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Data Access Pilot Project Data Access Pilot Project (DAPP)(DAPP)
Mei-Hua Huang, DMei-Hua Huang, DrPHrPH
Sharon Stein Merkin, PhDSharon Stein Merkin, PhD
Core Directors:Core Directors: Gail Greendale, MD, Arun Karlamangla, PhD, MD Gail Greendale, MD, Arun Karlamangla, PhD, MD Teresa Seema, PhDTeresa Seema, PhD
DAPP Faculty:DAPP Faculty: Mei-Hua Huang, DrPHMei-Hua Huang, DrPH
Sharon Stein Merkin, PhDSharon Stein Merkin, PhD
Weijuan Han, MSWeijuan Han, MS
Funded by the Older Americans Independence Center (OAIC)Funded by the Older Americans Independence Center (OAIC)
Why DAPP?Why DAPP?
Personal Data ShopperPersonal Data Shopper
Tailor to your study needsTailor to your study needs How do you get your data?How do you get your data? Guidance/adviceGuidance/advice EfficiencyEfficiency
Introductions to DAPP FacultyIntroductions to DAPP Faculty
Mei-Hua Huang, DrPH, Mei-Hua Huang, DrPH,
Nutritional EpidemiologyNutritional Epidemiology
Sharon Stein Merkin, PhD, Sharon Stein Merkin, PhD,
Social EpidemiologySocial Epidemiology
Example using Public Data- Example using Public Data- NHANESNHANES
Is education associated with awareness,
treatment and control of hypertension?
DATA
• Potential overlap in the literature
• Obtain data
• weighting/survey design issues
unique to NHANES
STUDY DESIGN
• Cross sectional
• Multiple waves?
• Defining exposure and
outcome
• Analysis plan
Analysis
Publication
Example of Data Requiring ProposalExample of Data Requiring Proposal- SWAN- SWAN
Study Hypothesis
Data Study Design
Analysis
Publication
• Potential overlap• Request data access• Submit concept proposal to
publication committee• Analysis
Abstract, poster and manuscript submitted to publication committee Time consuming:
minimum months
Services of DAPPServices of DAPPResearch guidance/consultingResearch guidance/consulting
Guidance in implementing study hypothesesGuidance in implementing study hypotheses Identifying relevant datasetsIdentifying relevant datasets Assistance with data accessAssistance with data access
Available onlineAvailable online• Public data (e.g., NHANES)Public data (e.g., NHANES)• Non-public (e.g., SWAN)Non-public (e.g., SWAN)
Request to Study PI (e.g., PEPI)Request to Study PI (e.g., PEPI)
Guidance in navigating datasetsGuidance in navigating datasets ContactsContacts Analysis services*Analysis services*
*Minimal, potential analyst time depending on funding*Minimal, potential analyst time depending on funding
Dataset ListDataset ListStudyStudy Study DesignStudy Design
Study of Women's Health Across the Nation Study of Women's Health Across the Nation (SWAN)(SWAN)
Longitudinal Longitudinal cohortcohort
Postmenopausal Estrogen/Progestin Postmenopausal Estrogen/Progestin Interventions (PEPI)Interventions (PEPI)
Clinical trialClinical trial
Osteoporotic Fractures in Men (MrOS) StudyOsteoporotic Fractures in Men (MrOS) Study Longitudinal Longitudinal cohortcohort
Study of Osteoporotic Fractures (SOF)Study of Osteoporotic Fractures (SOF) Longitudinal Longitudinal cohortcohort
Rancho Bernardo StudyRancho Bernardo Study Longitudinal Longitudinal cohortcohort
Yoga Empowers Seniors Study (YESS)Yoga Empowers Seniors Study (YESS) Clinical trialClinical trial
Yoga for Kyphosis TrialYoga for Kyphosis Trial Clinical trialClinical trial
Dataset ListDataset ListStudyStudy Study DesignStudy Design
National Health and Nutrition Examination National Health and Nutrition Examination Survey (NHANES)Survey (NHANES)
Cross-sectionalCross-sectional
Multiethnic Study of Atherosclerosis (MESA)Multiethnic Study of Atherosclerosis (MESA) Longitudinal Longitudinal cohortcohort
Midlife in the United States (MIDUS)Midlife in the United States (MIDUS) Longitudinal Longitudinal cohortcohort
Coronary Artery Disease Risk Development in Coronary Artery Disease Risk Development in Young Adults (CARDIA) StudyYoung Adults (CARDIA) Study
Longitudinal Longitudinal cohortcohort
Atherosclerosis Risk in Communities (ARIC) Atherosclerosis Risk in Communities (ARIC) StudyStudy
Longitudinal Longitudinal cohortcohort
Cardiovascular Health Study (CHS)Cardiovascular Health Study (CHS) Longitudinal Longitudinal cohortcohort
Health and Retirement Study (HRS)Health and Retirement Study (HRS) Longitudinal Longitudinal cohortcohort
MIDUS: Midlife in the United MIDUS: Midlife in the United StatesStates
Longitudinal cohort study Main objective: psychosocial, behavioral,
sociodemographic correlates with aging n=7108; ages 24-74 years
MIDUS 1: White (88%), AA (6%), Other (6%) MIDUS 2: White (80%), AA (15%), Other (5%)
2 visits MIDUS 1: 1994-1995; MIDUS 2: 2005-2006 (including
new Milwaukee participants) Recruited from across the U.S. Access: public, download from ICPSR website
MIDUS: Midlife in the United MIDUS: Midlife in the United StatesStates
MIDUS 1 MIDUS II
Project 1 n=7108
Phone/SAQ
Demographics, Psychosocial, Medical history
n=5555
Phone/SAQ
Demographics, Psychosocial, Medical history
Project 2 Daily Diary
n=2022
Project 3 Cognition
n=4518
Project 4 Biomarkers
n=1255
CHS: Cardiovascular Health CHS: Cardiovascular Health StudyStudy
Longitudinal cohort study Main objective: study determinants of
cardiovascular disease n=5888; ages 65+ years; White (81%) AA
(16%) Other (3%) 10 exams
Baseline: 1989; yearly follow-up through 1999.AA cohort initiated study in 1992
Recruited from 4 US communities Access: proposal and approval from CHS
CHS: Cardiovascular Health CHS: Cardiovascular Health StudyStudy
Base yr3 yr4 yr5 yr6 yr7 yr8 yr9 yr10 yr11
Self-rated health
x x x x x x x x x X
Education x
Income x x x x
Depression x x x x x x x x x x
Phlebotomy x x x x x
Nutrition x x
AA cohort
ARIC: Atherosclerosis Risk in ARIC: Atherosclerosis Risk in CommunitiesCommunities
Longitudinal cohort study Main objective: investigate the cause of
atherosclerosis and its clinical outcomes n=15,792; ages 45-64 years; White (73%)
Non-White (27%) 5 visitsBaseline: 1987-1989; Visit 2: 1990-1992; Visit
3: 1993-1995; Visit 4: 1996-1998; Visit 5: 2009-2011
Recruited from 4 US communities Access: proposal and approval from ARIC
CARDIA: Coronary Artery Risk CARDIA: Coronary Artery Risk in Young Adultsin Young Adults
Longitudinal cohort study Main objective: study determinants of subclinical
cardiovascular disease n=5115; ages 18-30 years; White (50%) AA
(50%) 8 visits
Baseline: 1985-1986, Visit 2: 1987-88, Visit 3: 1990-91, Visit 4: 1992-93, Visit 5: 1995-96, Visit 6: 2000-01, Visit 7: 2005-6, Visit 8: 2010-11
Recruited from 4 US communities Access: proposal and approval from CARDIA
MESA: Multi-Ethnic Study of MESA: Multi-Ethnic Study of AtherosclerosisAtherosclerosis
Longitudinal cohort study Main objective: study determinants of subclinical
cardiovascular disease n=6814; ages 45-84 years; White (38%) AA
(28%) Chinese (12%) and Hispanic (22%) 5 exams
Baseline: 2000-2002; Exam 2: 2002-2004; Exam 3: 2004-2005; Exam 4: 2005-2007; Exam 5: 2010-2012
Recruited from 6 US communities Access: proposal and approval from MESA
MESA: Multi-Ethnic Study of MESA: Multi-Ethnic Study of AtherosclerosisAtherosclerosis
Exam 1 Exam 2 Exam 3 Exam 4 Exam 5
N=6814 N=6232 N=5939 N=5704 N=4651
Personal/ Medical Hx/ Psychosocial
X X X X X
Family Hx X
Sleep Hx X X A2500
Residential/neighborhood X
Occupation/employment X X X
Physical Activity X X X X
Food Frequency (Diet) X X
Anthropometry X X X X X
Phlebotomy collection X X X X X
Urine collection X X X X
Genotyping X
Cognitive Function X
Study of Women’s Health Across the Nation (SWAN)
Multi-center, multi-ethnic, community based longitudinal study
Characterize the biological, symptomatic, and psychosocial changes that occur during the MT
Understand the effects of these changes on women's health during and after the MT
SWAN Overview: Cohort
Eligibility aged 42-52 years at least 1 menstrual period in prior 3 mo a member of each site's racial/ethnic group
Participants3,302 women at 7 clinical sites
1550 Caucasian [all sites] 935 African American [Chicago, Pittsburgh, Boston,
Detroit] 286 Hispanic [NJ] 250 Chinese [Davis] 281 Japanese [LA]
SWAN Ancillary Studies
Fat Patterning (Diabetes Risk) Functional Status Hip Strength Mammographic Density Mental Health Phytoestrogens Sleep Subclincial Atherosclerosis (SWAN Heart)
How to get started using DAPPHow to get started using DAPP
Contact :
Dr. Huang ([email protected]) or Dr. Merkin ([email protected])
Dataset Information http://geronet.ucla.edu/dapp
Complete a pre-consultation survey