Agenda CIAHD Monthly Research Meeting SPH I, Room 2610 November 14, :30 2:00pm est/11:30-12:00pm cst. I. CIAHD-Updates 10 minutes

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1 Agenda CIAHD Monthly Research Meeting SPH I, Room 2610 November 14, :30 2:00pm est/11:30-12:00pm cst I. CIAHD-Updates 10 minutes II. Presentation: 45 minutes Samson Gebreab, PhD (NGHRI) Cross-sectional and longitudinal associations of type 2 diabetes and neighborhood environments: The Jackson Heart Study (JHS) *Light refreshments will be provided for UM attendees Website Connection Information: Webinar Address: Login as Guest, using your full name no password required CIAHD Overall Research Meetings Presentation Dates: Date Est Time Cst Time Presenter/Presentation Friday, September 19, :30-2:30 11:30-1:30 Megan Andrew, CIAHD Pilot Awardee, Changing residential segregation, changing racial/ethnic disparities in birth outcomes Friday, October 24, :30-2:30 11:30-1:30 Alana LeBron, UM PhD-C, Heightened Discrimination Against Latinos Following September 11th & Implications for Cardiovascular Health Friday, November 14, :30-2:30 11:30-1:30 Samson Gebreab, NGHRI, Neighborhood and diabetes Jackson Heart Study Friday, January 23, :30-2:30 11:30-1:30 Carina Gronlund, UM, Postdoctoral Research Fellow, Vulnerability to the Cardiovascular and Inflammatory Effects of Heat: Results from the Jackson Heart Study Friday, February 13, :30-2:30 11:30-1:30 Jaime Slaughter, Drexel, Birth Outcomes Friday, March 20, :30-2:30 11:30-1:30 Sarah Reeves, CIAHD Pilot Awardee, Ethnicity and the Availability and Use of Rehabilitation Venues Friday, April 10, :30-2:30 11:30-1:30 Kiarri Kershaw, CIAHD Pilot Awardee, Longitudinal associations of neighborhood-level racial segregation with cardiometabolic health Friday, May 15, :30-2:30 11:30-1:30 CIAHD Project PIs and Core Directors Update

2 Cross sectional and longitudinal associations of type 2 diabetes and neighborhood environments: The Jackson Heart Study (JHS). Samson Gebreab CIAHD 11/14/2014 Disclaimer Dr. Gebreab contributed to this presentation in his personal capacity. The views expressed are his own and do not necessarily represent the views of the National Institutes of Health or the United States Government. Background Neighborhood environment has been implicated with a variety of health outcomes, including type 2 diabetes. Diez Roux et al. (2002) found neighborhood deprivation was associated with the insulin resistance syndrome in black adults using ARIC Study. Schootman et al. (2007) found adverse housing conditions were associated with an increased risk of diabetes in urban middle aged African Americans living in St. Louis, Missouri. Krishnan et al. (2009) found association between neighborhood socioeconomic status and incidence of diabetes among African American women in the Black Women's Health Study. Auchincloss et al. (2009) found better neighborhood resources for physical activity and healthy foods associated with a lower incidence of diabetes in MESA study, but this study did not investigate the associations by race/ethnicity. Overall, there is limited studies of the associations between specific features of neighborhood environments and diabetes in African Americans. 1

3 Conceptual Model Neighborhood Environments and Incident Diabetes Socio Demographic (age, gender, SES) Family History Obesity Neighborhood Environments Incident T2DM Health Behaviors (smoking, alcohol, physical activity, diet) Objectives To examine cross sectional and longitudinal associations between neighborhood physical and social environments and type 2 diabetes. To examine where individual socioeconomic status, level of physical activity, diet, and BMI partially explain the associations of neighborhood physical and social environments with type 2 diabetes. Research Hypothesis Are neighborhood environments at baseline associated with prevalence, of type 2 diabetes. Hypothesis 1: People living in better neighborhood environment experience decreased odds of having type 2 diabetes. Are neighborhood environments at baseline associated with incidence of type 2 diabetes? Hypothesis 2: People living in better neighborhood environments at baseline experience lower risk of type 2 diabetes. Are changes in neighborhood environments over time associated with incident of type 2 diabetes? Hypothesis 3: People living in neighborhoods with greater improvements of neighborhood environments over time will have decreased risk in diabetes over time. 2

4 Study Population The Jackson Heart Study (JHS) is a prospective cohort study designed to investigate factors that influence the development of CVD in African Americans. Between 2000 and 2004, 5,301, non institutionalized African American men and women aged 21 to 95 were recruited from three counties (Hinds, Madison, Rankin counties ). For this analysis data from the baseline and 2 follow up exams was used. Baseline exam ( ), exam 2 ( ) and exam 3 ( ) Outcome Diabetes was measured at baseline, Exam 2, and Exam 3. Type 2 diabetes was defined according to 2010 American Diabetes Association criteria (ADA, 2010). Prevalence of diabetes was determined based in participants that have type 2 diabetes at baseline exam. Incident diabetes was determined in participants who were free of type 2 diabetes at baseline exam. The date of incident diabetes was assigned to the midpoint between the last visit without diabetes and the next visit with diabetes. Neighborhood Environments Survey Based Neighborhood Environments (measured at exam 1) Social cohesion Violence Problems Age& gender adjusted unconditional empirical Bayes estimates GIS Based Densities of Neighborhood Resources ( measured at Exam 1 & Exam 2) Food store density Favorable food stores Sum of supermarket (chain and non chain) and fruit and vegetable markets 1 mile Kernel density Unfavorable food stores Sum of convenience stores, bakeries/nuts/candy/ice cream, liquor stores, drinking places (alcoholic), fast food chains and fast food nonchains 1 mile Kernel density Total physical activities resources Indoor conditioning, dance, bowling, backing, hiking, and team and racquet sports, swimming, physical activity instruction, and water activities. 1 mile Kernel density 3

5 Survey Based Neighborhood Environments Items Description Code Social Cohesion 1 =Strongly Disagree (D) to 4=Strongly Agree (A) AF3V13 This is a close knit neighborhood AF3V14 People around here are willing to help their neighbors AF3V15 People in this neighborhood generally don't get along (REVERSE CODED) AF3V16 People in this neighborhood can be trusted AF3V17 People in this neighborhood do not share the same values (REVERSE CODED) Violence 1=Never (N) to 4 =Often (O) AF3V19 How often was there a fight in this neighborhood in which a weapon was used AF3V20 How often was there a violent argument between neighbors AF3V21 How often were there gang fights? AF3V22 How often was there a sexual assault or rape? AF3V23 How often was there a robbery or mugging? Problems 1= Not really a problem (N), 4=Very serious problem (V) AF3V24 Excessive noise AF3V25 Heavy traffic or speeding cars AF3V26 Lack of access to adequate food and/or shopping AF3V27 Lack of parks and playground AF3V28 Trash and Litter AF3V29 No sidewalks and poorly maintained sidewalks Correlation coefficients SC VO NP Social cohesion (SC) Violence (VO) 0.76 Problems (NP) Correlation coefficients K1FAVV1 K1UNFAVV1 K1PAIV1 K1FAVV1 K1UNFAVV K1PAIV

6 Additional Covariates Baseline covariates Age (years) Gender (Male or female) Socioeconomic status: Income and Education BMI (continuous) Smoking (current smokers) Alcohol consumption (yes/no) Physical activity (continuous) Family history of diabetes (yes/no) Diet (% fat), Also adjusted for Time-varying covariates (Age, BMI) Statistical Analysis Generalized estimating equations (GEEs) models were used to estimate the associations between neighborhood features and prevalence of diabetes, with census tract id specified as a cluster variable. Cox proportional hazards models with sandwich estimator were used to estimate the associations neighborhood features (time invariant and time varying) and incident of diabetes. Midpoint between visits was used to approximate time to incidence of diabetes. As a sensitivity analysis, interval censoring using weibull accelerated failure time (AFT) regression models were also performed (results were similar). Five sequential models were fitted for each neighborhood features. Model 1: Age and family history, Model 2: Model 1 + individual SES variables (i.e., income and education), Model 3: Model 2 + current smokers + alcohol consumption, Model 4: Model 3 + physical activity + diet, Model 5: Model 4 + BMI Sample size flow chart Prevalence of Diabetes (Baseline Exam) Incidence of Diabetes (Exam 1 Exam3) Excluding missing diabetes N=92 Excluding baseline diabetes & missing diabetes N= Excluding missing Neighborhood variables N=11 Excluding missing Neighborhood variables N= Excluding missing baseline covariates N=315 Excluding missing baseline covariates N= Analysis sample (Note: Missing Income 3695 Analysis sample (Note: Missing income (N=766 (16%)) coded as dummy variable) (N=562(15%)) coded as dummy variable) 5

7 Social cohesion: P value for overall association = P value for non linear = Violence: P value for overall association = P value for non linear = Problems: P value for overall association = P value for non linear = Favorable food stores: P value for overall association = P value for non linear = Unfavorable food stores: P value for overall association = P value for non linear = Physical activities Resources: P value for overall association = P value for non linear = Total Sample No. of participants 4914 No (N=3839) Prevalence of Type II Diabetes a Yes (N=1075) P Value Demographic Characteristics Age, y, mean(sd) 55.2 (12.8) 53.7 (13.0) 60.6 (10.6) <0.001 men Family History of diabetes <0.001 Socioeconomic Status Income <0.001 Low Income Lower Middle Upper Middle Affluent Education <0.001 < HS HS/GED Voc/Some College/AA degree College Graduate Risk factors/health Behaviors Smoking status Never Former Current Alcohol drinking <0.001 Physical activity, mean (SD) 8.4 (2.6) 8.6 (2.5) 7.5(2.6) <0.001 Percent fat 35.0 (6.9) 34.9 (6.8) 34.3 (7.3) BMI, mean (SD) 31.8 (7.3) 31.1(7.1) 34.3(7.2) <0.001 Prevalence of Diabetes b Percieved Social Environments Social cohesion 3.02 ( ) 3.03 ( ) 3.01( ) <0.001 Violence 1.28 ( ) 1.26( ) 1.28( ) <0.001 Problems 1.58 ( ) 1.56 ( ) 1.61( ) <0.001 c GIS Based Neighborhood Resources Baseline 1 mile favorable food stores 0.00( ) 0.00( ) 0.05 ( ) <0.001 Baseline 1 mile unfavorable food store 2.34( ) 2.18( ) 2.81( ) <0.001 Baseline 1 mile Physical activity resources 0.16( ) 0.14 ( ) 0.19( ) Table 1: Participants characteristics at baseline by prevalence of diabetes ( ) 6

8 Table 2: Adjusted PRs for Type 2 Diabetes Prevalence Corresponding to a Difference Between the 90th and 10th Percentiles in Perceived Social Environments Women (N=3110) Social Cohesion Violence Problems Model No. PR (95% CI) P Value PR (95% CI) P Value PR (95% CI) P Value Model (0.85, 1.00) (1.00,1.20) (0.99, 1.22) Model (0.85, 1.01) (0.99, 1.19) (0.97, 1.21) Model (0.84, 1.01) (0.99, 1.19) (0.97, 1.21) Model (0.86, 1.05) (1.00, 1.19) (0.97,1.21) Model (0.88, 1.07) (0.97,1.17) (0.94,1.18) Men (N=1804) Social Cohesion Violence Problems Model No. PR (95% CI) P Value PR (95% CI) P Value PR (95% CI) P Value Model (0.68, 0.99) (0.95,1.29) (1.30, 1.81) <.0001 Model (0.65, 0.97) (0.95,1.34) (1.34,1.75) <.0001 Model (0.64, 0.92) (0.97,1.38) (1.29, 1.69) <.0001 Model (0.66, 0.91) (1.02,1.43) (1.18, 1.58) <.0001 Model (0.65, 0.90) (1.02,1.43) (1.18, 1.60) <.0001 Abbreviations: BMI, body mass index (calculated as weight in kilograms divided by height in meters squared); CI, confidence interval; PR, Prevalence Ratio. Model 1: Age, and family history of diabetes Model 2: Model 1 + Income, and educational level Model 3: Model 2 + Alcohol intake, and cigarette smoking status Model 4: Model 3 + physical activity level, and diet (percent fat) Model 5: Model 4 + BMI Adjusted PRs for Type 2 Diabetes Prevalence Corresponding to a Difference Between the 90th and 10th Percentiles in Neighborhood Resources Women (N=3110) Men (N=1804) Age &Family P Fully Age &Family P Fully P History adjusted value Adjusted P value History adjusted value Adjusted value Favorable food stores 1.07(1.00, 1.15) (0.97,1.14) (0.87, 1.05) (0.86, 1.05) Unfavorable food stores 1.09(0.95, 1.25) (0.95,1.27) (0.86,1.13) (0.88, 1.23) Physical activities resources 1.08(1.01, 1.16) (1.00, 1.17) (0.89,1.09) (0.88, 1.12) Fully adjusted model: age, family history, income, education, alcohol intake, current smokers, physical activity, percent fat, and BMI Incident of Diabetes No. of participants 3695 No (N=3172) Yes (N=523) P Value Demographic Characteristics Age, y, mean(sd) 53.8 (13.0) 53.6 (13.3) 55.2 (11.1) Men Family History of diabetes <0.001 Socioeconomic Status Income Low Income Lower Middle Upper Middle Affluent Education < HS HS/GED Voc/Some College/AA degree College Graduate Risk factors/health Behaviors Smoking status Never Former Current Alcohol drinking Physical activity, mean (SD) 8.6 (2.5) 8.7 (2.5) 8.6(2.5) Percent fat 35.0 (6.8) 34.9 (6.8) 34.9 (6.8) BMI, mean (SD) 31.1 (7.1) 30.7(7.1) 33.6(7.1) <.0001 Diabetes at any follow up examination b Perceived Neighborhood Environments Social Cohesion 3.03 ( ) 3.03 ( ) 3.01 ( ) Violence 1.26 ( ) 1.26 ( ) 1.26 ( ) Problems 1.56 ( ) 1.56 ( ) 1.58 ( ) c GIS Based Neighborhood Environments Table 2: Participants characteristics at baseline by incident diabetes ( ) Baseline 1 mile Favorable food Stores 0.00( ) 0.00( ) 0.02( ) Change in Favorable Food Stores 0.00( ) 0.00 ( ) 0.00( ) Baseline 1 mile unfavorable food Stores 2.18( ) 2.10( ) 2.49( ) Change in Unfavorable food stores 0.07( ) 0.05( ) 0.21( ) Baseline 1 mile Physical activity resources 0.14( ) 0.14( ) 0.17( ) Change in Physical activity resources 0.00( ) 0.00( ) 0.02( )

9 Table 3a: Adjusted HRs for Type 2 Diabetes Incidence Corresponding to a Difference Between the 90th and 10th Percentiles in Perceived Neighborhood Environments Women (N= 2313, Events=331) Neighborhood Social Cohesion Violence Problems Model No. HR (95% CI) P Value HR (95% CI) P Value HR (95% CI) P Value Model (0.58,0.92) (0.86,1.42) (0.89,1.59) Model (0.59,0.94) (0.84,1.38) (0.87,1.56) Model (0.58,0.93) (0.84,1.38) (0.87,1.57) Model (0.56,0.93) (0.84,1.42) (0.88,1.64) Model (0.59,0.98) (0.79,1.33) (0.85,1.55) Men (N= 1382, Events= 192) Neighborhood Social Cohesion Violence Problems Model No. HR (95% CI) P Value HR (95% CI) P Value HR (95% CI) P Value Model (0.71,1.27) (0.90,1.49) (0.94,1.60) Model (0.71,1.36) (0.87,1.54) (0.89,1.63) Model (0.70,1.37) (0.86,1.54) (0.89,1.64) Model (0.64,1.25) (0.88,1.59) (0.91,1.68) Model (0.64,1.27) (0.86,1.53) (0.88,1.65) Abbreviations: BMI, body mass index (calculated as weight in kilograms divided by height in meters squared); CI, confidence interval; HR, hazard ratio. Model 1: Age, and family history of diabetes Model 2: Model 1 + Income, and educational level Model 3: Model 2 + Alcohol intake, and cigarette smoking status Model 4: Model 3 + physical activity level, and diet (percent fat) Model 5: Model 4 + BMI HR is estimated using Cox Hazard regression with sandwich estimator accounting for nesting within neighborhood, and time to event was approximated by using midpoints between clinic visits Table 3b: Adjusted HRs for Type 2 Diabetes Incidence Corresponding to a Difference Between the 90th and 10th Percentiles in Perceived Neighborhood Environments Women (N= 2313, Events=331) Social Cohesion Violence Problems HR (95% CI) P Value HR (95% CI) P Value HR (95% CI) Model No. P Value Model (0.55, 0.97) (0.84, 1.42) (0.89, 1.55) Model (0.55, 1.00) (0.81, 1.40) (0.87,1.55) Model (0.55, 0.99) (1.41, 0.82) (0.87, 1.55) Model (0.53, 0.99) (0.82, 1.44) (0.89, 1.62) Model (0.55, 1.03) (0.77, 1.36) (1.55, 0.85) Men (N= 1382, Events= 192) Social Cohesion Violence Problems HR (95% CI) P Value HR (95% CI) P Value HR (95% CI) Model No. P Value Model (0.67, 1.38) (0.83, 1.61) (0.86, 1.72) Model (0.68,1.45) (0.81, 1.63) (0.84, 1.72) Model (0.68, 1.45) (0.80,1.63) ( 0.82,1.73) Model (0.60, 1.34) (0.81,1.70) (0.83, 1.80) Model (0.61,1.36) (0.78, 1.64) (0.80, 1.74) Abbreviations: BMI, body mass index (calculated as weight in kilograms divided by height in meters squared); CI, confidence interval; HR, hazard ratio. Model 1: Age, and family history of diabetes Model 2: Model 1 + Income, and educational level Model 3: Model 2 + Alcohol intake, and cigarette smoking status Model 4: Model 3 + physical activity level, and diet (percent fat) Model 5: Model 4 + BMI HR is estimated using interval censoring of Parametric accelerated failure Weibull distribution.adjusted HRs for Type 2 Diabetes Incidence Corresponding to a Difference Between the 90th and 10th Percentiles in Neighborhood Resources Women (N= 2313, Events=331) Men (N= 1382, Events= 192) Age & Family P P Age & Family P P History adjusted value Fully Adjusted value History adjusted value Fully Adjusted value Baseline Favorable food stores 1.18(0.93, 1.51) (0.99,1.73) (0.98, 1.72) (0.91, 1.37) Baseline Unfavorable food stores 1.26(1.02, 1.56) (1.01, 1.55) (1.17,1.88) (1.15, 1.90) Baseline Physical activity resources 1.09(0.92, 1.29) (0.92, 1.30) (0.91,1.37) (0.89, 1.36) Fully adjusted model: age, family history, income, education, alcohol intake, current smokers, physical activity, percent fat and BMI 8

10 Summary of Findings Neighborhoods with better social cohesion were associated, with 24% of lower prevalence of diabetes in men, but not in women. Neighborhoods with worse problem were associated, with 37% of higher prevalence of diabetes in men, but not in women. Neighborhood violence, densities of favorable and unfavorable food stores, and physical activities resources were not associated with prevalence of diabetes in both women and men. Neighborhoods with higher social cohesion was associated, with 28% of lower incidence of diabetes in women after adjusting for risk factors of diabetes. Additional adjustment for baseline BMI slightly reduced to 24% of lower incidence of diabetes among women. Density of unfavorable food stores was associated with 25% and 48% of increased risk of diabetes in women and men, respectively, even after adjusting for diabetes risk factors, including BMI. Neighborhood violence and problems, and densities of favorable food stores and physical activity resources were not associated with incident diabetes. Strengths and Limitations Strengths Longitudinal and incident data. Specific features of neighborhood environments Survey and GIS based measures Limitations Results are not generalizable to other population or other regions of US Residual confounding factors: eating habits, cultural beliefs health conscious, etc. GIS based densities of food stores physical resources are limited don t capturing the types, access and pricing food items and physical activity resources, as well as awareness of these resources. Measurement errors. Acknowledgements Dr. Ana Diez Roux CIAHD Jackson Heart Study NHGRI s Division of Intermural Research 9

11 Thank You! Any feedback or question would be greatly appreciated. 10