Epidemic levels of physical inactivity and obesity have stimulated interest in developing efficient means of identifying people at risk of cardiovascular disease. Metabolic syndrome (MetS) is one such construct that is increasingly being recognized for its predictive ability in distinguishing individuals who are at high risk of future vascular events.1 Variously referred to as insulin-resistance syndrome, syndrome X, or dysmetabolic syndrome, MetS is a constellation of metabolic abnormalities that interact to accelerate the progression of atherosclerosis and increase the risk of developing cardiovascular or cerebrovascular disease.2,3 Although consensus is lacking with regard to the absolute constituents of MetS, common components include obesity, insulin resistance, hypertension, and hypertriglyceridemia.4 The unique combination of these clinical manifestations puts people at greater risk of future morbidity than would be expected from the combined risk of the individual components. For example, compared with people without MetS, individuals with MetS have a twofold or more increase in the risk of stroke,5 coronary heart disease (CHD),6 and myocardial infarction.5 Moreover, men with MetS are between two and four times more likely to die of cardiovascular disease.7 Population statistics indicate that the overall prevalence of MetS in most countries is between 20% and 30%.8 Prevalence increases with age9; ∼42% of Americans older than 60 years have been reported to have MetS.10
Most individuals poststroke have atherosclerotic lesions throughout their vascular system, which is not surprising because ischemic stroke and CHD share many of the same predisposing risk factors.11 In fact, as many as 75% of people post-stroke also have heart disease12 and 20%-25% of persons who have had a stroke will have a second stroke or another cardiovascular incident in the ensuing three years.13,14 Clearly, vascular risk assessment should be of concern in the clinical management of people post-stroke.
It is conceivable that, for the stroke population, gains in cardiorespiratory fitness achieved through aerobic training15–18 might confer protection against further vascular events. Goldberg and Berger19 maintained that prevention of stroke recurrence is a critical, yet underaddressed, goal of stroke rehabilitation. In support of the notion that the role of the physical therapist in secondary prevention has not been fully realized, two studies have found that contemporary physical therapy for people post-stroke is of insufficient intensity to induce a cardiorespiratory training effect.20,21
An important first step in implementing effective intervention strategies is to identify individuals at greatest risk of further morbidity.22 Currently, vascular risk assessment in stroke rehabilitation is lacking. Given the high incidence of cardiovascular disease in the stroke population, it could be argued that the majority of people in stroke rehabilitation are at risk of further morbidity, rendering risk assessment unnecessary. However, not all people with a history of cardiac disease are at equal risk, and people without a history of heart disease are also at risk. Thus, identifying relative risk is important for judicious allocation of limited healthcare resources. Given that MetS has been found to be predictive of stroke recurrence,1,23 MetS might be useful in stratifying risk of the prescription and monitoring of appropriate preemptive interventions.
The prevalence of MetS among the general stroke population has been studied previously,5,24,25 but the prevalence in the “middle band” of individuals with moderate functional limitations who participate in stroke rehabilitation26 has not been investigated. Also, the concept of MetS is useful only in health conditions that have a constellation of MetS components; the degree of clustering of interrelating components has not been examined in the stroke population. Therefore, the study was undertaken as an initial step in determining the utility of the MetS construct for cardiovascular risk stratification in stroke rehabilitation. Specifically, we set out to document the prevalence of MetS and its components in patients at the initiation of stroke rehabilitation. We also examined the extent of clustering or interrelatedness of components of MetS in this population. Our hypotheses were that (1) MetS would be more prevalent in people undergoing stroke rehabilitation than in the general population and (2) components of MetS would cluster in this population.
Approval was received from the Capital District Health Authority Research Ethics Board to conduct a retrospective review of the health records of patients who had participated in inpatient stroke rehabilitation between 2002 and 2005 at an adult physical rehabilitation center. This time frame was chosen because the criteria for admission into the center were stable during this period. A staff member not involved in the study used a random number generator to select 50 records per year from the center’s stroke registry. Nineteen records were excluded because of incomplete admission assessments (because of unexpected discharge or emergency readmission to the acute care site) and replaced with randomly selected records from the corresponding years. Two hundred of 362 records from the four-year period were reviewed. Two trained research assistants (an experienced physical therapist enrolled in graduate school and an occupational therapy student) extracted data from each chart pertaining to the admission assessment. In the event of lack of agreement regarding the data recorded, consensus was obtained by discussing the disagreement with the principal investigator.
Data regarding the patients’ demographic and clinical characteristics included age, sex, smoking history, type of stroke (ischemic vs hemorrhagic, based on radiological reports), total score of 126 on the Functional Independence Measure (FIM),27 number of comorbidities, number of prescription medications, lipid-altering and antihypertensive medications, and history of CHD (as indicated by myocardial infarction by history or electrocardiogram, angina pectoris, and coronary reperfusion procedures28). Other variables that have been reported previously to be associated with MetS, including race,9 muscle strength,29 grip strength,30 peak oxygen consumption,31,32 mobility,33 and activities of daily living,34 were not recorded because of lack of consistent reporting in the health records.
For the purpose of this study, the MetS components were based mainly on the National Cholesterol Education Program-Adult Treatment Panel III.4 However, because waist circumference was not consistently documented in the health records, body mass index (BMI) was used as a substitute criterion, in keeping with previous studies.2,7,35 On the basis of the approach used by Gorter et al,36 individuals taking antihypertensive medications were considered to have fulfilled the criteria for hypertension and those with diabetes mellitus (DM) to have fulfilled the criteria for insulin resistance, defined as impaired fasting glucose. However, the use of a lipid-altering medication was not included as a criterion for hypertriglyceridemia or low high-density lipoprotein cholesterol (HDL-C) because of the variable effects of these drugs on triglycerides and HDL-C. Thus, patients having three or more of the following abnormalities were defined as having MetS:
- Obesity: BMI of ≥30 kg/m2, calculated as weight in kilograms divided by the square of height in meters.
- Hypertension: systolic blood pressure (SBP) ≥130 mm Hg or diastolic blood pressure (DBP) ≥85 mm Hg or use of antihypertensive medications.
- Hypertriglyceridemia: serum triglycerides >1.69 mmol/L.
- Low HDL-C: serum HDL-C <1.04 mmol/L in men and <1.3 mmol/L in women.
- Insulin resistance: fasting serum glucose of ≥6.1 mmol/L or diagnosis of DM.
All statistical analyses were performed with SPSS 11.0.1 (SPSS Inc., Chicago, IL). Normality of data distribution was determined using the standard errors of kurtosis and skewness. Descriptive analyses were conducted of the demographic and clinical characteristics with nominal data expressed as frequencies and interval data as means and standard deviations for normally distributed variables, and medians with interquartile ranges for variables not normally distributed. Comparisons of patients’ characteristics and the prevalence of the individual MetS components between the subgroups with and without MetS were done using the Pearson χ2 test and Student t tests for independent samples, as appropriate. Results with P values <0.05 were considered statistically significant.
To explore the extent of clustering of MetS components, factor analysis was applied, according to the approach used by Lempiäinen et al37 in investigating the interrelatedness of insulin-resistance syndrome components in CHD. This method allows inclusion of intercorrelating variables and involves principal component analysis to assess the strength of association among these variables. Independent variables included age, number of comorbidities, history of CHD, smoking habits, FIM score, together with the components of MetS. Mean arterial pressure was used for blood pressure and the ratio of triglycerides to HDL-C for the dyslipidemia component, as recommended by Pladevall et al.38 Plasma glucose was logarithmically transformed because of the skewed distribution of nontransformed data. The initial variables were transformed using orthogonal (varimax) rotation to derive a smaller number of unmeasured (latent) variables or factors.39 The correlation (loading) found between a factor and the original independent variables quantified the amount of variability in the measured variable that can be explained by the underlying factor.39 Factors with eigenvalues of 1.00 were retained in the final analysis, and factor loadings of >0.40 (P < 0.05) were considered indicative of a meaningful relationship.39
As indicated in Table 1, 121 (60.5%) patients (65.5% men and 54.4% women) satisfied the diagnostic criteria for MetS (ie, at least three of the following: obesity, hypertension, hypertriglyceridemia, low HDL-C, and insulin resistance). No significant differences between the subgroups with and without MetS were found for age, sex, smoking history, or FIM score. Demographic and clinical characteristics with higher frequency in the subgroup with MetS included diagnosis of ischemic stroke (as opposed to hemorrhagic stroke), prescription of antihypertensive and lipid-altering medication, and history of CHD. In addition, the subgroup with MetS had a higher number of comorbidities and used more prescription drugs. The greater severity of metabolic abnormalities in the MetS subgroup was reflected in the absolute values of BMI, HDL-C, and triglycerides, whereas SBP and DBPs were controlled to the same extent in the two subgroups. The odds of having DM were almost four times greater for those who had MetS than for those without MetS [ie, odds ratio of 3.9; 95% confidence interval (CI), 2.6-8.3].
The prevalence of the individual components of MetS and the number of the MetS diagnostic criteria met are presented in Table 2. The most frequently observed component was hypertension or the use of antihypertensive medication, and obesity was the least prevalent component. At least one MetS component was present in 193 patients (97%); four or five components were found in 55 patients (28%).
Principal component factor analysis revealed significant loadings (>0.40) on the second factor for BMI, mean arterial pressure, triglycerides to HDL-C ratio, and fasting serum glucose, indicating clustering of core components of MetS under one factor (Table 3). However, some of the MetS components also loaded on other factors, which was not unexpected given that this type of analysis assesses relative rather than absolute association among variables. In fact, fasting serum glucose loaded highest on the third factor. The significant loadings on first factor (age, smoking history, number of comorbidities, and history of CHD) represented cardiovascular involvement. The third factor, with significant loading of smoking history, FIM score, and fasting serum glucose, and the fourth factor, with significant loading of history of CHD, BMI, and triglycerides-to-HDL-C ratio, were thought to reflect combinations of lifestyle factors, impaired glucose tolerance, and dyslipidemia. Altogether, the four factors accounted for 57% of the total variance.
The results of the study supported our first hypothesis that MetS in people undergoing stroke rehabilitation would be more prevalent than in the general population. The prevalence of MetS (61%) in our sample of 200 stroke rehabilitation patients was substantially higher than that of the general population of Americans older than 60 years (∼42%).10 Comparative data for other stroke rehabilitation populations are not available, but prevalence figures of MetS in the general stroke population vary widely. Rates of 20%,25 44%,24 and 50%40 have been reported for ischemic stroke; 43% for all forms of cerebrovascular disease;5,36 and 62% for individuals post-stroke with diabetes.41 The vast majority of our sample (97%) had at least one MetS component, which is comparable with the figure of 93% previously reported in a group of individuals with all forms of cerebrovascular disease.36 Further, more than one fourth of our patients had four to five components, consistent with a previous study of individuals with ischemic stroke.24 Importantly, the risk of cardiovascular disease increases with the number of MetS components—more than a fivefold increase in risk has been reported in the presence of four or more components compared with a single component (ie, odds ratio of 5.9; 95% CI, 2.5-13.7).42
Not surprisingly, patients classified as having MetS had more comorbidities, used more prescription medications (including antihypertensive and lipid-altering drugs), and were more likely to have had a history of CHD. Our finding that MetS was observed more frequently in patients with ischemic stroke is consistent with the finding of an odds ratio of 3.1 (95% CI, 1.7-5.6) for atherothrombotic infarction in the presence of MetS.25 Neither age nor current or past smoking habits was a determinant of MetS prevalence, in keeping with the findings of Gorter et al,36 but in contrast to those of Ninomiya et al,5 who found positive effects of both age and current (but not past) smoking habit on MetS prevalence in their stroke cohort. Given previous indications of differences in prevalence of MetS in men and women,37,38 our findings of a lack of a significant sex effect are difficult to explain. Ninomiya et al5 reported a significant association between MetS and sex in patients after myocardial infarction but not in patients post-stroke, suggesting that the sex difference typically associated with MetS may not be manifest in the stroke population.
Blazer et al33 reported that the presence of MetS was an independent and highly significant predictor of decline in mobility of older, community-based adults. The investigators postulated that the related functional decline might be attributed to factors known to be associated with MetS such as vascular morbidity, muscular weakness,29,30 and low cardiorespiratory fitness levels.31,32 In this study, any effects of MetS components on mobility of the patients were probably overshadowed by the direct effects of the stroke, hence the lack of association between MetS and FIM scores.
The finding that hypertension (or use of antihypertensive medications) was the most prevalent MetS component in both subgroups was not unexpected because ∼50% of strokes are attributable to elevated blood pressure.43 Previous studies also found that hypertension and low HDL-C were the most prevalent MetS components and obesity the least prevalent in individuals with cardiac disease and intracranial stenosis.36,44 In contrast, Ninomiya et al5 found that hypertension and hypertriglyceridemia were the most prevalent and insulin resistance was the least prevalent in the general stroke population. Variability in the study populations and application of different diagnostic criteria for MetS could explain these differences.
In support of our second hypothesis that components of MetS would cluster in patients undergoing stroke rehabilitation, factor analysis revealed that the components clustered mainly on a single factor. This finding reaffirms previous reports of the validity of MetS as a distinct subgroup of signs or symptoms forming a characteristic clinical entity.37,38 Interrelatedness of the components has important therapeutic implications. MetS is associated with vascular risk that is not accounted for entirely by the individual component conditions.45 Furthermore, the rate of hospital readmission in the first six months post-stroke has been reported to double if the patient has MetS.46 Thus, early screening for MetS among individuals participating in stroke rehabilitation could be helpful in determining judicious implementation of interventions aimed at reducing future vascular events. For example, although aggressive therapies, including multiple drugs, would be indicated for individuals who meet the criteria for MetS (three to five components), a more preventive approach would be warranted for those who do not have MetS. Implementation of a targeted educational program at the individual level regarding lifestyle changes (ie, physical activity, weight loss, medication adherence, smoking cessation, stress management) should be introduced before the metabolic disturbances become chronic and increasingly recalcitrant to conservative, nonpharmacological strategies. In addition, prescription of aerobic exercise should be considered, given that low-exercise capacity is common in individuals participating in stroke rehabilitation47 and is associated with increased clustering of the metabolic abnormalities associated with MetS.48–52 Indeed, aerobic training, particularly of moderate intensity,53 has been shown to modify all components of MetS.54,55 With regard to the most prevalent MetS component in our cohort—hypertension—an extensive meta-analysis concluded that regular aerobic exercise leads to significant SBP and DBP reductions (−3.8 mm Hg [95% CI, −5.0 to −2.7 mm Hg] and −2.6 mm Hg [95% CI, −3.4 to −1.8], respectively).56
These results must be interpreted in light of the study limitations. First, our analysis was limited to retrospective data collected at the initiation of stroke rehabilitation. Our initial plan to compare admission and discharge data could not be realized because of lack of consistent reporting at discharge. Further, not all variables that might have related to MetS were standardized entries in the health records. Second, the data may not be generalizable because the sample was from a single rehabilitation center located in a region of predominantly Scottish ancestry with a very high prevalence of cardiovascular disease. Additionally, MetS can be diagnosed by several definitions, making it difficult to compare findings across studies. For example, the International Diabetes Federation definition of MetS includes increased waist circumference because abdominal adiposity is the body fat parameter most closely associated with MetS.57 Our use of BMI, rather than waist circumference, was supported by a previous finding that the substitution of BMI for waist circumference did not affect the robustness of MetS criteria.2 Also, the prevalence of hypertriglyceridemia and low HDL-C may have been underestimated because lipid-altering medication was not included as a criterion for either of these MetS components. Finally, although the ability of MetS to predict future cardiovascular events is not disputed, some have questioned whether MetS as a single entity is a better predictor than its individual components.58,59 Given these limitations, it will be important to perform prospective, longitudinal studies to extend our findings by relating the presence of MetS to outcomes of stroke rehabilitation.
Our findings of a high prevalence of MetS, together with significant clustering of its components, support the application of the MetS as a clinical entity for vascular risk stratification and treatment planning in stroke rehabilitation. The disturbed metabolic profile of the cohort under study underlines the need for greater emphasis on targeted interventions to reduce the risk of further vascular morbidity. A prospective study using the MetS as a risk assessment tool for secondary prevention would be a next logical step in evaluating its utility for cardiovascular risk stratification in stroke rehabilitation.
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