University of Delaware August 7 2009 Presentation to accept 2008 George A Miller Award for outstanding article across specialty areas Division 1 APA Social Class Disparities in Health A Vexing Puzzle with a Surprising Answer ID: 557322
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Linda S. Gottfredson, Professor
University of DelawareAugust 7, 2009Presentation to accept 2008 George A. Miller Award for outstanding article across specialty areas, Division 1, APA
Social Class Disparities in Health: A Vexing Puzzle with a Surprising Answer?
American Psychological AssociationSlide2
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What are “disparities”? What’s the vexing puzzle?
Is human cognitive diversity key to solving it?If yes, so what?AgendaAnswers: All surprisingSlide3
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What are “disparities”?
Why such a vexing puzzle?Is human cognitive diversity the key to solving it?If yes, so what?Agenda ExamplesSlide4
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“Disparity” =
group differences on health outcome X
“Explaining”
between
-group variation
Means, rates, etc.
16 yrs
12 yrs
8 yrs
Typical
indicators of socioeconomic status (SES)
Years education
Occupational status
Income
But not clear what they really represent or have in common
?Slide5
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Typical health disparities by education; in all races & sexes:
% of non-ill 51-year-olds expected to have this chronic illness by age 63(Hayward et al, 2000)
HypertensionDiabetes whiteCOPD blackCancer
MenWomen
%
YearsSlide6
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Typical health disparities by education; in all races & sexes:
% of non-ill 51-year-olds expected to have this chronic illness by age 63(Hayward et al, 2000)
HypertensionDiabetes whiteCOPD blackCancer
MenWomen
%
Fewer health problems in higher social classes (educ, occup, or $)
True for all races, sexes Exceptions are rare (e.g., cancer morbidity)
YearsSlide7
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Disparities in health behavior by education; all races & sexes:
% who smoke, 2006 (age adjusted)(CDC, Health in the United States, 2008, Table 64)
%Slide8
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Typical course of behavior disparities over time, by education: % who smoke, 1974-2006, ages 25+
(age-adjusted) (CDC, Health in the United States, 2008, Table 64)
16.520.6% better, gap bigger
%Slide9
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Many families of health disparities
HEALTH HABITS
MORTALITY
KNOWLEDGE
CHRONIC ILLNESSES
INJURIES
INFECTIOUS DISEASES
ADHERENCESlide10
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Many families of health disparities
HEALTH HABITS
MORTALITY
KNOWLEDGE
CHRONIC ILLNESSES
INJURIES
INFECTIOUS DISEASES
ADHERENCE
Outcomes for
populationsSlide11
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11
a
bcdd
fg
This is not about individual differences in health outcomes
Not “explaining”
within-group variation
Within-group and between-group variance may arise from
different
mix of causes
Often misunderstood!Slide12
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Study of populations aided by epidemiological approach
OutcomesMeans, rates, relative risk, odds ratios for groups
Predictors—classic trioExposure to hazards, help (probability)Host (susceptibility)Vector (virulence, burden)Slide13
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Study of populations aided by epidemiological approach
OutcomesMeans, rates, relative risk, odds ratios for groups Predictors—classic trioExposure (probability)
Host (susceptibility)Vector (virulence, burden)
Missing 2/3
Current focus of SES disparities researchSlide14
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What are “disparities”?
Why such a vexing puzzle? But first, what exactly are we trying to explain?StatisticallySubstantively Is human cognitive diversity the key to solving it?If yes, so what?Agenda
IllustrationSlide15
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Illustration with 2 disparities
# 1
# 2Slide16
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16
1
2345Social class groupings
Health(groupmeanor rate)
Each disparity is a gradient, with a slope (ß)
Statistically…
# 1
ß
1Slide17
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17
1
2345
Social class groupings
Health(groupmeanor rate)
Each disparity is a gradient, with a slope
Statistically…
# 2
# 1
ß
1Slide18
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18
1
2345Social class groupings
Health(groupmeanor rate)
Each disparity is a gradient, with a slope
Statistically…
# 2
# 1
ß
1
ß
2Slide19
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1
2345Social class groupingsHealth
(groupmeanor rate)
Many families of health gradients (slopes):
Morbidity, mortality, knowledge, prevention, adherence, etc.
rare
ß
1
ß
8
ß
7
-ß
6
ß
5
ß
4
ß
3
ß
2Slide20
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So, to explain SES disparities:
Explain the distribution of co-evolving gradients (ß, their standardized slopes)ß ß ßßßß3ß8
ßßßßß4
ß
ßß2
ß6
ß
ß
ß
ß
ß
ß
ß
ß
7
ß
ß
ß
ß
ß
2
ß
ß
1
ß
0
Slopes (steepness) of gradients
negative
positive
Common policy goal : All
β
= 0 Slide21
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What are “disparities”?
Why such a vexing puzzle? But first, what exactly are we trying to explain?StatisticallySubstantively Is human cognitive diversity the key to solving it?If yes, so what?Agenda
ExamplesSlide22
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General puzzle
: Health disparities are
too general for SES mechanisms to explain
They are pervasive, persistent and monotonic regardless of time, place, health system, disease, and behavior. Why??Slide23
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Exposure hypothesis 1:
“Wealth = health” (can afford good care)health
wealth
No leveling off when resources are more than sufficient
REJECTED—Puzzle greater!Slide24
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Experimental test of exposure hypothesis 1:
Equalize access to care equalize health Time 1: Unequal access Time 2: After equal access (free care)
Health disparities
grow
, not shrink
FAILED—Puzzle greater!
E.g., UK in 1950sSlide25
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Experimental test of exposure hypothesis 2:
Unequal education unequal health Time 1: Unequal knowledge of signs and symptoms Time 2: After public health campaign
Knowledge disparities
grow
, not shrink
FAILED—Puzzle greater!Slide26
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Or disparities even reverse direction with new screening tests
(e.g., death rates from breast cancer) Negative disparities for Outcome X at Time 1 Positive disparities for Outcome X at Time 2
ß
-ß
More educated women have
higher
death rates
Slide27
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Access matters, but so does utilization
Even if equal access
Unequal use & misuse
Mammograms
Adherence to treatment
Seat belt use
Etc.
“Health literacy”Slide28
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1
2345Social class groupingsHealth
(groupmeanor rate)
Summary of puzzle
rare
Exposure can’t explain why gradients:
Virtually never = zero
Virtually always positive
All monotonic (~linear)
For ~all health outcomes & behaviors
Steepen when resources equalized
What levers the gradients up or
down?
Can’t be material resources.Slide29
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So, the field seeking more “fundamental cause” of SES disparities
This cause must: be pervasive & domain-general have linear (monotonic) effectsnot be materialMost popular suspect = inequality itselfrelative deprivation chronic psychological stress damaging physiological process: “allostatic load” Stress important, but can’t explain:why adding resources increases disparitiesdisparities in non-biological outcomes Slide30
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2006
2003-2005
Biological mechanismsInvolved hereBut not here
First, physical illness is only one cause of injury & death: Causes of death, males by age(CDC, Health data interactive)
Common theme—all are preventableSlide31
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Example: Unintentional (“accidental”) death Odds ratios by neighborhood income
(1980-86)
20 per 100,00021Reference group Odds = % affected Odds ratio = Odds for Group 1_______ % not Odds for reference group
Just differential exposure??Slide32
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Selected causes of “motor vehicle traffic” death, by neighborhood income/capita
(1980-86)(Baker, O’Neill, Ginsburg, & Li, 1992)
203.215.20
.18
.26
elderly
adult men
young men
toddlers
young men
young men
Primarily:
Rate per 100,000Slide33
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Selected “other” causes of unintentional death, by neighborhood income/capita
(1980-86) (Baker, O’Neill, Ginsburg, & Li, 1992)
20.02.60.04
2.30
.06
.38
.78
Odds ratio
Deaths per 100,000
.12
infants, elderly
rises with age
young men
toddlers, elderly
young men
young men
infants, elderly
Infants
Primarily:
Self-exposure
Differential biological
susceptivitySlide34
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PreventionIt’s our job It’s daily, unrelenting, life-long (hazards are everywhere)It’s complex
It’s a highly cognitive, multi-step, active processSpot & avoid hazardsRecognize signs of system veering out of control
Take action to regain controlLimit progression of illness/accident or damage it doesAdhere to treatmentLearn from experience to adjust future behaviorThe common mechanism for illness and injury?
Passive-patient model is dead wrongSlide35
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What are “disparities”?
Why such a vexing puzzle?Is human cognitive diversity the key?If yes, so what?Agenda IQ/
gSlide36
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Alternative hypothesis for disparities in health:
“Intelligence (g) differences are the “fundamental cause” Two g–based levers ratchet up gradients* Bigger IQ differences (people) Heavier cognitive load (tasks) susceptibility burden
*
Based on extensive research in education & employmentSlide37
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Gaps in IQ/
g (cognitive susceptibility-efficiency)Heaviercognitiveload (g loadingof tasks)
Heavier
cognitiveload (g loading
of tasks)
ßß
ß
ß
ß
ß
ß
ß
ß
ß
ß
ß
ß
Translated: A hypothesis about gradientsSlide38
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Background fact #1
Great cognitive diversity is a biological fact about all populations70 75 80 85 90 95 100 105 110 115 120 125 130
IQSlide39
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Background fact #2IQ
≈ g (general mental ability factor)g is no longer a black boxg is a domain-general facility for learning, reasoning, spotting & solving novel problemsHigher g reduces susceptibility to errorGives bigger edge as task complexity (cognitive load) increasesAllows one to exploit resources more fully & effectively (e.g., classroom instruction, medical treatments)Slide40
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Background fact #2IQ
≈ g (general mental ability factor)g is no longer a black boxg is a domain-general facility for learning, reasoning, spotting & solving novel problemsHigher g reduces susceptibility to errorGives bigger edge as task complexity (cognitive load) increasesAllows one to exploit resources more fully & effectively (e.g., classroom instruction, medical treatments)Slide41
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Gives an edge in planning; anticipating problems Slide42
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Background fact #3
Mean IQs differ by occupation level and years education70 75 80 85 90 95 100 105 110 115 120 125 130
0-7
8
9-11
12
13-15
16+
Unskilled
Semiskilled
Skilled
Manager, Cler, Sales
Professional & Tech
Occupation:
Years education:
WAIS-R IQ (mean
+
1 SD), US adults ages 16-74
IQSlide43
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Background fact #4:
Some SES indicators correlate more with IQ .8 Standardized academic achievement .6 Years education.5 Occupation level.3-.4 Income
(prior)
IQ
All
moderately
heritable,
& overlap
genetically
with IQSlide44
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.8
Literacy.8 Standardized academic achievement .6 Years education.5 Occupation level
.3-.4 Income
(prior)
IQ
Excellent
Good
Weak
Background fact #4:
Conversely, some are better surrogates for IQ
Better surrogates for
g
s
how larger
health disparities Slide45
Better surrogates for
g
show larger
health disparities(steeper gradients)45income
occupation
education
“literacy”Slide46
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.8
Literacy.8 Standardized academic achievement .6 Years education.5 Occupation level.3-.4 Income
Excellent
Good
Weak
Background fact #4:
Conversely, some are better surrogates for IQ
(prior)
IQ
Cannot “control” for SES without
controlling away much
of (genetic)
g
itselfSlide47
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Gaps small when learning & reasoning demands are light Gaps large when learning & reasoning demands are heavy
Common in schools & jobs
Background fact #5:
Task complexity increases gaps in performanceSlide48
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Gaps small when learning & reasoning demands are light Gaps large when learning & reasoning demands are heavy
Common in schools & jobs
Background fact #5:
Task complexity increases gaps in performance
Cognitive load brings out differences in cognitive susceptibilitySlide49
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New technologies make life increasingly
complex, which puts yet higher premium on gPreventive & curative care becoming increasing complexSlide50
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Background fact #6:
People differ more than often assumed U.S. Dept of Education 1993 survey of adult functional literacy (nationally representative sample, ages 16+, N=26,091)NALS Level
% pop.
Simulated Everyday Tasks
5
3%
Use calculator to determine cost of carpet for a room
Use table of information to compare 2 credit cards
4
17%
Use eligibility pamphlet to calculate SSI benefits
Explain difference between 2 types of employee benefits
3
31%
Calculate miles per gallon from mileage record chart
Write brief letter explaining error on credit card bill
2
27%
Determine difference in price between 2 show tickets
Locate intersection on street map
1
22%
Total bank deposit entry
Locate expiration date on driver’s license
Routinely able to perform tasks only up to this level of difficultySlide51
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51
NALS Level
% pop.
Simulated Everyday Tasks
5
3%
Use calculator to determine cost of carpet for a room
Use table of information to compare 2 credit cards
4
17%
Use eligibility pamphlet to calculate SSI benefits
Explain difference between 2 types of employee benefits
3
31%
Calculate miles per gallon from mileage record chart
Write brief letter explaining error on credit card bill
2
27%
Determine difference in price between 2 show tickets
Locate intersection on street map
1
22%
Total bank deposit entry
Locate expiration date on driver’s license
Difficulty based on “process complexity”
level of inference
abstractness of info
distracting information
Not reading per se, but “problem solving”
Background fact #6:
People differ more than often assumed
U.S. Dept of Education 1993 survey of adult functional literacy
(nationally representative sample, ages 16+, N=26,091)
Cognitive load brings out cognitive susceptibilitiesSlide52
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Item at NALS Level 1
Literal match One item Little distracting info 22% of US adults
78% of adults do better
80% probability of correctly answering items of this difficulty level
*
*Slide53
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Item at NALS Level 2
X Simple inference Little distracting information
27% of US adults
51%
22%Slide54
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Another item at NALS Level 2
27% of US adults
Match two pieces of info
51%
22%Slide55
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Item at NALS Level 3
31% of US adults Cycle through complex table Irrelevant info
20%
49%Slide56
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Item at NALS Level 4
More elements to match
More inferences
More distracting information
3%
80%
17% of US adults
Solved
Or,
Slide57
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Item at NALS Level 5
97% Search through complex displays Multiple distractors Make high-level text-based inferences Use specialized knowledge
3% of US adultsSlide58
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NALS Level
% pop.
Simulated Everyday Tasks
5
3%
Use calculator to determine cost of carpet for a room
Use table of information to compare 2 credit cards
4
17%
Use eligibility pamphlet to calculate SSI benefits
Explain difference between 2 types of employee benefits
3
31%
Calculate miles per gallon from mileage record chart
Write brief letter explaining error on credit card bill
2
27%
Determine difference in price between 2 show tickets
Locate intersection on street map
1
22%
Total bank deposit entry
Locate expiration date on driver’s license
US Dept of Education: People at levels 1-2 are below literacy level required to enjoy rights & fulfill responsibilities of citizenship
Could teach these individual
items, but not all such tasks
in daily life
Background fact #6:
People differ more than often assumed
U.S. Dept of Education 1993 survey of adult functional literacy
(nationally representative sample, ages 16+, N=26,091)Slide59
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What are “disparities”?
Why such a vexing puzzle?Is human cognitive diversity the key to solving it?If yes, so what?Mine the other 2/3 (cognitive susceptibility & cognitive load)AgendaSlide60
Passive exposure matters
SES
differences predicted
Current SES stress modelAlternative g stress modelPredictorsTime 1Time 2Time 1
Time 2ExposurePassiveEp
+
+
ActiveEa
S
usceptibility
Biological
Sb
0
+
Cognitive
Sc
B
urden
Biological
Bb
Cognitive
Bc
Health
outcomes
Physiological
Yp
0
+
Behavioral
Yb
mechanism
Y = ∑
Ep
60Slide61
But so does
g-based self-exposure, susceptibility, & cognitive load
SES
differences predictedCurrent SES stress modelAlternative g stress modelPredictors
Time 1Time 2Time 1
Time 2Exposure
PassiveEp
+++
+
Active
Ea
+
+
S
usceptibility
Biological
Sb
0
+
?
+
Cognitive
Sc
+
+
B
urden
Biological
Bb
?
?
Cognitive
Bc
?
+
Health
outcomes
Physiological
Yp
0
+
?
++
Behavioral
Yb
+
+
mechanism
Y = ∑
Ep
Y
= ∑E(S)(B)
61Slide62
SES
differences predicted
Current SES stress model
Alternative g stress modelPredictorsTime 1Time 2Time 1Time 2
ExposurePassiveEp
Active
Ea
S
usceptibility
Biological
Sb
Cognitive
Sc
B
urden
Biological
Bb
Cognitive
Bc
Health
outcomes
Physiological
Yp
Behavioral
Yb
mechanism
Y = ∑
Ep
Y
= ∑E(S)(B)
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Internal
External
External
Some are multiplicative
6 (not 1) generators of health disparities,
and multiplicative besidesSlide63
2 new points of leverage
SES
differences predicted
Current SES stress modelAlternative g stress modelPredictorsTime 1Time 2Time 1
Time 2ExposurePassiveEp
Active
Ea
S
usceptibility
Biological
Sb
Cognitive
Sc
B
urden
Biological
Bb
Cognitive
Bc
Health
outcomes
Physiological
Yp
Behavioral
Yb
mechanism
Y = ∑
Ep
Y
= ∑E(S)(B)
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Internal
External
External
#1
#2
Respect diversity of needs
Lighten the loadSlide64
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Need appreciate differential cognitive
needs#1Slide65
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Need appreciate size of cognitive
burdensExample: Do job analysis of chronic diseases
Diabetes?
#2Slide66
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Guidance for providers?
E.g., Matrices of cognitive riskIQIQLo
Hi
Lo
Hi
Lo
Hi
Some errors more dangerous
But all cumulate
Triage
Task complexity
Error rates to expect by
patient susceptibility
task cognitive load
#1
#2
#1
#2Slide67
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Conclusions
Key mechanisms unrecognizedMechanisms highly exploitableHuge opportunity costsFor national policyFor clinic practiceFor vulnerable populationsAmerican Psychological AssociationSlide68
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Thank You
Linda S. Gottfredson, ProfessorUniversity of Delawarehttp://www.udel.edu/educ/gottfredsongottfred@udel.edu(302) 831-1650
American Psychological Association