1
Results: For both hospital-based and community-based settings, visits where patients had diagnosed hypertension had a greater proportion of visits where BP was measured at the time of the visit compared to visits where the patient did not have diagnosed hypertension. Visits to hospital based physician ofces had a greater proportion of visits where BP was measured at the time of the visit compared to visits made to community based physician ofces. No signicant differences were seen over time for either diagnosed hypertension or care setting. Conclusion: Each year, over one billion outpatient visits are made to community-based and hospital-based physician ofces; providing opportu- nities to monitor BP. Preliminary data suggest that monitoring opportunities are being missed for both care settings regardless of diagnosis of hyperten- sion. Methods P44-S. Categorising Continuous Risk Factors: Issues and Impications D.Y. Abdallah. School of Public Health, University College Dublin, Dublin, Ireland Purpose: Grouping continuous variables into two or more categories for the purposes of simplicity and ease of analysis and interpretation is a widely used approach in medical and epidemiologic research. Categorization, however, has been found to lead to loss of power and efciency, to affect internal validity, and to produce biased results. This review of the literature aims to highlight the bias produced by categorizing continuous variables and its impact on evidence synthesis. Methods: A literature review of the effects of categorization is performed with a discussion of the alternative methods proposed to model outcome- exposure relationships. The impact of modeling body mass index (BMI) as a continuous variable versus the categorization of BMI is compared using examples from the literature. Results: Categorization of continuous variables is statistically unnecessary and can result in loss of efciency. Dichotomization has been found to hinder meta-analyses of observational studies and to pose several drawbacks such as loss of power, residual confounding, and assumptions of linearity. Several alternative modeling methods have been proposed, such as spline regression and smoothing techniques and generalized additive models. These methods have higher power, but require adequate sample size and sufcient data on ranges of exposure. For meta-analyses of doseresponse relationships, a number of techniques have been developed for the synthesis of summary regression slopes. We review the complexities, limitations, and challenges posed by these methods. In relation to BMI, some research suggests that different modeling techniques considerably inuence estimates of the rela- tionship between BMI and mortality, with categorizations yielding biased results. Yet, other researchers have found BMI categorization to produce good t estimates. Conclusion: Grouping of continuous variables produces inconsistent and biased risk estimates. When modeling epidemiological and medical data, researchers should be aware of the trade-offs between proper statistical approaches and ease of interpretability of results. P45. Is Choice of Segregation Index Important in Assessing the Role of Racial Residential Segregation on AIDS Survival? K.P. Fennie, L. Maddox, K. Lut, V. Pelletier, M.J. Trepka. Department of Epidemiology, Florida International University, Miami, FL Purpose: Non-Hispanic Blacks (NHB) have disproportionately lower AIDS survival compared to Non-Hispanic Whites. Racial residential segregation may be one environmental factor playing a role in observed racial disparities in AIDS survival. Segregation can be measured, using many indices, on ve dimensions: Unevenness, exposure, concentration, centralization, and clus- tering. Unevenness (Dissimilarity Index) is used widely due to its simplicity and historical context. We compare AIDS survival among NHB diagnosed from 1999 to 2004 in Florida on ve indices representing the ve dimensions of segregation. Methods: Data were obtained from the Florida HIV/AIDS Surveillance System, Florida Vital Records, and the National Death Index. Weighted Cox models were run to examine segregation on survival, controlling for demo- graphic and clinical factors and area-level poverty. Results: Among those diagnosed post-HAART, segregation was associated with lower survival using measures of exposure (HR¼1.32, 95%CI¼ 1.07, 1.64), concentration (HR¼1.31, 95%CI¼ 1.12,1.53), centralization (HR¼1.52, 95%CI¼ 1.19, 1.94), and clustering (HR¼1.56, 95%CI¼1.15, 2.13). Unevenness was not associated with survival. Conclusion: The Dissimilarity Index is used commonly to measure segre- gation; yet it failed to show an association between segregation and survival. Using other less used indices measuring different dimensions may help us to understand better, the role of segregation on health outcomes. P46. The Health of Women (HOW) Study: A Novel Approach to the Cohort Study C.A. Fischetti, N. Sykes, L. Bernstein, J. Sullivan-Halley, J. Clague, S.M. Love. Dr. Susan Love Research Foundation, Santa Monica, CA Purpose: The purpose of the Health of Women (HOW) Study is to examine risk factors for breast cancer and factors that may contribute to long-term survivorship through an innovative online system that allows for participant engagement and data sharing with the research community. Methods: The HOW Study is conducted through online and mobile phone platforms. Questionnaires are developed in our custom built survey tool and are available for completion on the study's website. The system allows for automated skip patterns within questionnaires and collection of data directly into a SQL database. The cohort is open to anyone 18 years or older; recruitment sources include the Love/Avon Army of Women and the general public. Participants will be given the opportunity to pose questions they would like to see answered. The HOW Study is also a novel resource allowing outside researchers to submit questions to be incorporated into HOW questionnaires and creating a data sharing platform that facilitates researcher access to HOW data after an application process. Results: The HOW Study launched October 2012 and currently has 41, 300 participants from across the nation and the globe. We have released 1 baseline questionnaire and breast cancer-specic questionnaires to capture diagnosis and treatment with greater than 90% completion rate for each. Conclusion: We have shown that we can recruit and engage participants in an online cohort study. We believe that this study has the potential to transform epidemiologic research by engaging both participants and the research community. P47-S. Exam-Based Surveys for Evaluating Municipal Health Policy: New York City Health and Nutrition Examination Survey, 2004 and 2013 A.L. Freeman, Q.T. Vo, E.F. Snell, S.E. Perlman, P. DuBois, C.M. Greene, L.E. Thorpe. CUNY School of Public Health, New York, NY Purpose: Nearly a decade after the rst local Health and Nutrition Exami- nation Survey (HANES) was conducted in New York City (NYC), a second NYC HANES is being launched in 2013. Through a health survey, physical exam and biospecimen collection, the study will compare the health of NYC adults at two time periods to help evaluate municipal policy initiatives launched during the interim. It also will serve as a gold standardsource to test the validity of using a distributed electronic health record (EHR) network for population health surveillance purposes. Methods: We constructed a rigorous sampling frame of NYC housing employing address-based sampling and a three-stage cluster sample design. For survey questions and biospecimens, we prioritized consistency with 2004 NYC HANES. NYC trends will be compared to national data from NHANES. Questions were added to facilitate comparison to EHR data. Results: Using biomeasures from 2004 and 2013, we will measure the impact of the following municipal policy changes: anti-tobacco measures (cotinine), the launch of the rst hemoglobin A1c registry, and a ban on trans-fats in restaurants (trans-fatty acid biomarkers). Estimates on key measures of behaviors, clinical services, and disease prevalence and management will also be compared to estimates derived from a NYC based EHR network serving 1.2 million patients. Conclusion: NYC HANES and a NYC initiative to advance EHR surveillance represent novel methodologic approaches in epidemiology to assess pop- ulation health and inform policy. Abstracts / Annals of Epidemiology 23 (2013) 581e598 591

Categorising Continuous Risk Factors: Issues and Impications

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Abstracts / Annals of Epidemiology 23 (2013) 581e598 591

Results: For both hospital-based and community-based settings, visitswhere patients had diagnosed hypertension had a greater proportion ofvisits where BP was measured at the time of the visit compared to visitswhere the patient did not have diagnosed hypertension. Visits to hospitalbased physician offices had a greater proportion of visits where BP wasmeasured at the time of the visit compared to visits made to communitybased physician offices. No significant differences were seen over time foreither diagnosed hypertension or care setting.Conclusion: Each year, over one billion outpatient visits are made tocommunity-based and hospital-based physician offices; providing opportu-nities to monitor BP. Preliminary data suggest that monitoring opportunitiesare being missed for both care settings regardless of diagnosis of hyperten-sion.

Methods

P44-S. Categorising Continuous Risk Factors: Issues andImpications

D.Y. Abdallah. School of Public Health, University College Dublin, Dublin,Ireland

Purpose: Grouping continuous variables into two or more categories for thepurposes of simplicity and ease of analysis and interpretation is a widelyused approach in medical and epidemiologic research. Categorization,however, has been found to lead to loss of power and efficiency, to affectinternal validity, and to produce biased results. This review of the literatureaims to highlight the bias produced by categorizing continuous variables andits impact on evidence synthesis.Methods: A literature review of the effects of categorization is performedwith a discussion of the alternative methods proposed to model outcome-exposure relationships. The impact of modeling body mass index (BMI) asa continuous variable versus the categorization of BMI is compared usingexamples from the literature.Results: Categorization of continuous variables is statistically unnecessaryand can result in loss of efficiency. Dichotomization has been found to hindermeta-analyses of observational studies and to pose several drawbacks suchas loss of power, residual confounding, and assumptions of linearity. Severalalternative modeling methods have been proposed, such as spline regressionand smoothing techniques and generalized additive models. These methodshave higher power, but require adequate sample size and sufficient data onranges of exposure. For meta-analyses of doseresponse relationships,a number of techniques have been developed for the synthesis of summaryregression slopes. We review the complexities, limitations, and challengesposed by these methods. In relation to BMI, some research suggests thatdifferent modeling techniques considerably influence estimates of the rela-tionship between BMI and mortality, with categorizations yielding biasedresults. Yet, other researchers have found BMI categorization to producegood fit estimates.Conclusion: Grouping of continuous variables produces inconsistent andbiased risk estimates. When modeling epidemiological and medical data,researchers should be aware of the trade-offs between proper statisticalapproaches and ease of interpretability of results.

P45. Is Choice of Segregation Index Important in Assessing theRole of Racial Residential Segregation on AIDS Survival?

K.P. Fennie, L. Maddox, K. Lutfi, V. Pelletier, M.J. Trepka. Department ofEpidemiology, Florida International University, Miami, FL

Purpose: Non-Hispanic Blacks (NHB) have disproportionately lower AIDSsurvival compared to Non-Hispanic Whites. Racial residential segregationmay be one environmental factor playing a role in observed racial disparitiesin AIDS survival. Segregation can be measured, using many indices, on fivedimensions: Unevenness, exposure, concentration, centralization, and clus-tering. Unevenness (Dissimilarity Index) is used widely due to its simplicityand historical context. We compare AIDS survival among NHB diagnosedfrom 1999 to 2004 in Florida on five indices representing the five dimensionsof segregation.Methods: Data were obtained from the Florida HIV/AIDS SurveillanceSystem, Florida Vital Records, and the National Death Index. Weighted Cox

models were run to examine segregation on survival, controlling for demo-graphic and clinical factors and area-level poverty.Results: Among those diagnosed post-HAART, segregation was associatedwith lower survival usingmeasures of exposure (HR¼1.32, 95%CI¼ 1.07,1.64),concentration (HR¼1.31, 95%CI¼ 1.12, 1.53), centralization (HR¼1.52, 95%CI¼1.19, 1.94), and clustering (HR¼1.56, 95%CI¼1.15, 2.13). Unevenness was notassociated with survival.Conclusion: The Dissimilarity Index is used commonly to measure segre-gation; yet it failed to show an association between segregation and survival.Using other less used indices measuring different dimensions may help us tounderstand better, the role of segregation on health outcomes.

P46. The Health of Women (HOW) Study: A Novel Approach tothe Cohort Study

C.A. Fischetti, N. Sykes, L. Bernstein, J. Sullivan-Halley, J. Clague, S.M. Love.Dr. Susan Love Research Foundation, Santa Monica, CA

Purpose: The purpose of the Health of Women (HOW) Study is to examinerisk factors for breast cancer and factors that may contribute to long-termsurvivorship through an innovative online system that allows for participantengagement and data sharing with the research community.Methods: The HOW Study is conducted through online and mobile phoneplatforms. Questionnaires are developed in our custom built survey tool andare available for completion on the study's website. The system allows forautomated skip patternswithin questionnaires and collection of data directlyinto a SQL database. The cohort is open to anyone 18 years or older;recruitment sources include the Love/Avon Army of Women and the generalpublic. Participants will be given the opportunity to pose questions theywould like to see answered. The HOW Study is also a novel resource allowingoutside researchers to submit questions to be incorporated into HOWquestionnaires and creating a data sharing platform that facilitatesresearcher access to HOW data after an application process.Results: The HOW Study launched October 2012 and currently has 41, 300participants from across the nation and the globe. We have released 1baseline questionnaire and breast cancer-specific questionnaires to capturediagnosis and treatment with greater than 90% completion rate for each.Conclusion: We have shown that we can recruit and engage participants inan online cohort study. We believe that this study has the potential totransform epidemiologic research by engaging both participants and theresearch community.

P47-S. Exam-Based Surveys for Evaluating Municipal HealthPolicy: New York City Health and Nutrition ExaminationSurvey, 2004 and 2013

A.L. Freeman, Q.T. Vo, E.F. Snell, S.E. Perlman, P. DuBois, C.M. Greene,L.E. Thorpe. CUNY School of Public Health, New York, NY

Purpose: Nearly a decade after the first local Health and Nutrition Exami-nation Survey (HANES) was conducted in New York City (NYC), a second NYCHANES is being launched in 2013. Through a health survey, physical examand biospecimen collection, the study will compare the health of NYC adultsat two time periods to help evaluate municipal policy initiatives launchedduring the interim. It also will serve as a “gold standard” source to test thevalidity of using a distributed electronic health record (EHR) network forpopulation health surveillance purposes.Methods: We constructed a rigorous sampling frame of NYC housingemploying address-based sampling and a three-stage cluster sample design.For survey questions and biospecimens, we prioritized consistency with2004 NYC HANES. NYC trends will be compared to national data fromNHANES. Questions were added to facilitate comparison to EHR data.Results: Using biomeasures from 2004 and 2013, wewill measure the impactof the following municipal policy changes: anti-tobacco measures (cotinine),the launch of the first hemoglobin A1c registry, and a ban on trans-fats inrestaurants (trans-fatty acid biomarkers). Estimates on key measures ofbehaviors, clinical services, and disease prevalence and management willalso be compared to estimates derived from a NYC based EHR networkserving 1.2 million patients.Conclusion: NYC HANES and a NYC initiative to advance EHR surveillancerepresent novel methodologic approaches in epidemiology to assess pop-ulation health and inform policy.