Agenda CIAHD Monthly Research Meeting SPH Tower 1, Room 4645 February 3, :30 3:00pm. I. Meeting Overview 5 minutes

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1 Agenda CIAHD Monthly Research Meeting SPH Tower 1, Room 4645 February 3, :30 3:00pm I. Meeting Overview 5 minutes II. Project Presentations 2008/2009 Funded Pilot Project: PI Marc Turenne Disparities in Access to Higher Quality Health Care: Access to and Choice of an Initial Renal Dialysis Provider 40 minutes 2007/2008 Funded Pilot Project : PI Amy Schulz Socioeconomic Patterns in the prevalence of Metabolic Syndrome among non-hispanic Black, non-hispanic White, and Latino adults in Detroit, Michigan 40 minutes III. Meeting Wrap-up/Action Items 5 minutes *Light snacks will be provided for UM attendees

2 2/3/2010 Disparities in Access to Higher Quality Health Care: Access to and Choice of an Initial Renal Dialysis Provider Pilot Project CIAHD February 3, 2010 Background End-stage renal disease (ESRD) Cause: usually diabetes or hypertension (71%) Treatment: transplantation (18K/year) or dialysis (355K on 12/31/06; 60K on transplant waiting list) Comorbidity: cardiovascular disease (61%), cerebrovascular disease (20%) Dialysis facility: regular source of care 3 sessions/week for in-center dialysis Regular (e.g., monthly) evaluations for home dialysis Management of anemia, bone disease, and other conditions related to ESRD Medicare coverage Racial and ethnic disparities in ESRD Incidence of ESRD Higher rates in black (3.7x), American Indian/Alaskan Native (1.9x) and Hispanic populations (1.5x) Nephrologist care prior to ESRD May expand ESRD treatment options (treatment modality, type of vascular access, provider) Less pre-esrd care for black and Hispanic vs. white patients Treatment of ESRD Delayed wait listing for a transplant in black and Hispanic populations Black patients less likely to have preferred type of vascular access for dialysis and to achieve the minimum clinical target for the dose of dialysis 1

3 2/3/2010 Research Questions Are there disparities in access to higher quality dialysis care related to: I. Availability and extent of choice of dialysis providers II. Accessibility of higher quality dialysis providers III. Use of information about quality of care in selecting a dialysis provider Measures I. Availability and extent of choice of providers a. Number of dialysis facilities b. Distance to nearest facility II. III. Accessibility of providers with higher quality of care a. % of available facilities with higher vs. lower measured quality b. Distance to nearest facility with higher h vs. lower measured quality Selecting a provider with higher quality of care a. % of patients treated at nearest facility b. % of patients selecting facility with higher vs. lower measured quality c. % of patients who bypass a nearer facility for a more distant facility with relatively higher reported quality of care Study Design Examine possible disparities in patient access to and choice of an initial dialysis provider related to: Patient characteristics Race and ethnicity Insurance coverage Pre-ESRD care Area socioeconomic indicators Payer mix among dialysis patients Per capita income 2

4 2/3/2010 Primary data sources I. ESRD Medical Evidence Form Race, ethnicity Pre-ESRD care by nephrologist Insurance Completed by providers at onset of ESRD II. Standard Information Management System (SIMS) Patient status Treatment modality Dialysis provider III. Dialysis Facility Compare Facility-specific measures of patient survival and clinical outcomes published on CMS website Study Population Individuals who began chronic renal dialysis for the treatment of ESRD in the U.S. during Jan Sept 2006, for at least 90 days Dialysis facility and modality identified on day 90 of treatment to allow for stabilization period Excludes patients who recovered renal function, received a kidney transplant, or died in the first 90 days Other exclusions were made for patients with unknown location of patient residence and/or dialysis facility (4.9%) n = 67,465 patients available for analysis I. Availability and extent of choice of providers 3

5 2/3/2010 What is the relevant provider search area? May vary substantially across patients depending on both measured and unmeasured characteristics Individual patient characteristics, such as: Preference for in-center vs. home dialysis Transportation Social support Employment Population density Examined distances traveled by patients to their current facility Between zip code centroids 140 Distance to dialysis facility Miles n=67,465 0 Total Metro Micro Not in CBSA In-center dialysis Metro Micro Not in CBSA Home dialysis Definition of search areas For each patient, the outer edge of the search area was based on the 75 th percentile of the distance currently traveled to a facility by patients with the same dialysis modality and CBSA status Outer edge of search area, in miles from patient zip code In-center Home CBSA dialysis dialysis Metro Micro Not in CBSA

6 2/3/2010 Number of facilities in search area cilities Fac n=67,465 0 Total Metro Micro No CBSA In-center dialysis Metro Micro No CBSA Home dialysis Availability of facilities by race In-center dialysis, metropolitan areas Facilities in search area Distance to nearest facility Race Patients Mean Median Mean Median Amer. Indian / AK Native Asian 1, Black 16, Pacific Islander White 31, Availability of facilities by race In-center dialysis, not in CBSA Facilities in search area Distance to nearest facility Race Patients Mean Median Mean Median Amer. Indian / AK Native Black 1, White 2,

7 2/3/2010 Availability of facilities by ethnicity In-center dialysis Facilities in search area Distance to nearest facility Area Hispanic Patients Mean Median Mean Median Metro Yes 7, No 43, Not in CBSA Yes No 3, II. Accessibility of providers with higher measured quality of care Adjusted mortality rates by facility (1) Patient mortality: 22%/year at risk Facility Standardized Mortality Ratio (SMR): ratio of observed to expected deaths Adjustments: age, race, ethnicity, sex, diabetes, duration of ESRD, comorbidities and BMI at incidence, population death rates Identification of facilities with higher or lower mortality while accounting for differences in patient population. 6

8 2/3/2010 Adjusted mortality rates by facility (2) Publicly reported measures on CMS website assign facilities to categories based on whether patient survival is: o Better than expected o As expected o Worse than expected Definitions o Better than expected at least 20% lower mortality based on upper bound of 95% confidence interval for facility SMR o Worse than expected at least 20% higher mortality based on lower bound of 95% confidence interval for facility SMR Snapshot of Dialysis Facility Compare (as of Jan 2010) Patient Survival for January 2005 to December 2008* Survival Categories for the 4814 facilities with available data in US Survival Categories for the 151 facilities with available data in Michigan FMC DIALYSIS - WEST ANN ARBOR ST JOSEPH MERCY HOSP DIALYSIS UNIV OF MI DIALYSIS - ADULT UNIV OF MI DIALYSIS CLINICS - ANN ARBOR Better Than Worse Than As Expected Expected** Expected** *The most recent data available. If a facility was not open during this period, information will not be available on this Website. (Contact the facility for the most current information). **Statistically better or worse than the "As Expected" survival category. For more detail about this information, please view the Patient Survival Frequently Asked Questions. Publicly reported patient survival measures for individual dialysis facilities, January 2006* Measure of patient survival Facilities n % Better than expected % As expected 3, % Worse than expected % Total 4, % *Published on the CMS website as part of Dialysis Facility Compare. Excludes facilities with insufficient data available. 7

9 2/3/2010 Proximity to facilities with better vs. worse than expected survival Measure of patient survival at facility Patients with at least 1 facility of this type in their search area^ n Percent Better than expected 8, % Worse than expected 14, % ^Calculated among patients with at least 1 facility in their search area. Sample size by race and ethnicity* Race/ethnicity Patients American Indian / Alaskan Native (AI / AN) 551 Asian 2,096 Black 19,272 Pacific Islander (PI) 508 White 36,877 Hispanic 8,223 Not Hispanic 51,301 *Includes patients with at least 1 facility in their search area. Available facilities with better vs. worse than expected survival, by race ties in search area Percent of facilit 8.0% 7.0% 6.0% 5.0% 4.0% 3.0% 2.0% 1.0% * Facilities with better than expected survival * * * Facilities with worse than expected survival * * 0.0% AI / AN Asian Black PI White AI / AN Asian Black PI White ^Calculated among patients with at least 1 facility in their search area. *p<0.05 vs. white. 8

10 2/3/ % Available facilities with better vs. worse than expected survival, by ethnicity ies in search area 6.0% 5.0% 4.0% * Percent of faciliti 3.0% 2.0% 1.0% * 0.0% Hispanic Not Hispanic Hispanic Not Hispanic ^Calculated among patients with at least 1 facility in their search area. *p<0.05 vs. not Hispanic. Available facilities with better vs. worse than expected survival, by patient insurance Patient insurance at start of ESRD treatment Patients Percent of facilities in search area^ with survival: Better than expected Worse than expected None 4, % 4.1% Medicaid 15, % 4.0%* Medicare 22, % 4.4% Employer 16, % 3.8%* ^Calculated among patients with at least 1 facility in their search area. *p<0.05 vs. not Hispanic. Available facilities with better vs. worse than expected survival, by level of employer coverage in area Employer coverage among new dialysis patients in county Patients Percent of facilities in search area^ with survival: Better than expected Worse than expected Quartile 1 (<20.3%) 14, %* 6.3%* Quartile 2 (20.3% to 26.7%) 14, %* 3.6%* Quartile 3 (26.7% to 33.5%) 15, %* 4.1%* Quartile 4 (>=33.5%) 15, % 3.3% ^Calculated among patients with at least 1 facility in their search area. *p<0.05 vs. quartile 4. 9

11 2/3/2010 Insurance coverage by ethnicity Hispanic Patients % of patients with employer coverage at start of treatment for ESRD % of patients residing in counties with high employer coverage (Q4) Yes 9, % 10.8% No 58, % 28.0% Available facilities with better vs. worse than expected survival, by area employer coverage and patient ethnicity Level of employer coverage in county of patient residence Hispanic Patients Percent of facilities in search area^ with survival: Better than expected Worse than expected High quartile (>=33.5%) Yes % 2.9% 27% 2.7% No 14, % 3.3% Low quartile (<20.3%) Yes 2, %* 10.8%* No 11, % 5.2% ^Calculated among patients with at least 1 facility in their search area. *p<0.05 vs. not Hispanic. III. Selecting a provider with higher measured quality of care 10

12 2/3/2010 Selection of nearest facility* 90% 80% 78% ent of patients Perce 70% 60% 50% 40% 30% 47% 43% 63% 36% 51% 37% 20% 10% 0% Total Metro Micro Not in CBSA In-center dialysis Metro Micro Not in CBSA Home dialysis *There may be other facilities that are equidistant (e.g., in the same zip code as the selected facility). Selection of nearest facility by pre-esrd nephrologist care* Pre-ESRD care by nephrologist Patients % choosing nearest facility Total In-center dialysis Home dialysis None 19, % 46.4% 38.8% <12 months 24, % 49.1% 38.7% At least 12 months 16, % 51.9% 39.6% *There may be other facilities that are equidistant (e.g., in the same zip code as the selected facility). Selection of nearest facility by race and ethnicity* Race/ethnicity Patients % choosing nearest facility Amer. Indian / AK Native % Asian 2, % Black 20, % Pacific Islander % White 43, % Hispanic 9, % Not Hispanic 58, % *There may be other facilities that are equidistant (e.g., in the same zip code as the selected facility). 11

13 2/3/2010 Making inferences about the use of quality information in selecting a facility 14.0% 12.0% Bypassed nearest facility Nearest facility ing facility with rse survival Percent select better/wor 10.0% 8.0% 6.0% 4.0% 2.0% 61% 39% 58% 42% 0.0% Search area includes facility with better than expected survival (n=8,780) Search area includes facility with worse than expected survival (n=14,458) Selection of facilities with better than expected survival, by race % treated at facility with better than expected survival Chosen Race Patients^ Total facility is also the nearest facility Patient bypassed closer facility % of facilities in search area with better than expected survival How many times farther is the nearest facility with better than expected survival? Asian % 8.2% 5.6% 18.0% 2.9 Black 3, % 2.0% 4.9% 9.0% 4.4 White 4, % 3.9% 5.6% 11.5% 3.1 ^Includes patients with a search area that includes at least 1 facility with better than expected survival and at least 1 facility with a different classification (survival is as expected or worse than expected). Selection of facilities with better than expected survival, by ethnicity % treated at facility with better than expected survival Chosen facility is also the nearest est Patient bypassed closer cose Hispanic Patients^ Total facility facility % of facilities in search area with better than expected survival How many times farther is the nearest facility with better than expected survival? Yes 1, % 1.3% 3.9% 7.3% 4.8 No 7, % 4.0% 5.7% 12.0% 3.3 ^Includes patients with a search area that includes at least 1 facility with better than expected survival and at least 1 facility with a different classification (survival is as expected or worse than expected). 12

14 2/3/2010 Selection of facilities with better than expected survival, by pre-esrd nephrologist care % treated at facility with better than expected survival Chosen Care by nephrologist before ESRD Patients^ Total facility is also the nearest facility Patient bypassed closer facility % of facilities in search area with better than expected survival How many times farther is the nearest facility with better than expected survival? None 2, % 2.8% 4.2% 9.5% 4.2 <=12 months 3, % 3.2% 5.5% 11.2% 3.4 >12 months 1, % 5.5% 7.2% 14.3% 2.8 ^Includes patients with a search area that includes at least 1 facility with better than expected survival and at least 1 facility with a different classification (survival is as expected or worse than expected). Summary Availability of providers Limited number of providers available in rural areas and for American Indian/Alaskan Native patients Accessibility of higher quality providers Most consistent disparities observed for Hispanic patients Potential role for community level factors (e.g., payer mix) Selection of higher h quality providers Patients of all races and ethnicities have a relatively high likelihood of being treated at the nearest facility Selection of nearest facility may disadvantage black and Hispanic patients for whom it is less likely to be a higher quality facility Relatively similar tendencies for patients to bypass nearer facilities to be treated at higher quality facilities and lower quality facilities are not consistent with patient use of information about quality in choosing a more distant facility Limitations Primary quality measure (facility SMR) may have limited sensitivity Other available quality measures that reflect intermediate clinical outcomes ( dose of dialysis and anemia management) are publicly reported, but have other limitations Not risk adjusted More difficult to compare facilities Distances calculated between zip code centroids Other factors affecting accessibility of providers not measured (e.g., transportation, excess capacity at facility) Use of information about quality is not directly observed Search area definitions Large variation in population density across metro areas Impact of defining broad vs. narrow search areas should be explored 13

15 2/3/2010 Further research Distinguish role of individual vs. community level factors, such as: Patient level: preference for nearest or most convenient facility, pre-esrd care, insurance, use of information about quality Community level: limited choice of providers in some areas, resources available (e.g., payer mix) in area, residential segregation by race/ethnicity it Policy implications vary depending on source of disparities: Differences in payer mix Legislative proposals to extend MSP period may pose risk at community level Differences in pre-esrd care Initiatives to promote awareness and management of chronic kidney disease before reaching ESRD may reduce disparities 14

16 Characterizing the distribution and correlates of Metabolic Syndrome in a Tri-Ethnic Urban Sample A.J. Schulz, L. Lachance, G. Mentz, J. Johnson, C.A. Stokes, C.B. Gaines Healthy Environments Partnership: Brightmoor Community Center, Detroit Department of Health & Wellness Promotion, Detroit Hispanic Development Corporation, Friends of Parkside, Henry Ford Health System, Rebuilding Communities Incorporated, University of Michigan School of Public Health Why Heart Disease? Leading cause of death in the US, Michigan and Detroit; Deaths from heart disease in 700 the US have 600 declined steadily over the past years, but more 400 for some groups than for others; 300 Racial and 200 socioeconomic 100 disparities remain in heart disease. 0 Rate of Death 1980 Age-Adjusted Heart Disease Death Rates by Race and Sex, Michigan Residents, Year White Male White Female Black Male Black Female Why Heart Disease in Detroit? City of Detroit =418 United States = *Year 2000 heart disease mortality rates /100,000 population. 1

17 R a t e p e r M o r ta lity Mortality and HH income Eastside 97% Black Detroit City Southwest 82% Black ~50% Latino Northwest 70% Black Michigan 14% Black Oakland County 12% Black 0 $0 $10,000 $20,000 $30,000 $40,000 $50,000 $60,000 $70,000 Median Household Income Healthy Environments Partnership Conceptual Model Fundamental factors Intermediate factors Proximate factors Health outcomes Macro Social Factors (e.g., political, legal, economic systems; cultural beliefs) Race-based residential segregation Concentration of poverty and wealth Social environment (e.g., municipal investment, public participation) Physical environment (e.g., PM, age and condition of housing stock, land use) Social relationships Health behaviors (e.g., diet, physical activity) Perceived stressors (e.g., financial, environ) Health risk indicators and health outcomes (e.g. blood lipid levels, high blood pressure, metabolic syndrome) H1: Distribution of MetS and components varies by race/ethnicity* Race Ethnicity Metabolic Syndrome Waist Circumference Blood Pressure HDL Triglycerides Glucose * Gender-specific prevalence, adjusting for age 2

18 H2: Racial/ethnic variation in MetS is attenuated after accounting for socioeconomic status* Income Education Race Ethnicity Metabolic Syndrome Waist Circumference Blood pressure HDL Triglycerides Glucose * Gender specific prevalence, adjusting for age H3: There are differences in social patterning by definition of MetS Most US studies use ATP III definition Some evidence that a greater proportion p meet IDF definition criteria compared to ATP III Does definition used influence evidence of social patterning? Data Healthy Environments Partnership Survey (n=919) Two stage stratified random sample: >40% poverty; <40% poverty >80% Black; <80% Black 1. Random selection of HUs; 2. random selection of respondent age 25+ Self reported health, stress, SEP, neighborhood Anthropometric measures NHANES (n=1114) Metropolitan area (proxy for urban) Limit to 25+ 3

19 MetS-IDF* Waist circumference Women 80 cm Men 94 cm + Any Two of: Blood pressure (mmhg) Systolic 130 Diastolic 85 HBP Tx HDL (mg/dl) Women <50 Men <40 Tx Triglycerides (mg/dl dl) 150 or Tx Fasting glucose (mg/dl) 100 or Tx MetS-ATP III** Any Three Waist Circumference: Women Men cm Blood pressure (mmhg) Systolic 130 Diastolic 85 HDL (mg/dl dl) Women <50 Men <40 Tx Triglycerides (mg/dl dl) 150 or Tx Fasting glucose (mg/dl) 100 or Tx *International Diabetes Federation Consensus Worldwide definition. ** Adult Treatment Panel III, National Cholesterol Education Program Weighted demographics HEP % Mean (s.d.) Age (mean) 45.7 (0.7) Female 52.3% African American: 56.8 White: 18.8 Latino: 22.2 Per capita HH income: <4.5K K K 24.7 >16.2K 24.6 Education < 12 yrs yrs 29.1 > 12 yrs 32.8 MetS Components % Mean (s.d.) Blood pressure medication (%) 16.9 Blood Pressure Diastolic (weighted mean) 79.3 (0.5) Systolic (weighted mean) (0.7) HDL (weighted mean) 53.8 (0.6) Male 53.9 (0.9) Female 53.6 (0.7) Hypercholesteremia (%) 40.1 Triglycerides (weighted mean) (6.6) Waist circumference (cm) 97.9 (0.6) Male 98.7 (0.9) Female 97.1 (0.6) 4

20 Age-adjusted Proportion MetS by Definition IDF 63.0 Male 62.8 Female 63.1 ATP III 59.9 Male 49.8 Female Female Table 2: Weighted gender-specific prevalence ratios IDF and ATP III MetS across racial & ethnic categories, adjusted for age (Model 1) & for age & income (Model 2) (95% CI). Model 1 Hisp 0.64 (0.46, 0.88) NHW 0.71 (0.59, 0.86) NHB (ref) Female Male IDF ATP III IDF ATP III Model (0.33, 1.17) 0.69 (0.51, 0.93) Model (0.26, 1.26) 0.65 (0.43, 0.99) Model (0.17, 1.86) 0.64 (0.33, 1.23) Model (0.31, 0.92) 0.59 (0.40, 0.99) Model (0.20, 1.36) 0.58 (0.31, 1.08) Model (0.14, 1.69) 0.55 (0.23, 1.32) Model (0.08, 2.95) 0.54 (0.15, 1.95) = adjusted for age 2=adjusted for age and income Table 3a: Weighted, age-adjusted adjusted gender- specific prevalence ratio of MetS by per capita household income, full sample (95% CI). Women Men Per capita IDF ATP III IDF ATP III HH income Q (1.28, 1.54) (1.20,1.84) (1.53, 1.85) (1.08, 2.71) Q (1.36, 1.57) 1.60 (1.12,2.29) 1.75 (1.62, 1.90) 1.85 (1.01, 3.39) Q (1.42, 1.64) 1.62 (1.18,2.20) 1.82 (1.66, 2.00) 1.87 (1.07, 3.27) Q4 (High, ref)

21 Table 3b: Weighted, age-adjusted adjusted gender- specific prevalence ratio of MetS by per capita household income, full sample (95% CI). Female Male Years Ed IDF ATP III IDF ATP III < 12 yrs 1.48 (1.18, ) 1.84) 1.54 (089 (0.89, 265) 2.65) 1.77 (1.13, ) 2.77) 1.79 (059 (0.59, 545) 5.45) 12 yrs 1.48 (1.12, 1.94) 1.60 (0.79, 3.25) 1.77 (1.08, 2.92) 1.86 (0.52, 6.67) > 12 yrs (ref) Table 4a. Weighted age-adjusted adjusted gender-specific prevalence ratios for MetS, comparing racial and ethnic groups within income and education strata (NHB, ref). Women IDF ATP III Hispanic NHW NHB (ref) Hispanic NHW NHB (ref) Income Q (0.99,1.03) (0.95,1.02) 1 (0.99,1.03) (0.96,1.02) 1 Q (0.98,1.09) (0.95,1.05) 1 (0.98,1.08) (0.96,1.05) 1 Q (0.98,1.07) (0.93,1.02) 1 (0.98,1.07) (0.94,1.02) 1 Q (0.95,1.11) (0.96,1.04) 1 (0.96,1.10) (0.96,1.04) 1 Education 1.05 <12 (1.01,1.09) (1.01,1.11) > (0.96,1.05) 1.00 (0.97,1.04) (0.94,1.02) (0.94,1.01) (1.01,1.08) 1.05 (1.01,1.10) 1.00 (0.97,1.04) 1.00 (0.97,1.04) (0.94,1.02) (0.95,1.01) 1 Table 4b. Weighted age-adjusted adjusted gender-specific prevalence ratios for MetS, comparing racial and ethnic groups within income and education strata (NHB, ref). Men IDF ATP III Hispanic NHW NHB (ref) Hispanic NHW NHB (ref) Income Q (1.00,1.09) (0.83,1.05) 1 (1.00,1.08) (0.84,1.05) 1 Q (1.00,1.12) (0.94,1.05) 1 (1.00,1.11) (0.94,1.04) 1 Q (0.92,1.04) (0.92,1.01) 1 (0.93,1.04) (0.93,1.01) 1 Q (1.02,1.10) (0.93,1.04) 1 (1.02,1.09) (0.94,1.03) 1 Education 1.10 <12 (1.03,1.16) (1.01,1.08) > (0.94,1.03) 1.04 (0.98,1.11) (0.90,1.00) (0.88,0.98) (1.03,1.15) 1.04 (1.01,1.07) 0.98 (0.94,1.03) 1.04 (0.98,1.10) (0.90,1.00) (0.89,0.98) 1 6

22 Limitations Cross sectional data Relatively small sample Relatively circumscribed income & education levels 50% <$20K 7% >4 years college Detroit residents may experience reduced access to resources necessary to maintain health regardless of income Summary Higher prevalence MetS than other studies (NHANES, Pitt County, JHS) Gender-specific racial & ethnic differences largely attenuated after adjusting for income Results consistent with hypothesis that MetS varies by SEP (income & education) IDF may be more sensitive to differences by SEP? Some variations remain after accounting for income & education (e.g., Hispanics with <=12 yrs > MetS than NHB in same ed. category) Next Steps Why is prevalence so much higher in this sample, compared to NHANES, Pitt Co, JHS? Income? Education? Stress? Observed social & physical environmental characteristics? Race-based residential segregation & econ. divestment? Analyses Prevalence ratios after adjusting for psychosocial stress (Schulz) Jackson/Detroit study (Johnson) Multilevel models/neighborhood characteristics (Schulz) Distribution of MetS Components (L. Lachance) Standardized models comparing NHANES urban & HEP (Mentz/Schulz) 7

23 Weighted demographics HEP & NHANES HEP NHANES Age (mean) 45.7 (0.7) 48.9 (0.7) Female 52.3% 51.0% African American: White: Latino: Per capita HH income: <4.5K K K >16.2K Education < 12 yrs yrs > 12 yrs

24 Socioeconomic Patterns in the prevalence of Metabolic Syndrome among non-hispanic Black, non-hispanic White, and Latino adults in Detroit, Michigan Amy J. Schulz, Laurie Lachance, Jonetta Johnson, Graciela Mentz, Carmen Stokes, Causandra Gaines Table 1. Demographics/Sample Characteristics Weighted Mean (SE) Weighted % Age (weighted mean) 45.7 (0.7) Gender (%) Male 47.7 Female 52.3 Race/Ethnicity(%) Hispanic 22.2 Non-Hispanic White 18.8 Non-Hispanic Black (referent) 56.8 Income/persons in HU (%) <$4, $4500 7, $7,500 16, $16,200 + (referent) 24.6 Education (%) < 12 years years 29.1 >12 years (referent) 32.8 MetS Components Blood pressure medication (%) 16.9 Diastolic Blood Pressure (weighted mean) 79.3 (0.5) Systolic Blood Pressure (weighted mean) (0.7) High Density Lipoproteins (weighted mean) 53.8 (0.6) HDL Male HDL Female 53.9 (0.9) 53.6 (0.7) Medication for hypercholesteremia (%) 40.1 Triglycerides (weighted mean) (6.6) Waist circumference (weighted mean in cm) 97.9 (0.6) WC Male WC Female 98.7 (0.9) 97.1 (0.6) Age-adjusted Proportion MetS by Definition MetS (% IDF) 63.0 Male Female MetS (% ATP III) 59.9 Male Female Under review, please do not circulate without permission from first author

25 Table 2: Weighted gender-specific prevalence ratios of IDF and ATP III MetS across racial and ethnic categories, adjusted for age (Model 1) and for age and income (Model 2) (95% CI). Female Male MetS-IDF MetS ATP III MetS-IDF Male ATP III Model 1 Model 2 Model 1 Model 2 Model 1 Model 2 Model 1 Model 2 Hispanic 0.64 (0.46,0.88) 0.62 (0.33,1.17) 0.57 (0.26, 1.26) 0.56 (0.17, 1.86) 0.53 (0.31, 0.92) 0.52 (0.20, 1.36) 0.48 (0.14, 1.69) 0.47 (0.08, 2.95) NHW 0.71 (0.59,0.86) 0.69 (0.51,0.93) 0.65 (0.43, 0.99) 0.64 (0.33, 1.23) 0.59 (0.40, 0.88) 0.58 (0.31, 1.08) 0.55 (0.23, 1.32) 0.54 (0.15, 1.95) NHB

26 Table 3: Weighted, age-adjusted gender-specific prevalence ratio of MetS by per capita household income, for full sample and within racial and ethnic categories. (95% CI) IDF Women ATP-III IDF Men ATP-III Per Capita Household Income: Full sample <$4, (1.28, 1.54) 1.48(1.20,1.84) 1.68 (1.53, 1.85) 1.71 (1.08, 2.71) $4,500-7, (1.36, 1.57) 1.60(1.12,2.29) 1.75 (1.62, 1.90) 1.85 (1.01, 3.39) $7,500-16, (1.42, 1.64) 1.62(1.18,2.20) 1.82 (1.66, 2.00) 1.87 (1.07, 3.27) >$16,200 (ref) Hispanic <$4, (0.91, 2.46) 1.63(0.73,3.68) 1.78 (0.75, 4.21) 1.93 (0.48, 7.83) $4,500-7, (0.85, 2.90) 1.81(0.56,5.90) 1.87 (0.70, 5.00) 2.14 (0.37, 12.56) $7,500-16, (0.86, 3.13) 1.81(0.55,6.00) 1.95 (0.70, 5.41) 2.14 (0.36, 12.80) >$16,200 (ref) Non-Hispanic White <$4, (1.14, 1.57) 1.42(1.05,1.92) 1.59 (1.00, 2.55) 1.68 (0.70, 4.00) $4,500-7, (1.12, 1.77) 1.57(0.82,3.01) 1.67 (0.93, 3.01) 1.86 (0.54, 6.40) $7,500-16, (1.12, 1.91) 1.57(0.80,3.09) 1.74 (0.93, 3.27) 1.86 (0.53, 6.56) >$16,200 (ref) Non-Hispanic Black <$4, (1.15, 1.63) 1.48(0.95,2.31) 1.63 (0.96, 2.77) 1.76 (0.63, 4.89) $4,500-7, (1.08, 1.91) 1.65(0.73,3.73) 1.71 (0.89, 3.29) 1.95 (0.48, 7.90) $7,500-16, (1.08, 2.07) 1.65(0.71,3.82) 1.78 (0.89, 3.57) 1.95 (0.47, 8.08) >$16,200 (ref)

27 Table 4: Weighted, age-adjusted gender-specific prevalence ratio of MetS by level of education, for full sample and within racial and ethnic categories (95% CI) IDF Women ATP-III IDF Men ATP-III Level of Education: Full sample <12 years 1.48 (1.18, 1.84) 1.54 (0.89, 2.65) 1.77 (1.13, 2.77) 1.79 (0.59, 5.45) 12 years 1.48 (1.12, 1.94) 1.60 (0.79, 3.25) 1.77 (1.08, 2.92) 1.86 (0.52, 6.67) >12 years (ref) Hispanic <12 years 1.56 (1.15, 2.11) 1.71 (0.75, 3.89) 1.86 (1.10, 3.15) 2.04 (0.53, 7.78) 12 years 1.61 (1.10, 2.34) 1.84 (0.62, 5.50) 1.92 (1.05, 3.51) 2.20 (0.44, 10.98) >12 years (ref) Non-Hispanic White <12 years 1.40 (1.19, 1.64) 1.46 (1.06, 2.01) 1.67 (1.16, 2.39) 1.74 (0.76, 4.00) 12 years 1.44 (1.15, 1.79) 1.58 (0.87, 2.85) 1.72 (1.11, 2.65) 1.88 (0.63, 5.65) >12 years (ref) Non-Hispanic Black <12 years 1.42 (1.17, 1.73) 1.52 (0.95, 2.43) 1.70 (1.12, 2.58) 1.82 (0.68, 4.83) 12 years 1.47 (1.11, 1.93) 1.64 (0.79, 3.43) 1.75 (1.06, 2.89) 1.96 (0.57, 6.82) >12 years (ref)

28 Table 5. Weighted age-adjusted gender-specific prevalence ratios for MetS, comparing racial and ethnic groups within income and education strata (non-hispanic Black, referent). (95% CI) Per capita household income MetS (IDF) Non- Hispanic Black Female MetS (ATP III) Non- Hispanic Black Hispanic Non-Hispanic White Hispanic Non-Hispanic White <$4, (0.99,1.03) 0.98(0.95,1.02) (0.99,1.03) 0.99(0.96,1.02) 1 $4,500-7, (0.98,1.09) 1.00(0.95,1.05) (0.98,1.08) 1.00(0.96,1.05) 1 $7,500-16, (0.98,1.07) 0.97(0.93,1.02) (0.98,1.07) 0.98(0.94,1.02) 1 >$16, (0.95,1.11) 1.00(0.96,1.04) (0.96,1.10) 1.00(0.96,1.04) 1 Education <12 years 1.05(1.01,1.09) 1.00(0.97,1.04) (1.01,1.08) 1.00(0.97,1.04) 1 12 years 1.06(1.01,1.11) 0.98(0.94,1.02) (1.01,1.10) 0.98(0.94,1.02) 1 >12 years 1.00 (0.96,1.05) 0.98(0.94,1.01) (0.97,1.04) 0.98(0.95,1.01) 1 Per capita household income Hispanic MetS (IDF) Non-Hispanic White Non- Hispanic Black Male Hispanic MetS (ATP III) Non-Hispanic White Non- Hispanic Black <$4, (0.100,1.09) 0.93(0.83,1.05) (1.00,1.081) 0.94(0.84,1.05) 1 $4,500-7, (1.00,1.12) 0.99(0.94,1.05) (1.00,1.11) 0.99(0.94,1.04) 1 $7,500-16, (0.92,1.04) 0.96(0.92,1.01) (0.93,1.04) 0.97(0.93,1.01) 1 >$16, (1.02,1.10) 0.98(0.93,1.04) (1.02,1.09) 0.99(0.94,1.03) 1 Education <12 years 1.10(1.03,1.16) 1.04(0.98,1.11) (1.03,1.15) 1.04(0.98,1.10) 1 12 years 1.05(1.01,1.08) 0.95(0.90,1.00) (1.01,1.07) 0.95(0.90,1.00) 1 >12 years 0.98(0.94,1.03) 0.93(0.88,0.98) (0.94,1.03) 0.93(0.89,0.98) 1 6