Terry Son Mercer University PharmD Candidate October 21, 2011 Metabolic Syndrome and Physical Performance in Elderly Men: The Osteoporotic Fractures in Men Study Everson-Rose SA, Paudel M, Taylor BC, et al. The American Geriatrics Society 2011; 59:1376-1384 Authors had no financial or any other kind of personal conflicts with this publication Terry Son Mercer University PharmD Candidate October 21, 2011

Background 2: Background MetS clustering of cardiovascular risk factors including central adiposity, altered glucose and insulin metabolism, hypertension, and dyslipedemia. Increases risk for stroke, cardiovascular diseas, DM, and mortality http://www.life-enhancement.com/article_template.asp?id=1948

Metabolic Syndrome (MetS) Background Metabolic Syndrome (MetS) Age-adjusted prevalence of MetS is nearly 24% in the United States and increases with age Adults age 60 or older, the prevalence exceeds 40% Increases risk for stroke, cardiovascular diseases, DM, and mortality Is related to cognitive decline Slide 2: increases risk fo http://minuqol.com/images/metabolic-syndrome.gif

Background Metabolic Syndrome (defined in study): Glucose dysregulation or insulin resistance Impaired fasting glucose (IFG) 100 - < 126 mg/dl Diabetes mellitus Fasting glucose ≥ 126 mg/dl History of diabetes or use of hypoglycemic medications at baseline, or hyperinsulinemia

Background Metabolic Syndrome (defined in study) continued: Two of the 4 characteristics SBP ≥ 140 mmHg or drug treatment for HTN HDL-C < 35 mg/dl Triglyceride ≥ 150 mg/dl BMI ≥ 30 kg/m²

Objective To examine the association between metabolic syndrome (MetS) and objective measures of physical performance

Design Cross-sectional analysis of cohort study, The Osteoporotic Fractures in Men Study March 2000 to April 2002

Setting/Patients Six clinical sites in the United States Ambulatory men 65 yo and older 5995 enrolled; 5,457 analyzed

Inclusion/Exclusion Inclusion: Exclusion: ≥ 65 yo w/o bilateral hip replacement Able to walk w/o assistance of another person Healthy aging and fracture risk Exclusion: Not specified

Intervention Association between metabolic syndrome (MetS) and physical performance was evaluated in 3 ways: Performance scores were examined in relation to individual MetS components Performance examined according to number of MetS components a person had Performance for men with and w/o MetS was evaluated based on WHO criteria

Intervention Physical Performance assessed upper and lower body strength, gait speed, and balance Grip strength Narrow walk speed Walking speed Time to complete five repeated chair stands Physical performance measured at baseline

Intervention Individual scores were converted to quintiles Worst = 1 Best = 5 Unable to compete = 0 Scores were summed for all overall score Mean 11.6 ± 4.3, range 1-20

Outcomes Primary Analyses: Evaluate the individual MetS components in relation to physical performance Evaluate overall performance scores for men with and without MetS (according to WHO criteria)

Outcomes Secondary Analyses: Evaluate the individual physical performance measures Grip strength Narrow walk speed Walking speed Repeated chair stands

Statistics Descriptive statistics t-test for continuous variables Chi-square tests for categorical variables Linear Regression models Model 1 (minimally adjusted model) Included covariates for age, race, education, clinic site Model 2: (multivariable-adjusted model) Included additional covariates for smoking status, alcohol consumption, physical activity, history of falls or fractures, self-rated health , and # of chronic medical conditions. Descriptive statistics were computed to compare men with and without MetS on baseline characteristics Linear regression to assess the association between metsS and physical performance.

Statistics t-test Used for 2 independent samples Men with and w/o MetS Contained continuous data Can take on any value within a finite or infinite interval Can be counted, ordered, and measured Examples: SBP, BMI, physical activity scale, and age Example: men with

Results Participant Characteristics * Component Glucose dysregulation or insulin resistance * Obese HTN or Using Anti-HTN Medications Low HDL-C High Triglycerides N 3,262 1,187 2,458 733 1,992 % tage 60 22 45 13 36.5 * Subcomponent DM Hyperinsulinemia IFG N 840 1,143 1,279

Results Participant Characteristics # of MetS Components 3 or more 2 1 N 1,495 1,447 1,614 901 1,437 (26.3%) participants met WHO criteria for MetS IFG, DM, hyperinsulinemia, and At least 2 of 4 characteristics (HTN, low HDL-C, obese, low triglycerides)

Baseline Demographics Slide 16: baseline demographics Men with and without MetS differ significantly on all characteristics except race or ethnicity and history of falls and fractures 11% minority

Results SBP or HTN is not associated with physical performance Low HDL-C is not significantly associated with physical performance after adjustment for multiple variables

Results Figure 1: Mean Physical Performance score according to number of MetS components P = < 0.001 Results adjusted using multivariable model The greater # of MetS components, the lower the physical performance score Results when minimally adjusted had similar trend across component categories (P< 0.001)

Results Participants without MetS did statistically better on physical performance measures whether adjusted minimally or multivariablely

Results Physical performance was affected in participants with MetS on: Narrow walk speed Walking speed Repeated chair stands Whether or not the participants have MetS, grip strength performance was not significantly affected

Authors’ Conclusion Metabolic dysregulation is related to objectively assessed poorer physical performance in relatively healthy older men Participants with MetS had significantly worse performance of objective indicators on physical function than their peers without MetS

Commentary Strengths Physical performances were assessed objectively Well-characterized cohort of community-dwelling, older men Performance-based measures served as more valid measures than self-reported measures

Commentary Limitations May not be generalized to men from other demographics WHO criteria were adapted to define MetS because data on DBP or microalbuminuria were lacking, and BMI was used instead of waist circumference Did not address mechanism by which MetS contributes to poorer performance Data were cross-sectional only and did not address the temporal association

Metabolic syndrome http://kardiol.com/wp-content/uploads/2011/01/metabolic-syndrome-2.jpg