biosocial applications of sexual identity measures in add health

Social, Behavioral, and Biological Linkages Across the Life Course

Biosocial Applications of Sexual Identity Measures in Add Health

7th Annual CCBAR Workshop October 17, 20113

Carolyn Tucker Halpern

University of North Carolina at Chapel Hill


Outline

• Overview of Add Health design

• Indicators of orientation available in Add Health

• Size of sexual minority population: variation by indicator and interview wave

• Available biomarkers & rationale for selection

• Illustrative research, completed and possibilities

• The Future --- Wave V?


Disabled SampleSaturationSamples

from 16 Schools

Main Sample 200/Community

Ethnic Samples

GeneticSamples

High EducBlack

Cuban

Puerto Rican

Chinese

Cuban

Identical Twins Full SibsFraternal TwinsUnrelated Pairs

in Same HHHalf Sibs

HS

Sampling Frame of Adolescents and Parents N = 100,000+ (100 to 4,000 per pair of schools)

School Sampling Frame = QED

H

Feeder

HS HS HS HS

Feeder Feeder Feeder Feeder


Wave II1996

(88.6%)

Wave III2001-2002

(77.4%)

SchoolAdmin

144

Adolescentsin grades 7-12

20,745

Adolescentsin grades 8-12

14,738

AdultsAged 24-32

15,701

Wave IV2007-08(80.3%)

Wave I1994-1995

(79%)

In-SchoolAdministration

In-HomeAdministration

Students90,118

Partners1,507

Parent17,670

Young AdultsAged 18-26

15,197

SchoolAdmin

128

IIV Study~ 100


Race/Ethnicity N %

Mexico 1,767 8.5

Cuba 508 2.5

Central-South America 647 3.1

Puerto Rico 570 2.8

China 341 1.7

Philippines 643 3.1

Other Asia 601 2.9

Black (Africa/Afro-Caribbean) 4,601 22.2

Non-Hispanic White (Eur/Canada) 10,760 52.0

Native American (non-Hispanic) 248 1.2

Total N 20,686 100.0

Race and Ethnic Diversity in Add Health

Missing on race/ethnicity=59


Indicators of Sexual Orientation in Add Health

• Attraction to same and/or other sex

• Sexual partnerships with same and/or other sex

• Identification/self-labeling


Indicators of Sexual Orientation

• Romantic Attraction to same and/or other sex– Waves I – IV

– Attracted to males?

– Attracted to females?

• Sexual partnerships with same and/or other sex– Waves I -- IV

– Possible number of partners varies across waves

– Type of partner-specific information available varies across waves


Indicators of Sexual Orientation

• Identification/self-labeling (Waves III, IV)– Please choose the description that best fits how you

think about yourself • 100% heterosexual (straight) • mostly heterosexual (straight), but somewhat attracted to

people of your own sex• bisexual that is, attracted to men and women equally • mostly homosexual (gay), but somewhat attracted to

people of the opposite sex• 100% homosexual (gay) • not sexually attracted to either males or females


How large is the sexual minority population in Add Health?

• Estimates vary, depending on:– Eligibility criteria used for analysis samples– Indicator(s) used– Developmental period(s)


Percentages of Males in Attraction Categories

0

2

4

6

8

10

12

14

16

18

Wave I Wave III Wave IV

Interview Wave

We

igh

ted

Pe

rce

nta

ge None

Same

Both

Waves I, III, IV Other sex only: 77.4. 91.1, 95.0%


Waves I, III, IV Other sex: 82.3, 83.3, 89.3%


Waves III & IV: 94% 100% Heterosexual


Waves III, IV: 85%, 80% 100% Heterosexual


Non-exclusively heterosexual identity

112(22.7%)

35(7.8%)

Attracted to the same sex

107(21.2%)

Has had a same-sex partner

187(33.1%)

46(11.0%)

15(3.3%)

4(1.0%)

Sexual Minority Males, Wave 4, n=506 (9.0% of males in analytic sample)

Consistency acrossIndicators


Non-exclusively heterosexual identity

485(30.7%)

26(1.9%)

Attracted to the same sex

238(16.1%)

Has had a same-sex partner

395(26.1%)

215(14.1%)

159(10.6%)

8(0.4%)

Sexual Minority Females, Wave 4, n=1,526 (24.3 % of females in analytic sample)

Consistency acrossIndicators


Percentages of Respondents who Report Same-sex Attraction, Add Health Waves I, II, III

Reporting NNN:

86% of Males82% of Females

N=No; Y=Yes

Halpern CT, Udry JR. Patterns of same- and opposite-sex attraction, romance, and sexual behavior from adolescence to adulthood: A prospective analysis. Society for the Scientific Study of Sexuality Meetings, San Antonio, TX, November 2003


Biomarkers in Add Health


Add Health Choice of Biological Data• Biological states that are reasonably prevalent in the

general population of youth & young adults

• Biological states and process theoretically and/or empirically linked to future health

• Measures that can characterize those processes

• Feasible for a large scale, national field study

• Valid and reliable

• Appropriate for longitudinal designs

• Non-invasive, cost-efficient, practical


Domain, Marker & Biospecimen -- Wave IVDomain Marker Biospecimen

Cardiovascular blood pressure, pulse Blood pressure monitor

Metabolic processes lipids, glucose, glycosylated hemoglobin (HbA1c)

Dried Blood Spots

Immune function EBV Dried Blood Spots

Inflammatory processes

CRP Dried Blood Spots

Genetic 10 candidate loci Saliva

HPA Axis cortisol (pretest only) Saliva


Biospecimen Participation

• 99% Height, weight, waist (all Waves)

• 99% Blood pressure (Wave IV)

• 96% Saliva (DNA Wave IV; 78% archived)

• 95% Saliva (HIV; Wave III)

• 94% Blood Spots (Wave IV; 76% archived)

• 92% Urine (STIs; Wave III)


Intra-Individual Variation (IIV) Study• Repeat collection of biomarkers on the same 100 individuals

over a short interval to estimate reliability of measures.

• Randomly selected ½ IIV cases in pretest and ½ in main study.

• Interview IIV respondents twice, 1-2 weeks apart– Visit 1: full interview + biomarkers– Visit 2: abbreviated interview + biomarkers

• Process the biomarkers (labs and technicians masked)

• Compute the intra-class correlation (ICC) as a measure of reliability

• Use reliability estimates to monitor biomarker data quality and correct for measurement error.


Reliability of Biomarkers in Add Health Wave IV

Type Measure ICC (95% CI)

Anthropometric Weight 1.00 (1.00-1.00)

Height 0.98 (0.98-0.99)

BMI 0.99 (0.99-1.00)

Waist 0.98 (0.97-0.99)

Cardiovascular DBP 0.81 (0.74-0.88)

SBP 0.68 (0.57-0.79)

PR 0.47 (0.31-0.63)

Metabolic HbA1C 0.97 (0.96-0.98)

Glucose (non-fasting) 0.39 (0.21-0.58)

Inflammatory hsCRP 0.70 (0.59-0.81)

Immune EBV 0.97 (0.96-0.98)


Behavioral, Social, Contextual Content Across WavesWaves I, II

Demographic

Family, siblings, friends

Education, work

Physical and mental health

Daily activities and sleep

Relationships

Sexual, & fertility histories

Substance use

Delinquency and violence

Attitudes, religion

Economics, expectations

Psychological, personality

Wave III

Demographic


Education, work, military



Relationships


Substance use

Involvmt w/criminal justice sys

Attitudes, religion


Psychological, personality

Children and parenting

Civic participation

Gambling

Mentoring

Wave IV

Demographic


Educ, work, military (records)



Relationships


Substance use and abuse

Involvmt w/criminal justice sys

Work attitudes and chars, relig


Big 5 Personality, stressors

Children and parenting

Civic participation

Cognitive function

Psychosocial factors


Illustrative Research

• Examples to date

• Future possibilities


Sexual Minority Definitions

• “Any 1 indicator:” Respondents endorsing at least one of the indicators of minority status

• “All 3 indicators:” Respondents endorsing all three indicators

• “Heterosexual majority:” Respondents endorsing none of the three indicators

Strutz K, Herring AH, Halpern CT. Disparities in health status and health care access for young adult sexual minorities in the United States. Under review.


Health Disparities in Young Adulthood Based on Self-Report

• Numerous, especially for females

• Evident for “any 1 indicator” and “all 3” indicators

• Examples– Overall self-rated health– Depression, anxiety disorder– STI diagnoses– Health care access & foregone care

• Similar patterns regardless of concordance/discordance in indicators



Sexual Minority & Majority Females: BMI

0

10

20

30

40

50

Minority Majority

We

igh

ted

Pe

rce

nta

ge

NormalOverweightObese



Strutz K, Herring AH, Halpern CT. Disparities in health status and health care accessfor young adult sexual minorities in the United States. Under review.


Sexual Identity & CVD Markers in Young Adulthood (Wave IV)

• Compared with heterosexuals, in adjusted models:

– Gay/bisexual identified men had elevated:• Diastolic blood pressure (Mean 84.06 vs 81.62 mmhg)• Pulse rate (mean 75.64 vs 72.48)• CRP (mean 2.16 vs 2.07 mg/L)

– Lesbian/bisexual identified women had lower:• CRP (2.28 vs 2.53 mg/L)• Despite more CVD risk factors

• If replicated, differential timing in physical evidence of CVD risk

Hatzenbuehler ML, McLaughlin, KA, Slopen N. Sexual Orientation Disparities in Cardiovascular Biomarkers Among Young Adults. Am J Prev Med 2013;44(6):612–621


Capitalizing on Add Health to Better Understand Pathways to Health

• Extensive, multilevel social, psychological, behavioral, environmental, and biological data

• Longitudinal design, beginning in early adolescence, allows examination of timing, duration, and accumulated impacts of social and environmental factors

• Map pathways leading to differences in mental and physical health, and consequences across the life course


Genetic Data

• Diverse phenotypic data, coupled with extensive social and contextual data, offer many opportunities to test gene by environment (GxE) interactions

• Candidate genes in the dopamine and serotonin pathways have been genotyped

• Genome-wide genotyping ongoing for samples provided by 12,000 respondents who consented to archive their specimens for further testing


Social Disadvantage and Health

• Exposure to social disadvantage early in life associated with poor health in later adulthood.

• Less attention to adolescent and young adult stages of life course.– Seek autonomy in choosing their own environments,

health behaviors, habits and future lifestyles.

– Physical, physiological, and neurological changes linked to puberty make adolescents especially receptive to their broadening environments.


Neighborhood Disadvantage & Blood Pressure

1) Levels: Exposure to higher levels of neigh disadvantage associated with greater hypertension risk at any point in time;

2) Timing: Exposure during sensitive period of adolescence more detrimental for subsequent health than transition to adulthood;

3) Duration: Longer durations of neigh disadvantage over time associated with greater hypertension risk;

4) Mobility: Those who move out of disadvantaged neighs will experience better health than those who remain.

Gerkin K, Harris KM. 2013 Population Association of America Presentation.


Findings

• Social disadvantage early in life can leave a biological imprint that may affect later adult health.

• Adolescence is a sensitive period

– Neighborhood disadvantage experienced during adolescence more detrimental for future blood pressure than during transition to adulthood.

• Cumulative effects also important, but adolescence seems to anchor these effects and likely set the health trajectory into adulthood.

• Associations did not differ significantly by race or sex

• Extension to sexual minorities?


Future Possibilities: Add Health Wave V Program Project

• Chronic conditions are occurring at increasingly younger ages in the US

• Add Health cohort is entering the ages when chronic disease will explode

• Life stages of adolescence and the transition to adulthood are virtually ignored in disease models, and yet these are the stages when young people begin to choose their environments, health behaviors, habits and future lifestyles

• Life stages especially relevant to sexuality & sexual identity, hypotheses related to minority stress


Wave V Scientific Objective

• Trace the additive and interactive social, biological, genetic, and behavioral pathways that lead to chronic disease by– Linking adult health and disease risk to physical and social

exposures that occur during

• Gestation

• Childhood

• Adolescence

• Transition to early adulthood

• Young adulthood


Wave V Interview 2015-2018

• Original Wave I respondents who will be moving through their 4th decade of life (31-42 years).

• Collect the following data:– survey data reflecting both longitudinal and new

information;

– longitudinal and new biological data and specimens;

– geographic locations for longitudinal spatial data;

– and consent to obtain birth records of Add Health respondents born in a subset of states.


Wave V: Biological data

• Repeat measures of biomarkers that indicate change and onset of chronic disease:– anthropometrics– blood pressure – Whole blood assays of:

• Inflammation• Lipids• Glucose• Glycosylated hemoglobin

• New biomarkers of kidney disease:• Creatinine• Cystatin C


Add Health Project Team

• Kathleen Mullan Harris, PI & Director

• Carolyn Tucker Halpern, Co-I & Deputy Director

• Eric Whitsel, Co-PI IV Biology Core

• Jon Hussey, Co-investigator

• Joyce Tabor, Add Health Data Manager

• Ley Killeya-Jones, Add Health Project Manager

• Sarah Dean, Assistant Project Manager


Add Health Co-Funders• National Institute of Child Health and Human Development*• National Cancer Institute*• National Center for Health Statistics, Centers for Disease Control and Prevention, DHHS • National Center for Injury Prevention and Control, Centers for Disease Control and Prevention, DHHS* • National Center for Minority Health and Health Disparities*• National Institute of Allergy and Infectious Diseases*• National Institute of Deafness and Other Communication Disorders* • National Institute of General Medical Sciences • National Institute of Mental Health • National Institute of Nursing Research*• National Institute on Aging*• National Institute on Alcohol Abuse and Alcoholism*• National Institute on Drug Abuse* • National Science Foundation*• Office of AIDS Research, NIH*• Office of the Assistant Secretary for Planning and Evaluation, DHHS*• Office of Behavioral and Social Sciences Research, NIH*• Office of the Director, NIH • Office of Minority Health, Centers for Disease Control and Prevention, DHHS • Office of Minority Health, Office of Public Health and Science, DHHS• Office of Population Affairs, DHHS*• Office of Research on Women's Health, NIH*

*Wave 4 co-fundersData made available to more than 4


Add Health Web Page

http://www.cpc.unc.edu/projects/addhealth

• Online code books

• User guides to inform data analysis

• Bibliography of Add Health publications

• Information about the bi-annual Add Health Users Conference in Washington DC

• Information about data access


Questions?

biosocial applications of sexual identity measures in add health

Documents