1. The short term effects of metabolic syndrome and its components on all-cause-cause mortality-the Taipei Elderly Health Examination Cohort Wen-Liang Liu Taipei City Hospital, Taipei, Taiwan

2. Background Kylin 1923, multiple risk factors related to DM and hypertension Syndrome X, Insulin resistance syndrome, Insulin resistance syndrome Risk factors such as hypertension, dyslipidemia, obesity, and insulin resistance have been extensively studied in young adults Reverse metabolic syndrome – The significance of these risk factors in the very old remains a subject of debate Survival benefit of metabolic syndrome MS: a time-dependent variable

3. Selective studies reported the assocaition between metabolic sybdrome and all- cause mortality Author Year PublishedCountryNMean age Follow-up PeriodHRRemark Pavaglia2006Italy98174.5(45-97)41.51(MI) Vischer2009France33195.820.57Reverse MetS Chiang2012Taiwan68082.530.68(0.40-1.15)Survival benefit Maralani2012Australia3,086 65.9( ≧ 49) 100.96(0.69-1.34) 1.06(0.84-1.32) 1.23(1.01-1.51) Time-dependent association Bulter2006USA3,03573.660.61(N.S.) Thomas GN 2007Hong Kong 2,83625-748.452.02(1.02-4.00) Tsai SP2008USA35,25 9 ≧ 40 152.03(1.80-2.30) Wen CJ2008Taiwan10,54 7 >6581.48(1.16-1.90) Sun DL2012China1,53560.5151.47(1.20-1.80) Luksiene2012Lithuania2,45635-6491.98(1.16-3.38)

4. Implications from those studies Reverse metabolic syndrome – The significance of these risk factors in the very old remains unclear Survival benefit of MS in the elderly was observed in a short term period (<=4 years) Those studies involved a small sample size

5. Hypothesis The short term effect of MetS on all-cause mortality might be associated with a low risk of mortality The individual components of MetS might have different impacts on all-cause mortality and might modify the association

6. Purposes of the study To examine the impact of metabolic syndrome itself on all-cause mortality in the elderly population To explore the effects of individual components of MetS on all-cause mortality with a large sample size To evaluate the influence of individual components on the association between MetS and mortality

7. Methods Design: prospective study Study subjects: participants of the Taipei City Free Health Examination for the Elderly in 2007 40,686 elderly persons agreed to participate in the study and be followed up until December 31m2010 A structured questionnaire was designed to collect participants’ demographic, disease history, lifestyle factors Fasting blood sample were measured by an automated analyzer and to evaluate the blood biochemical indicators

8. Metabolic syndrome definition The National Cholesterol Education Program (NECP) Adult Treatment Panel III Guideline and modified by International Diabetes of Federation for Chinese Specially Metabolic syndrome: having any three of the following risk factors – Fasting glucose level >=100 mg/dL – Serum triglyceride level>=150 mg/dL – HDL-C level <40 mg/dL for male and <50 mg/dL for female – Systolic blood pressure >=130 mmHg or diastolic pressure>=85 mg/dL – Waist circumference >=90 for male and >=80 for female

9. Outcome variables All-cause mortality and CVD mortality Death records from National Mortality Registry – ICD9 for cause of death – Date of death – Basic information

10. Statistical analysis Continuous variable expressed as mean and standard deviation (Mean ±SD) Comparisons between continuous variables were performed by Student’s t-test Chi square test was used to evaluate the association between variables Cox proportional hazard model was used to evaluate the impact of MetS and its components on all-cause mortality All analysis were performed using SAS 9.3

11. Results 40,686 elderly persons participated in this study 15,775 (38.8%) persons were defined as having MetS 2,414 people died from all-cause within a mean follw-up period of 3.3 years Among those deceased, 526 (21.5%) were attributed to cardiovascular disease

12. Table 1: Baseline characteristic of study population Variables Overall cohort (N=40668) Age(yrs)74.91±6.34 Body mass index (Kg/M 2 )24.16±3.20 Height (cm)158.81±8.23 Weight (Kg)61.02±9.91 Waist circumference (cm)85.26±9.38 Systolic blood pressure (mmHg)135.67±18.80 Diastolic blood pressure (mmHg)75.41±11.10 Fasting blood sugar (mg/dL)104.63±22.67 Serum HDL-C (mg/dL)52.60±13.41 Serum total cholesterol (mg/dL)195.47±34.03 Serum triglyceride (mg/dL)121.54±62.50 Mean observation period (yrs)3.30±0.42

13. Table 1: Baseline characteristic of study population Variables% Gender (male %)53.62 Hypertension (5)42.24 Diabetes mellitus (%)11.80 Smoking (%)7.49 Alcohol drinking (%)19.28 Exercise (%)61.27 Medication use (%) Anti-hypertensive (%)42.66 Anti-diabetic agents (%)12.26 Lipid-lowering drugs (%)6.45 Metabolic syndrome (%)38.79 Central obesity (%)50.78 High plasma glucose (%)47.49 High blood pressure (%)63.13 High serum triglyceride (%)25.37 Low HDL-C (%)30.42 All-cause mortality (%)5.27 Cancer (%)0.58 Cardiovascular disease0.42

14. Table 2: Characteristics of the study cohort by metabolic syndrome status at baseline MetS(-) (N=24893) MetS(+) (N=15775) t-test p-value Age(yr)73.83±6.4275.03±6.220.0018 Body mass index(kg/m 2 )23.15±2.9425.75±2.95<0.0001 Height(cm)158.30±8.13158.10±8.34<0.0001 Weight(kg)58.84±9.4364.46±9.68<0.0001 Waist circumference(cm)82.28±8.8989.96±8.12<0.0001 Systolic blood pressure(mg/dl)131.50±18.61142.2±17.17<0.0001 Diastolic blood pressure(mg/dl)73.71±10.7978.10±10.96<0.0001 Fasting plasma glucose(mg/dl)98.18±16.40114.80±27.01<0.0001 Serum HDL-C(mg/dl)56.77±13.1746.02±310.93<0.0001 Serum total cholesterol(mg/dl)195.30±33.38195.80±35.05<0.0001 Serum Triglyceride(mg/dl)97.13±42.61160.10±69.65<0.0001

15. Table 2: Characteristics of the study cohort by metabolic syndrome status at baseline Mortality(-) N=38524 Mortality(+) N=2144 x 2 -test p-value Sex (male %)58.3946.09<0.0001 Hypertension (%)32.9156.99<0.0001 Diabetes mellitus (%)5.5121.72<0.0001 Smoking (%)7.816.98<0.0001 Alcohol drinking (%)20.5917.21<0.0001 Exercise (%)64.1456.76<0.0001 Medication use (%)<0.0001 Anti-hypertensive (%)35.3454.22<0.0001 Anti-diabetic agents (%)7.2520.16<0.0001 Lipid-lowering drugs (%)5.228.38<0.0001 Metabolic syndrome (%)<0.0001 Central obesity (%)30.6682.52<0.0001 High blood pressure (%)50.3383.00<0.0001 High plasma glucose (%)29.2776.23<0.0001 High serum triglyceride (%)7.8553.00<0.0001 Low HDL-C (%)12.1259.31<0.0001 All-cause mortality (%)5.544.85<0.0001 Cancer (%)0.660.460.0088 Cardiovascular disease (%)0.460.340.676

16. Table 3. Comparisons of cardio-metabolic characteristics between study subjects who died or survived in the follow-up period (2007-2010) Mortality (-) N=38524 Mortality (+) N=38524 t-test p-value Age (yrs)74.62±6.1880.03±6.98<0.0001 Body mass index24.22±3.1723.00±3.53<0.0001 Height (cm)158.80±8.22159.50±8.40<0.0001 Weight (Kg)61.14±9.8558.67±10.58<0.0001 Waist circumference (cm)85.28±9.3484.94±10.050.1298 Systolic blood pressure (mmHg)135.70±18.70135.70±20.530.8879 Diastolic blood pressure (mmHg)75.50±11.0073.72±12.04<0.0001 Fasting blood sugar (mg/dL)104.60±22.44105.2±26.600.2994 Serum HDL-C (mg/dL)52.75±13.3849.95±13.64<0.0001 Serum total cholesterol (mg/dL)196.10±33.90183.70±35.89<0.0001 Serum triglyceride (mg/dL)122.00±62.63113.00±59.46<0.0001

17. Table 3. Comparisons of cardio-metabolic characteristics between study subjects who died or survived in the follow-up period (2007-2010) Variables Mortality (-) N=38524 Mortality (+) N=38524 Chi suare p-value Gender (male %)52.7469.36<0.0001 Hypertension (5)42.1643.670.1715 Diabetes mellitus (%)11.7013.570.0088 Smoking (%)7.2711.48<0.0001 Alcohol drinking (%)19.5714.06<0.0001 Exercise (%)61.9948.34<0.0001 Medication use (%) Anti-hypertensive (%)42.5444.870.0336 Anti-diabetic agents (%)11.9617.68<0.0001 Lipid-lowering drugs (%)6.525.180.0139 Metabolic syndrome (%)38.9635.680.0024 Central obesity (%)51.1244.68<0.0001 High plasma glucose (%)63.1562.640.6319 High blood pressure (%)47.4847.620.9000 High serum triglyceride (%)25.6420.48<0.0001 Low HDL-C (%)30.1335.68<0.0001

18. Table 4: Association between and all-cause mortality- modified by single component of MetS HR95% CI of HR Unadjusted model MetS0.8690.7940.952 Central obesity0.7730.7080.843 Tryglyceride0.7470.6710.921 Low HDL1.2871.1751.409 Hypertension0.9780.8941.073 Fasting blood sugar1.0060.9221.097 Single components added into the model (HR for MetS) HR95% CI of HR Central obesity0.9800.8841.087 Tryglyceride0.9930.8941.104 Low HDL0.6990.6280.777 Hypertension0.8620.7830.940 Fasting blood sugar0.8350.7550.924

19. Table 5: Risk factors for all-cause mortality-Cox regression model LevelHR 95% C.I. of HR P-value Metabolic syndromeYes vs No0.880.761.010.0736 SexMale1.521.371.69<0.0001 Age(yr)1.11 1.12<0.0001 High serum triglyceride(mg/dL) ≧ 150 0.850.740.960.0104 High serum total cholesterol (mg/dL) ≧ 200 0.790.710.87 <0.0001 Diabetes Mellitus(mg/dL)>1261.311.141.49<0.0001 Hypertension(mmHg)140/901.040.951.150.3645 Central obesity(cm)>80(female),>90(male)0.800.720.89<0.0001 SmokeYes vs. No1.661.431.91<0.0001 Alcohol drinking Often vs. none0.880.661.170.3917 Occasionally vs none0.610.530.70<0.0001 Exercise Often vs non- /occasionally 0.600.550.66<0.0001

20. Table 6: Risk factors for CVD mortality -Cox regression model LevelHR95% C.I. of HRP-value Metabolic syndromeYes vs No0.830.611.120.2198 SexMale1.311.061.630.0141 Age(yr)1.121.101.14<0.0001 High serum triglyceride(mg/dL) ≧ 150 0.930.711.210.5901 High serum total cholesterol (mg/dL) ≧ 200 0.700.570.870.0014 Diabetes Mellitus (mg/dL)>1261.020.751.380.3500 Hypertension (mmHg)140/901.401.151.690.0007 Central obesity (cm) >80(female), >90(male) 0.760.610.950.0159 Low HDL-C (mg/dL) <50(female)/ <40(male) 1.381.091.750.0081 SmokeYes vs. No1.120.781.600.5472 Alcohol drinking Often vs. none0.440.181.060.0666 Occasionally vs none0.630.460.850.0023 Exercise Often vs. non- /occasionally 0.580.480.71<0.0001

21. Conclusions MetS had a survival benefit in the elderly in this four year follow-up study Its survival effects mainly explained by higher triglyceride had larger waist circumference and strengthened by controlling for HDL-C High triglyceride level and a larger waist decreased mortality risk, and low-HDL-C had a greater mortality risk

22. Conclusions Weight loss may pose a high mortality risk in older people, and MetS was sensitive to weight change implying that non-MetS subjects might have experienced certain weight loss to a higher mortality The reverse metabolic syndrome proposed by Vischer, featured by low BMI. Low DBP, low total and HDL-C, might be associated with mortality in the elderly people Several epidemiologic studies had reported that lower serum cholesterol, triglyceride and DM increased all- cause mortality; suggesting the potential adverse impact of malnutrition