were missing the variables that define MetS, and these individuals were excluded from analysis. Cumulative mortality over the 3 years of follow-up was 6.3% (112 people), ranging from 4.1% for the MetS DM group to 10.4% for the MetS DMþ group; persons who died are excluded from analyses. Missing data due to nonresponse or loss to follow-up were nearly 36% for ADL, IADL, and strength/mobility scores by year 3, and the mechanism was nonrandom. For example, at follow-up year 3, the baseline mobility/strength score was for persons with no missing data, for persons with an item missing or persons lost to follow-up, for persons who died; all scores were significantly different. Therefore, to use GEE, multiple imputation was used to impute missing data in both the outcomes and the covariates according to the procedure described by Raghunathan and colleagues (27) using IVEware (28). This method takes advantage of observed covariates related to the missing data to estimate an imputation model. Our model included demographic variables, educational status, measures of individual metabolic abnormalities of MetS, CESD score, comorbid conditions and outcomes of interest, and individual items used for the composite scores of ADL, IADL, and mobility/strength measures. Eight imputed data sets were used in the analyses to account for variability present in the missing data (29). Separate multivariate models were evaluated for each of the three dependent variables: ADLs, IADLs, and mobility/ strength tasks. For each dependent variable, the model first included only the four metabolic groups and age. (Model 1) A subsequent model then added gender, education and an Age 3 Time interaction term to account for age-related differential decline (Model 2). Then, a third model included the previous covariates and added baseline body mass index (BMI) and comorbid conditions as time-varying covariates. When BMI or an incident chronic condition was significant, it was retained as a control in the model reported (Model 3). Model results are expressed as percent increase in the rate of change of the score of the dependent variable over the 3 years of follow-up. All analyses were done using PC-SAS version 8.1 (30). RESULTS Table 1 describes the characteristics of the study sample by metabolic group, as well as characteristics of the total sample. More than 45% of the sample have MetS. Among persons with diabetes, MetS is present in. 75%. The mean BMI for the entire sample is just below the World Health Organization (WHO) definition of obese (31), at 29.5 kg/m 2. As expected, persons with MetS (with or without DM) tend to have higher BMIs. The proportions of reported cardiovascular disease, other than claudication, are not significantly different among persons with MetSþDM than among those with MetS DM. The group with DM but without MetS (7.8%) has a higher proportion of men, is slightly older, and has a lower BMI than the groups with MetS. The prevalence of stroke, myocardial infarction, and claudication in this group is intermediate between the MetSþDM and MetSþDMþ groups. For ADL and IADL scores, both DM groups have more impairment (higher scores) than the groups without DM. For ADLs and IADLs, the MetS DMþ group has the highest scores; for mobility/strength limitations, the MetSþDMþ group has the highest score. Table 1 also gives the frequencies of the five components of MetS in each of the four metabolic groups and in the total sample. More than 60% of all the participants have blood pressure 130/85 mmhg. Among the group with MetS DMþ, 47.6% meet blood pressure criteria for MetS, although abdominal obesity and dyslipidemia are markedly less prevalent than in any other group, including the group with neither MetS nor DM (MetS DM ). Figure 1 is an unadjusted plot of the three dependent variables over the follow-up time by metabolic group status at baseline. For the ADLs, there are minimal differences between MetS DM and MetSþDM at baseline and throughout the follow-up. MetSþDMþ is also similar at baseline, but ADL disability increases during follow-up, and MetS DMþ demonstrates more impairment at baseline and throughout follow-up. For IADL disability, MetS DM and MetSþDM disability levels begin at a similar point and increase. The other two groups demonstrate higher impairment at baseline and continue to show increasing impairment throughout follow-up. The curves suggest an interaction between the rate of change of the MetSþDMþ groups versus the other three groups which was statistically significant in multivariate testing. For mobility/strength measures, the MetSþDM group is between the MetS DM and the two DM groups, and the MetSþDMþ group appears to have a different slope than the other three groups and to worsen more rapidly over time, but no interaction was significant. Tables 2, 3, and 4 illustrate results from the multivariate analyses using GEE regression. The numbers in the tables represent the percent increases (worsening) in the rates of change of the dependent variables scores over 3 years that were associated with MetS groups and model covariates. For all models, the MetS DM group is the reference group to which the mean percent change is compared. Table 2 gives results for ADL scores. For model 1, with only the metabolic groups (adjusted for age), MetS DMþ and MetSþDMþ were both associated with significant percent

4 MetS AND DISABILITY IN LATINOS 769 Table 1. Baseline Characteristics and Prevalence of MetS Components No MetS MetS Total No DM N ¼ 749 DM N ¼ 125 No DM N ¼ 330 DM N ¼ 402 Total Study N ¼ 1606 Population percentage 46.6% 7.8% 20.5% 25.0% Characteristic Female (%) ( p,.001) 70.6 ( p,.001) 63.2 ( p ¼.007) 58.4 Age, y ( p ¼.23) ( p ¼.78) ( p ¼.30) Body mass index ( p ¼.21) ( p,.0001) ( p,.0001) Education, y ( p ¼.52) ( p ¼.02) ( p ¼.01) CESD score ( p ¼.33) ( p ¼.009) ( p,.0001) Stroke, % ( p,.003) 7.6 ( p ¼.22) 15.4 ( p,.001) 9.4 Myocardial infarction, % ( p ¼.3) 7.6 ( p ¼.22) 14.9 ( p,.001) 8.7 Congestive heart failure, % ( p ¼.02) 2.4 ( p ¼.36) 4.0 ( p ¼.01) 2.9 Intermittent claudication, % ( p ¼.13) 9.2 ( p ¼.06) 12.7 ( p,.001) 8.8 Arthritis in knee or hip, % ( p ¼.46) 40.6 ( p,.0001) 42.5 ( p,.001) 34.7 ADL total score ( p ¼.07) ( p ¼.71) ( p ¼.01) IADL total score ( p ¼.0016) ( p ¼.40) ( p,.0001) Mobility/strength total score ( p ¼.037) ( p ¼.002) ( p,.0001) MetS component* Waist circumference, % ( p ¼.0013) 87.3 ( p,.0001) 79.4 ( p,.0001) 56.7 Triglycerides, % ( p ¼.0001) 86.7 ( p,.0001) 74.1 ( p,.0001) 53.6 HDL cholesterol, % ( p ¼.0008) 61.8 ( p,.0001) 53.7 ( p,.0001) 33.0 Blood pressure, % y ( p ¼.0696) 77.1 ( p,.0001) 84.0 ( p,.0001) 61.0 Fasting glucose, % z ( p,.0001) 25.5 ( p,.0001) 96.3 ( p,.0001) 38.4 Notes: Data are means 6 standard error unless otherwise indicated. Values of p refer to differences in means or percentages between a group and the group that has No MetS and No DM. *MetS components defined by the National Cholesterol Education Program are as follows: waist circumference: men. 102 cm, women. 88 cm; triglycerides: 150 mg/dl; HDL cholesterol: men, 40 mg/dl, women, 50 mg/dl; blood pressure: 130/85 mmhg; fasting glucose:. 110 mg/dl. y Includes participants currently using antihypertensive medication or self-report physician diagnosis. z Includes participants who reported currently using antidiabetic medication (insulin or oral agents). MetS ¼ the metabolic syndrome; DM ¼ type 2 diabetes except when referring to group with no MetS, when type of diabetes is not clear; CESD ¼ Center for Epidemiologic Studies Depression Scale; ADL ¼ activities of daily living; IADL ¼ instrumental ADL; HDL ¼ high-density lipoprotein. increases in the rates of change of ADL scores, 63% and 41%, respectively, over the 3-year follow-up. After controlling for gender, education, and the Age 3 Time in Model 2, these percent changes increased. However, controlling for incident comorbid conditions in Model 3 that were significant in the model (congestive heart failure, stroke, claudication, depressive symptoms; BMI was not significant) attenuated (i.e., decreased) these percent changes; attenuation for the MetSþDMþ group was the most pronounced, compared to the other groups. Table 3 gives results for IADL scores associated with each metabolic group. Again, despite attenuation after control for significant incident comorbidities (BMI was not significant), both DMþ groups, particularly the MetSþDMþ group, were associated with significant percent increases (worsening) in the rates of change in IADL scores over 3 years. Table 4 shows changes in mobility/strength task limitation rates of increase over the 3 years of follow-up, in the same three sequential models. After controlling for significant incident disease and BMI (significant in this model), MetSþDM, MetS DMþ, and MetSþDMþ all showed significant percent increases in the rates of change of the scores over 3 years: 8%, 43%, and 36.5%, respectively. DISCUSSION In older Mexican Americans, DM with or without MetS demonstrates increases in functional limitations and disability over 3 years even after adjustment for aging effects, BMI, and onset of new comorbidities. However, even without DM at baseline, MetS is associated with progression of mobility/strength limitations over 3 years, although not with progression of ADL/IADL disability. This association is reasonable because mobility and strength limitations are considered to be earlier in the disablement pathway that results in IADL and ADL disability (32). The relationship of the MetS, in the absence of DM, with mobility/strength impairment may occur because of the association of mobility and strength limitations with obesity (33), common in people with MetS. However, in our data, both MetS and BMI were independently and directly associated with mobility/strength limitations. Alternatively, or in addition, mildly elevated glucose, or preclinical or clinical atherosclerotic disease already present in some people with MetS (10,34), may help to explain the association of MetS with mobility/strength limitations. Regardless, our results suggest that mobility/strength impairments may occur during MetS before DM develops. Such mobility/strength impairments may make it difficult for older adults with MetS to begin to increase physical activity on their own, a potential hypothesis for investigation. Because DM has been shown to be preventable through lifestyle changes as well as medication in some people with high risk of DM due to obesity, inactivity, and glucose intolerance, this hypothesis could have relevance for diabetes prevention interventions (35,36).

5 770 BLAUM ET AL. Figure 1. Worsening scores on three impairment measurements over a 3-year period. The y axis: standardized mean of each score, which corrects for the difference in scale. The actual ranges of original scales are: activities of daily living (ADL) scores 0 21, instrumental ADL (IADL) scores 0 15, and mobility scores The association of ADL and IADL disability progression with diabetes, with or without MetS, is consistent with substantial research showing that obesity and atherosclerotic diseases do not completely explain diabetes-associated disability (17 19). The finding of diabetes without MetS is not unexpected. The prevalence of this group in our data is consistent with other epidemiologic studies that have demonstrated a low prevalence of a group of insulinsensitive DM patients with primarily an insulin-secretory defect (37). In our sample, this group of people with

6 MetS AND DISABILITY IN LATINOS 771 Table 2. Percent Change in the Rate of Increase (Worsening) in ADL Score Associated With MetS Groups (Compared to Reference Group) From Regression Models Using GEE After Multiple Imputation Procedure for Missing Values Group Model 1 Model 2 Model 3 MetS DM Ref Ref Ref MetSþ DM 9.5% 7.9% 5.2% MetS DMþ 63.3%* 87.5%* 68.1%* MetSþ DMþ 40.9%* 52.6%* 34.9%* Notes: Analysis in Model 1 controlled for age; Model 2 controlled for age, gender, education, and Time 3 Age interaction; Model 3 controlled for Model 2 covariates plus incident myocardial infarction, congestive heart failure, intermittent claudication, stroke, Center for Epidemiologic Studies Depression Scale score, and arthritis of hip and knee. *p,.001. ADL ¼ activities of daily living; GEE ¼ generalized estimating equations; MetS ¼ the metabolic syndrome; DM ¼ type 2 diabetes except when referring to group with no MetS, when type of diabetes is not clear; Ref ¼ reference group. diabetes but without MetS is likely a heterogeneous group. Research has demonstrated that MetS is not synonymous with insulin resistance (38) and that misclassification occurs. Similarly, factor analysis has demonstrated that a physiologically heterogeneous group of people is classified has having MetS (5). In our data, Latinos with diabetes who do not meet criteria for MetS may be a mixture of persons with diabetes who are insulin sensitive but with low insulin secretion, people who are misclassified as MetS but are insulin resistant, people who do not quite meet criteria for MetS but may have two characteristics or may just miss the defined criteria; a few may even be type 1. We did not investigate this group in our data because we do not have the variables necessary to fully characterize their metabolic status; this is a limitation of this study. However, compared to literature describing in detail the metabolic status of insulin-sensitive DM patients, our group had a higher prevalence of hypertension and atherosclerotic conditions (39), probably related to both misclassification and their Table 3. Percent Change in the Rate of Increase (Worsening) in IADL Score Associated With MetS Groups (Compared to Reference Group) From Regression Models Using GEE After Multiple Imputation Procedure for Missing Values Group Model 1 Model 2 Model 3 MetS DM Ref Ref Ref MetSþ DM 9.6% 8.8% 7.0% MetS DMþ 68.1%* 97.5%* 74.3%* MetSþ DMþ 57.7%* 71.1%* 50.8%* Notes: Analysis in Model 1 controlled for age; Model 2 controlled for age, gender, education, and Time 3 Age interaction; Model 3 controlled for Model 2 covariates plus incident myocardial infarction, congestive heart failure, intermittent claudication, stroke, Center for Epidemiologic Studies Depression Scale score, and arthritis of hip and knee. *p,.001. IADL ¼ instrumental activities of daily living; MetS ¼ the metabolic syndrome; GEE ¼ generalized estimating equations; DM ¼ type 2 diabetes except when referring to group with no MetS, when type of diabetes is not clear; Ref ¼ reference group. Table 4. Percent Change in the Rate of Increase (Worsening) in Mobility/Strength Score Associated With MetS Groups (Compared to Reference Group) From Regression Models Using GEE After Multiple Imputation Procedure for Missing Values Group Model 1 Model 2 Model 3 MetS DM Ref Ref Ref MetSþ DM 19.2%* 8.0%* 8.0%* MetS DMþ 45.2%* 56.5%* 43.0%* MetSþ DMþ 56.4%* 48.2%* 36.5%* Notes: Analysis in Model 1 controlled for age; Model 2 controlled for age, gender, education, and Time 3 Age interaction; Model 3 controlled for Model 2 covariates plus incident myocardial infarction, congestive heart failure, intermittent claudication, stroke, Center for Epidemiologic Studies Depression Scale score, and arthritis of hip and knee. *p,.001. MetS ¼ the metabolic syndrome; GEE ¼ generalized estimating equations; DM ¼ type 2 diabetes except when referring to group with no MetS, when type of diabetes is not clear; Ref ¼ reference group. prevalence of hypertension. However, the data are also consistent with the hypothesis that glycemic level may be related to disability (19), potentially through microvascular complications such as visual function and peripheral neuropathy, which are unmeasured in our study. Future research using detailed metabolic classification will be needed to sort out the relative contributions of insulin resistance versus hyperglycemia to disability. Our study has several limitations. We have no measures of hemoglobin A1c, body composition (other than height and weight), or activity levels. Such measures would have allowed better evaluation of metabolic status and the relationship of important risk factors for MetS to disability. Similarly, there were missing data due to nonresponse and loss to follow-up that were imputed through multiple imputation methodologies. Although imputed data increase variability of the estimates, they produce less biased estimates than does a complete case analysis when missing data are related to the reasons for being missing, as was the case in our data (29). Despite these limitations, we believe that our research has produced new information about the progression of physical limitations and disability in a growing population group, older Latinos, who have high prevalences of MetS and DM. Disability is a key outcome of DM, and the pathways through which it develops are multifactorial (18) and may include obesity, atherosclerotic complications, neuropathy, microvascular complications, muscle dysfunction, and hyperglycemia itself. This research deepens our understanding of disability in diabetes in two ways. First, it shows that MetS and insulin resistance may not need to be present for progressive disability to exist in diabetes. This finding is consistent with other evidence of pathways to diabetesrelated disability other than atherosclerosis (17 19). Second, it demonstrates that MetS is associated with mobility/ strength limitations. Pathways could include muscle abnormalities associated with insulin resistance (40) and atherosclerotic changes related to peripheral vascular disease, obesity, and inflammation (41). Mobility impairment could potentially compound a behavioral tendency toward low

7 772 BLAUM ET AL. activity levels in some people with MetS, thereby increasing risks for DM, worsening atherosclerotic disease and causing progressive mobility/strength impairment and eventual widespread disability. This research reinforces the importance of preventing progression of MetSþDM to MetSþ DMþ in older Latinos. Although MetS is associated with mobility/strength limitations, the association of these limitations with DM is much stronger; DM is also associated with ADL and IADL disability. Therefore it may be doubly important to maintain mobility and strength in older Latinos with MetS, even in the absence of DM. Self-management education and public health campaigns may be insufficient to accomplish this; specific exercise and compliance interventions may be needed. ACKNOWLEDGMENTS This work was supported by a National Institute on Aging (NIA) grant (AG 12975) and by National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) grant Dr. Blaum was supported by a Hartford Foundation pilot grant, and NIA grant (AG021493) and by the Ann Arbor VA-GRECC. CORRESPONDENCE Address correspondence to: Caroline S. Blaum, MD, MS, Associate Professor, The University of Michigan Medical School, 914 NIB, 300 North Ingalls St., Ann Arbor, MI cblaum@umich.edu REFERENCES 1. 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: Lawlor DA, Ebrahim S, Davey Smith G. The metabolic syndrome and coronary heart disease in older women: findings from the British Women s Heart and Health Study. Diabet Med. 2004;21: Centers for Disease Control and Prevention (CDC). 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