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Social disparities in maternal, child, and reproductive health


... child, adolescent, and reproductive health Local expertise available to expand National and international networks Core faculty Paula Braveman Paul Newacheck ... – PowerPoint PPT presentation

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Title: Social disparities in maternal, child, and reproductive health

Social disparities in maternal, child, and
reproductive health
  • Work of the Center on Social Disparities in

Healthy People 2010
  • Achieving Equity The Healthy People
  • Healthy People 2010 is firmly dedicated to the
    principle that regardless of age, gender, race,
    ethnicity, income, education, geographic
    location, disability, and sexual orientation
    every person deserves equal access tohealth
    care systems
  • HP2010 Vol. 1, p. 16

Healthy People 2010
  • Achieving Equity The Healthy People
  • HP 2010 recognizes that communities, States, and
    national organizations will need to take a
    multidisciplinary approach to achieving health
    equity that involves improving health, education,
    housing, labor, justice, transportation,
    agriculture, and the environment. HP2010 Vol. 1,
    p. 16

Goals of the Center on Social Disparities in
  • Address HP 2010 objectives
  • Address the need for better information and
    better use of existing information to guide
    efforts to reduce disparities
  • Studies, ongoing monitoring, dissemination
    inform policies to close gaps
  • Training
  • U.S. focus with international links

Social disparities in health
  • Health disparities
  • Health differences between more and less
    advantaged social groups
  • underlying advantage, position in social
  • E.g. groups specified in HP 2010 socioeconomic,
    racial/ethnic, geographic, age, disability,
    sexual orientation, and other

Why care about health disparities?
  • Ethical principles justice
  • Consonant with human rights principles
  • non-discrimination
  • rights to health/living standards
  • Disparities that put already disadvantaged groups
    at further disadvantage on health
  • Equal opportunity to be healthy implies concern
    for disparities in health and its social

Why a center at UCSF?
  • Two decades of work on disparities by core
    faculty (research and informing policy)
  • Leadership in US and internationally in placing
    health equity on agenda, developing methods,
    contributing to knowledge base
  • Core faculty expertise on maternal, infant,
    child, adolescent, and reproductive health
  • Local expertise available to expand
  • National and international networks

Core faculty
  • Paula Braveman
  • Paul Newacheck
  • Catherine Cubbin
  • Susan Egerter
  • Kristen Marchi
  • Claire Brindis
  • Dana Hughes
  • Geraldine Oliva
  • UCSF Departments of Family and Community Medicine
    and Pediatrics
  • UCSF Institute for Health Policy Studies

Affiliated faculty, e.g.
  • Art Reingold
  • Sylvia Guendelman
  • Len Syme
  • Marilyn Winkleby
  • Eliseo Perez-Stable
  • Eugene Washington
  • Nancy Adler
  • Ed Yelin
  • UC Berkeley School of Public Health
  • Stanford University
  • UCSF

Current activities
  • MIHA and PRAMS develop, apply, and disseminate
    methods for research and ongoing state-level
    monitoring of disparities
  • NHIS (1984-01) trends in child and adolescent
    health disparities methods for ongoing
  • Add Health individual, household, and contextual
    factors in disparities in adolescent reproductive
    health behaviors
  • Compare trends in health-related spending on
    children vs adults

Early products
  • Methods for research and ongoing monitoring
  • Measuring SES PH Reports 2001/2002
  • Monitoring health equity -- under review, JHNP
  • Model for state-level monitoring--Kaiser Policy
    Brief, in press submitting paper to AJPH
  • Inform interventions
  • Kaiser Policy Brief (3 outcomes)
  • Analyses re LBW/PTB
  • Cubbin et al., 2002 MCHJ - unintended
  • Under review Heck et al., breastfeeding (AJPM)
    Chung et al., sleep position (Amb Peds)

Measuring SES in studies of racial/ethnic
disparities Examples from maternal and infant
  • Paula Braveman, Catherine Cubbin, Kristen Marchi,
    Susan Egerter, Gilberto Chavez
  • Published in Public Health Reports during 2002
  • Special Issue on Health Disparities

  • Guide how SES is measured in studies of
    racial/ethnic disparities in LBW, delayed/no
    prenatal care, unintended childbearing, and
    breastfeeding intention
  • Focus on income and education, the measures used
    most in US
  • Address general public health audience

  • SES used throughout health literature but
    rarely defined
  • Diverse measures used without justifying why
    selected, how and when measured, or how
  • Conclusions about role of SES can vary based on

What do we mean by SES?
  • Socioeconomic status/position
  • Wealth-- and/or the associated power and social
  • Income, accumulated economic assets (wealth)
  • Education (prestige, wealth, power)
  • Occupation (power, prestige, wealth)
  • Multidimensional construct -- yet health studies
    often use a single SES measure

Without adequate SES measurement...
  • Cant assess role of SES in health or its
    contribution to other associations, e.g., between
    race/ethnicity and health
  • Racial/ethnic disparities often interpreted to
    reflect biological or cultural differences
    without adequately considering SES role

  • Large (n gt 10,000) statewide representative
    face-to-face postpartum survey in random sample
    of 19 California delivery hospitals, 1994-95
  • English and Spanish
  • Linked with birth certificates and census data
  • Sample characteristics similar to statewide

  • SES dimensions different general constructs
    income/wealth, education, occupation
  • Ways of specifying SES constructs e.g.
  • income income as a of poverty level income
    per family size (more specific construct)
  • continuous vs categorical (and how categorized)
  • level maternal, paternal, household, community
  • timing in life cycle

Individual-/household-level SES measures Income
  • Before-tax family income
  • of federal poverty level in 5 categories
  • continuous (log income in dollars)
  • quartiles based on continuous income
  • continuous income per family size
  • quartiles based on income per family size
  • Information missing for only 5

Educational attainment
  • Household education schooling of the most
    educated parent
  • Schooling in years (maternal, paternal,
  • source birth certificate
  • Maternal, paternal, household schooling in
  • source maternal level from survey
  • paternal level estimated from years in birth

  • Social construct
  • Region of family origin and/or associated
    superficial physical characteristics, which could
    influence experiences and responses
  • Mutually exclusive categories
  • African American
  • Asian/Pacific Islander
  • European American
  • Latina

Outcome measures
  • LBW
  • delayed or no prenatal care
  • unintended childbearing (not trying)
  • Not intending to breastfeed when interviewed in
    delivery hospital

Other variables
  • Age (years) and parity (1, 2-4, 5 births)
  • could confound associations between SES measures
    and health outcomes
  • But age and parity could be on causal pathway
    between an SES measure and a health outcome
  • so their inclusion could diminish observed
    association and mislead on role of SES

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Unadjusted associations SES?outcome and
  • Depended on the SES measure, outcome, and
    racial/ethnic group
  • At least one specification of both income and
    education were associated with each outcome
  • Relative odds significance varied by SES
    measure, outcome, and racial/ethnic group

Adjusted associations varied ...
  • Race/ethnicity ? outcomes
  • by SES measure (dimension, specification)
  • by outcome
  • SES ? outcomes
  • by SES measure (dimension, specification)
  • by outcome
  • by race/ethnicity (caution on this as a
  • All models adjusted for age, parity, and either
    SES or race/ethnicity

Adjusted1 associations between SES not
intending to breastfeed
1All models adjusted for age, parity, and
racial/ethnic group plt0.05, plt0.01, plt0.001
Adjusted1 associations between racial/ethnic
group and delayed prenatal care
1All models adjusted for age and parity. plt0.05,
plt0.01, plt0.001.
Findings dimensions of SES
  • Income and education correlations
  • Moderate overall lower among women of color
    (especially Latinas)
  • Education important SES measure but not
    acceptable income proxy
  • Using education as income proxy differentially
    misclassifies women of color

Findings how SES measures are specified
  • Correlations among different specifications of
    income generally strong overall and within
    racial/ethnic groups
  • Maternal education from survey and birth
    certificate strongly correlated
  • Only moderate correlations between maternal and
    paternal education -- ideally examine both

Conclusions overall
  • Researchers could reach different conclusions
    about roles of both SES and race/ethnicity,
    based on SES measures, outcomes, and groups
  • Both the dimension of SES (e.g., income or
    education) and how its specified matter

  • Only current income and education and
    individual/household level
  • Control for age and parity could control for
    intermediate steps on pathway
  • Race/ethnicity, age, and parity probably reflect
    unmeasured SES differences
  • Only English and Spanish
  • One state (but 1/7 US births)

Practical implications
  • Explore different SES measures overall and in
  • different specifications of income may not matter
  • education from birth certificates may be OK
  • Acknowledge limited dimensions and specifications
  • Consider how conclusions could vary
  • Choose measures based on pathways

Practical implications
  • Show SES was measured adequately before making
    claims about racial/ethnic or socioeconomic
    disparities in health
  • Concluding a racial/ethnic disparity is
    independent of SES would require exhaustive
    measurement of all SES factors relevant to all
    plausible pathways -- which is impossible

Measuring SES in studies of racial/ethnic
  • Concepts arent new
  • Contribution is to illustrate the concepts
  • for the general health researcher community
  • using large, population-based, diverse sample

Another CSDH effort
  • Social disparities in maternal and infant health
    a model for state-level monitoring
  • Braveman, Marchi, Egerter, Cubbin
  • Supported by Kaiser Family Foundation and CDC/DRH
  • Report for policy-makers and a scientific paper
    on methods (submitting to AJPH)

Model state-level report on disparities
  • Socioeconomic and racial/ethnic disparities in
  • unintended childbearing
  • delayed/no prenatal care
  • not intending to breastfeed
  • Statewide postpartum surveys linked with birth
    certificates and census data
  • California 1999-2001 and 1994-95 (n10,000 each)

Model state-level report on disparities goals
and overview
  • Measure gaps over time to help evaluate policies
  • Simple and complex measures of gap size
  • Identify groups to target
  • Outcome rates by income, education, neighborhood
    poverty, and race/ethnicity
  • Relative risks and rate differences compared to
    the most advantaged subgroup
  • Suggest issues to intervene on
  • Whole sample and subgroup multivariate analyses
  • Prevalence of significant risk factors in
    at-risk groups

4 primary social variables
  • Family income as poverty status 0-100, 101-200,
    201-300, 301-400, gt400 poverty
  • Maternal education ltHS, HS/GED, some college,
    college graduate
  • Neighborhood poverty gt20 vs lt20 poor in census
    tract (1990 or 2000)
  • Racial/ethnic group

Racial/ethnic groups
  • African American or Black
  • Asian/Pacific Islander (API)
  • European /Middle Eastern or White (reference)
  • Latina foreign-born
  • Latina US-born
  • Native American/Alaskan Native/American Indian
    (too few to analyze separately)

Multivariate analyses to suggest issues to
address delayed/no prenatal care
  • 4 primary social variables covariates
  • paternal education
  • age, parity, marital status, language
  • 1st-trimester insurance
  • regular source of pre-pregnancy care
  • unintended pregnancy or ambivalence
  • importance of care to others
  • sense of control/mastery
  • smoking/drinking during pregnancy
  • (2001 transportation, child care, other

A few results implications Measuring the gaps
over time
  • Most subgroups improved over time in absolute
  • But relative disparities didnt improve, because
    better-off groups improved as much/more
  • Similar pattern by income, education,
    neighborhood poverty, and racial/ethnic group,
    for all 3 outcomes
  • Need more intensive targeted efforts to reduce

Who to target (at-risk groups) to reduce
delayed/no prenatal care gaps
  • Income lt 300 of poverty
  • No college degree
  • Women in poor neighborhoods
  • All racial/ethnic groups except European
  • Need to reach wider segments of population not
    just poor, uneducated

What to intervene on in the at-risk groups?
  • No insurance coverage in first-trimester
  • prevalence 12-33 OR 4-5
  • Unintended pregnancy and/or ambivalence
  • prevalences 40-60 20-31 ORs 1.3-2
  • Prenatal care not very important to others
  • prevalence 8-10, OR 2-3
  • Transportation and childcare problems not

What to intervene on to reduce delayed/no care
gaps overall
  • Income (but not education) was still significant
    and strong (OR 3) after full adjustment
  • Address underlying socioeconomic disparities
  • Call attention to health disparities to support
    actions in other sectors
  • Be aware of limits of health-sector interventions
  • Racial/ethnic disparities (except for APIs)
  • Greatly reduced by socioeconomic variables
  • Eliminated in final model

  • Only English and Spanish
  • 2 time points
  • Survey methods not identical
  • Survey questions not always identical
  • Main value
  • develop replicable methods
  • identify current at-risk groups and their
  • NOT definitive assertions about change over time

Recommendations re monitoring approach
  • Examine outcome rates and rate differences by
    socioeconomic and racial/ethnic groups
  • Examine relative risks and rate differences
    compared to the a priori most advantaged group
  • Identify important risk factors overall and in
    at-risk groups check prevalence
  • Simple and useful
  • Is progress being made to close gaps?
  • Who to target on which outcomes and issues?

Do you REALLY need multiple SES measures for
policy-oriented monitoring?
  • Important a priori and per evidence
  • Different conclusions about race/ethnicity (and
    SES) if use income vs education
  • Examine at least 2 dimensions of SES (e.g.,
    income and education)
  • For policy-makers, dont display gt 1 SES measure
    unless different
  • Include in surveys

A model for state-level monitoring of
disparities Big challenges
  • Balancing rigor and depth against
    generalizability and sustainability
  • What states could do with PRAMS surveys, birth
    certificates, and census data
  • Numbers/statistical power concerns
  • Sound bites vs science
  • How much information and how to express it
  • Expressing caveats and limitations

  • Report illustrates approach to ongoing monitoring
    of health disparities that could inform policy to
    reduce disparities
  • Despite challenges, key components are feasible
    for most state health departments
  • Crux use a disparities lens
  • Disaggregate and compare to most advantaged
  • Health of most advantaged tells whats possible
    for all

The Center on Social Disparities in Health year
1-2 activities
  • Complete first phase work with MIHA and 7 PRAMS
    states NHIS Add Health Age equity
  • More publications and presentations
  • Web-site
  • Seminar series
  • Health Disparities Scholars
  • Funded by Kellogg Foundation
  • Minority Post-Doc Scholars
  • Harvard, U Michigan, Morgan State, UCSF

Developing proposals to study mechanisms
  • Study the roles of past SES and racial
    discrimination in birth outcomes
  • Using NLSY
  • Early stages of designing a large prospective
    study with primary data collection

Next steps Seek support to expand work
  • Replicate work in more PRAMS states, more
    outcomes, contextual analyses, collaborate with
    in-state researchers
  • More time points in NHIS data to examine trends
  • Analyze trends in social disparities in
  • reproductive health outcomes using NSFG
  • child immunizations using NIS
  • Disparities in near-miss maternal mortality
  • A. Foster-Rosales

Seek support for Fact sheets/brief reports on
  • State-specific, national
  • On-line, paper
  • Wide range of indicators and issues, including
    trends over time
  • Use all appropriate data sources for ongoing
    monitoring of trends, e.g. PRAMS, vital stats,
  • To draw attention and stimulate debate

Other wish-list items
  • Adapt technical materials for MCH data
    capacity-building to focus on disparities
  • Provide technical consultation to health
    departments to monitor disparities
  • Resource center
  • Public forums in states build on European
    experience with consensus-building around social
    inequalities in health

And more on the wish list
  • Collaborate with CDC/health department
    researchers on emerging concerns
  • Range of outcomes, e.g., pediatric asthma
  • Primary issue is disparities vs specific outcome
  • Eventually expand to adult health
  • International work
  • Global Equity Gauge initiative (Rockefeller,
    Swedish government)
  • Collaborate with CDC researchers to analyze MCH
    surveys from low-income countries

The current environment
  • Socioeconomic disparities and safety net holes
    likely to widen
  • Reducing disparities requires systematically
    targeted approach because the most advantaged
    tend to improve more
  • Some results suggest current interventions
    unlikely to succeed
  • Scarce resources require focused approach

The Center on Social Disparities in Health in the
current environment
  • Keep health disparities on the agenda
  • States, federal
  • Assess how gaps change over time in relation to
    policies in all sectors
  • Inform programs and policies to be more effective
    in reducing disparities
  • Transfer skills to health departments/other