individual behavioral and biological factors and communication with clinicians eliseo j....
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Individual Behavioral and Biological Individual Behavioral and Biological Factors and Communication with Factors and Communication with
CliniciansClinicians
Eliseo J. Pérez-Stable, MD
EPI 222: Health Disparities Research Methods
April 18, 2012
Conceptual Framework: Multi-level Conceptual Framework: Multi-level Determinants of Health DisparitiesDeterminants of Health Disparities
Psychosocial - beliefs, attitudes, adherence, coping, personality
Behavior - exercise, diet, alcohol, smoking, sexual behavior, substance use
Health care system
Demographics - age, gender, race, ethnicity, education, income
Physical environment
Social environment
HealthHealth& health care& health care
disparitiesdisparities
Biological - genetics,stress, allostatic load, opiate receptors, metabolism, telomeres
Contextual Individual-level
Technical aspects of health care
Communication Communication with clinicianswith clinicians
Economic resources
Life Expectancy at BirthLife Expectancy at Birth
Infant Mortality in California, 2006Infant Mortality in California, 2006(per 1000 live births)(per 1000 live births)
Af AmAf Am APIAPI WhiteWhite LatinoLatino
BirthsBirths 5.3% 11.2% 29% 52.2%
MortalityMortality
RateRateImmigrantImmigrant
US born US born LatinasLatinas
(CA, 2000)(CA, 2000)
12.1 4.1 4.6 5.1
4.85.8
Prevalence of Heart Disease, 2008AHA, Circulation. 2012;125:e2-e220
Total CVD CHD Stroke
Latino men 30.7 6.3 2.0
women 30.9 5.6 2.7
Black men 44.8 7.9 4.5
women 47.3 7.6 4.4
White men 37.4 8.5 2.4
women 33.8 5.8 3.3
Tobacco Use by Race/EthnicityTobacco Use by Race/Ethnicity
Differential Effect on Lung Cancer
Metabolism and Cotinine Cutpoint
Effects on Asthma
Cancer Incidence by Site and Cancer Incidence by Site and Race/Ethnicity in Men, U.S. 2003 - Race/Ethnicity in Men, U.S. 2003 -
2007 2007 (per 100,000 age-adjusted)(per 100,000 age-adjusted)
Af AmAf Am APIAPI WhiteWhite LatinoLatino
ProstateProstate 234.6234.6 9090 150.4150.4 125.8125.8
LungLung 110.2110.2 52.952.9 87.587.5 51.751.7
ColonColon 68.168.1 45.545.5 55.455.4 44.544.5
StomachStomach
LiverLiver16.716.7
7.47.4
17.517.5
12.612.6
9.69.6
4.44.4
14.814.8
9.09.0
Cigarette Smoking in the U.S. – 2011Cigarette Smoking in the U.S. – 2011National Health Interview SurveyNational Health Interview Survey
Why Differences in Lung Cancer?Why Differences in Lung Cancer?
• Prevalence of smoking–10-20 yr lag • Intensity of smoking – Number of
cigarettes per day• Other environmental exposures –
asbestos, air pollution, radon, combustion products
• Genetic predispositions – family history, specific genes
Multiethnic Cohort Study: Lung Multiethnic Cohort Study: Lung Cancer by Smoking IntensityCancer by Smoking Intensity
• 183,813 Af Ams, Japanese-Ams, Latinos, Native Hawaiians, Whites; age 45–75, in California and Hawaii
• 1979 cases lung cancer, identified through SEER, from 1993-2001; 1135 in men
• African Americans as referent group• Stratify by smoking intensity• Relative risk of Lung Cancer by
race/ethnicity within smoking levelHaiman CA, et al. N Engl J Med. 2006;354(4):333-42
Relative Risk of Lung Cancer by Relative Risk of Lung Cancer by Race/Ethnicity and Smoking IntensityRace/Ethnicity and Smoking Intensity
Cigs/dCigs/d Af AmAf Am HawaiiHawaii LatinoLatino JapanJapan WhiteWhite
1-91-9 1.01.0 0.880.88 0.210.21 0.250.25 0.450.45
11-2011-20 1.01.0 0.900.90 0.360.36 0.390.39 0.570.57
21-3021-30 1.01.0 0.930.93 0.610.61 0.610.61 0.730.73
31+31+ 1.01.0 0.950.95 0.790.79 0.750.75 0.820.82
Haiman CA, et al. N Engl J Med. 2006;354(4):333-42
TobaccoTobacco Cancer BiomarkersCancer Biomarkers
• 4-(methylnitrsoamino)-1-(3-pyridyl)-1-butanol (NNAL), a carcinogen itself and metabolite of the tobacco-specific carcinogen (NNK)
• Measured in 5 ml urine, 45 d half-life
• NNAL excretion is highly correlated to nicotine intake per cigarette and with lung cancer development
• Polycyclic aromatic hydrocarbons (PAH): combustion products and smoked and over cooked meats
Nicotine Metabolism and Intake in Nicotine Metabolism and Intake in African AmericansAfrican Americans
• African Americans have more lung cancer and higher cotinine levels per cigarette despite fewer cigarettes/day compared to Whites
• Total and renal clearance of cotinine were 20% lower in African Americans
• Nicotine intake per cigarette was 30% greater in African Americans and thus tobacco smoke intake is higher
JAMA 1999;280:152-56
Nicotine and Carcinogen Exposure in Nicotine and Carcinogen Exposure in White and African American SmokersWhite and African American Smokers
• 61 Black and 67 White smokers with average of 17.2 and 18.3 CPD
• Cotinine level: 179 vs. 164 ng/ml
• Cotinine/CPD higher in Blacks: 12.5 vs. 9.7
• Carcinogen exposure was inversely related to CPD and stronger for Blacks and those smoking mentholated brands
• Blacks smoke cigarettes differently Benowitz NL, et al.NTR 2011; 13: 772-783.
Nicotine Metabolism in Nicotine Metabolism in Chinese and LatinosChinese and Latinos
• Metabolic clearance of nicotine and cotinine in Latinos was similar to Whites and lower among Chinese
• Intake of nicotine per cigarette:– Chinese: 0.73 mg (0.53 to 0.94)– Latinos: 1.05 mg (0.85 to 1.25)
– Whites 1.10 (0.91 to 1.30)
• Nicotine intake = tobacco smoke
Personalize Cessation based on Personalize Cessation based on Biological Metrics?Biological Metrics?
• CYP2A6 genotype (main nicotine metabolizing enzyme)
• 3HC/Cot as marker of metabolism• African American light smokers• Persons with slower metabolism had
higher nicotine levels• Slowest 3HC/Cot quartile had higher quit
rates with OR = 1.85 (1.1-3.2)Ho MK, et al, Clin Pharmacol Ther 2009; 85: 635-43.
Genetics of Nicotine DependenceGenetics of Nicotine Dependence
• Focus on Cholinergic nicotinic receptor (alpha3/alpha5/beta4 complex (CHRN A3/A5/B4) subunit gene cluster on chromosome 15q24-25
• Association of CHRNA5 SNP rs16969968 with nicotine dependence in both Blacks (OR=2.04; 1.15–3.62) and Whites (OR = 1.40; 1.23 – 1.59
Wei J, et al. Human Genetics 2010; 127: 691-8
Ethnic Differences in Ethnic Differences in Serum Cotinine Levels: NHANES 3Serum Cotinine Levels: NHANES 3
>15 ng/mlpercent
≤15 ng/mlpercent
African Amssmokernon-smoker
962
498
Whitessmokernon-smoker
942
698
Mexican Amssmokernon-smoker
721
2899
JAMA 1998;280:135-139
Optimal Serum Cotinine for Optimal Serum Cotinine for Distinguishing Smoking StatusDistinguishing Smoking Status
• NHANES: 13,078 nonsmokers and 3,078 NHANES: 13,078 nonsmokers and 3,078 smokers; based on ROC curvessmokers; based on ROC curves
• Whites: 5.92 ng/mlWhites: 5.92 ng/ml• African Americans: 4.85 ng/mlAfrican Americans: 4.85 ng/ml• Mexican Americans: 0.84 ng/mlMexican Americans: 0.84 ng/ml• Overall cut point is 3.08 ng/ml; 96% Overall cut point is 3.08 ng/ml; 96%
sensitivity and 97% specificitysensitivity and 97% specificity• 15 ng/ml as a cutoff to define biochemical 15 ng/ml as a cutoff to define biochemical
smoking underestimates smokerssmoking underestimates smokersBenowitz N, Am J Epidemiol, November 19, 2008Benowitz N, Am J Epidemiol, November 19, 2008
SHS Exposure: %Non-smokers SHS Exposure: %Non-smokers with cotinine ≥ 0.05 ng/mlwith cotinine ≥ 0.05 ng/ml
1999-20001999-2000 2007-20082007-2008
TotalTotal 52.552.5 40.140.1
Age 3 to 11Age 3 to 11 64.964.9 53.653.6
WhitesWhites 49.649.6 40.140.1
African AmAfrican Am 74.274.2 55.955.9
Mexican AmMexican Am 44.344.3 36.736.7
Below povertyBelow poverty 71.671.6 60.560.5
National prevalence in 2005 = 14%
*
**
Maternal smoking by race/ethnicity
In-uteroIn-utero Tobacco Smoking Tobacco Smoking and Asthma-Related Outcomesand Asthma-Related Outcomes
Pediatrics 2011 (GALA I & SAGE I)
Smoking and Asthma SeveritySmoking and Asthma SeverityIn utero smoking Current SHS
Oh, et al. JACI 2012
Potential Biological Pathways to Potential Biological Pathways to Explain Race/Ethnic DifferencesExplain Race/Ethnic Differences
Genetic Ancestry and Breast Cancer
Vascular Events in Diabetes
Asthma, Alzheimer’s Disease, CVD
Cancer Incidence by Site and Cancer Incidence by Site and Race/Ethnicity, Women, U.S. 2003 Race/Ethnicity, Women, U.S. 2003
- 2007- 2007 (per 100,000 age-adjusted) (per 100,000 age-adjusted)
Af AmAf Am APIAPI White White LatinaLatina
BreastBreast 118.3118.3 9090 126.5126.5 8686
LungLung 53.353.3 52.952.9 27.527.5 26.826.8
ColonColon 68.168.1 45.545.5 55.455.4 44.544.5
UterusUterus 20.620.6 17.317.3 24.424.4 17.617.6
CervixCervix 10.110.1 7.57.5 7.97.9 1212
SEER registries, US
Genetic Ancestry and Breast CAGenetic Ancestry and Breast CA
• 106 ancestry markers genotyped in 106 ancestry markers genotyped in 440 cases and 597 controls440 cases and 597 controls
• Immigrants + less accult protectsImmigrants + less accult protects
• European ancestry associated with European ancestry associated with higher risk of breast CA: OR = 1.79higher risk of breast CA: OR = 1.79
• After adjustment, association was After adjustment, association was attenuated to OR = 1.39 (1.06 – 2.11)attenuated to OR = 1.39 (1.06 – 2.11)
Fejerman L, Cancer Res 2008; 68:9723-28Fejerman L, Cancer Res 2008; 68:9723-28
Genetic Ancestry and Breast Genetic Ancestry and Breast Cancer in MexicoCancer in Mexico
• 106 ancestry markers genotyped in 106 ancestry markers genotyped in 846 cases and 1035 controls 846 cases and 1035 controls
• Mexican City, Veracruz, MonterreyMexican City, Veracruz, Monterrey
• Every 25% increase in European Every 25% increase in European ancestry was associated with ancestry was associated with increased risk of breast CA: OR = increased risk of breast CA: OR = 1.20 (95% CI = 1.03-1.41) compared to 1.20 (95% CI = 1.03-1.41) compared to women with <25% women with <25%
Fejerman L, Cancer Epidemiol Biomarkers Prev 2010; online March Fejerman L, Cancer Epidemiol Biomarkers Prev 2010; online March 23 23
Ethnic Disparities in Diabetic Ethnic Disparities in Diabetic Complications at KPMCPComplications at KPMCP
• Observational study: 62 432 patientsObservational study: 62 432 patients
• 10% Lat, 64% W, 14% AA, 12% API10% Lat, 64% W, 14% AA, 12% API
• Latinos had less MI (0.68), CHF (0.61) Latinos had less MI (0.68), CHF (0.61) and stroke (0.72) compared to Whitesand stroke (0.72) compared to Whites
• More ESRD among Latinos–1.46More ESRD among Latinos–1.46
• Setting of uniform accessSetting of uniform access
• Genetics and environment?Genetics and environment?
Kaiser DM cohort: MI outcomeKaiser DM cohort: MI outcome
Age and sex-adjusted onlyAge and sex-adjusted only Fully-adjusted modelFully-adjusted model
African American
Latino
All AAPI
Chinese
Japanese
Filipino
Pacific Islander
South Asian
At 10 yrs, Compared to Whites…At 10 yrs, Compared to Whites…
Kaiser DM cohort: ESRD at 10 yKaiser DM cohort: ESRD at 10 yKanaya AM, et al. Diabetes Care, Feb 24, 2011, Online.Kanaya AM, et al. Diabetes Care, Feb 24, 2011, Online.
African American
Latino
All AAPI
Chinese
Japanese
Filipino
Pacific Islander
South Asian
Latinos and African Americans Live Latinos and African Americans Live Longer than Whites at ADC CentersLonger than Whites at ADC Centers
Race/EthnicityRace/Ethnicity % % MortalityMortality
Hazard Hazard Ratio*Ratio*
95% CI95% CI
African African AmericanAmerican
3030 0.850.85 0.74-0.960.74-0.96
LatinoLatino 2121 0.570.57 0.46-0.690.46-0.69
AsianAsian 1717 1.061.06 0.81-1.390.81-1.39
American American IndianIndian
3838 1.131.13 0.91-1.400.91-1.40
WhiteWhite 4141 1.01.0 refref*Adjusted for Demographics (age as the timescale, gender, educational level, ADC site, current marital status, living situation), MMSE Score, and age at first dementia symptom
U.S. Asthma Mortality 1990-1995U.S. Asthma Mortality 1990-1995Average Annual Rates per Million
11.315
40.75 40.9
0
10
20
30
40
50
Mexican Caucasian African
American
Puerto Rican
Homa et al. 2000Homa et al. 2000
UCS
F
Contribution
45%
52% 24%
61%
15%3.0%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
MexicanAmerican
Puerto Rican
Percent
Ancestral
Admixture
Native AmericanAfrican
European
Genetic Origins of LatinosGenetic Origins of Latinos
in preparation: Choudhry, Salari & Coyle, et al.
% R
ever
sib
ility
in F
EV 1
aft
er a
lbu
tero
l
0
2
4
6
8
10
12
14
Puerto Ricans Mexicans Puerto Ricans Mexicans
< 16 years old > 16 years old
P=0.0002 p=0.0003
Puerto Ricans Have Lower Drug Response to Albuterol
GALA Study Investigators AJRCCM 2004
Allostatic Load Score in Women: Allostatic Load Score in Women: NHANES, 1999-2005NHANES, 1999-2005
• CV: SBP, DBP, homocysteine, HR; Metabolic: BMI, A1C, HDL, Tchol; Inflammation: albumin, CRP• Higher scores by age, Blacks, less than high school, less income, formerly marries, US born
•Significant interaction by race-ethnicity and age; Blacks at 40-49 14% higher AL than Whites 50-59 and Mexican Americans were similar
•Foreign born had 11% lower AL
CHD Prediction Scores By EthnicityCHD Prediction Scores By EthnicityColor in Framingham?Color in Framingham?
• Applied sex specific CHD functions to 6 ethnically diverse cohorts
• White and Black men and women prediction of CHD events works well
• Japanese & Latino men and American Indian men & women–risk is overestimated
• Adjust for different rates of risk factors and underlying rate of CHD
JAMA 2001; 286:180-7
Chronic Stress, Race, Unhealthy Chronic Stress, Race, Unhealthy Behaviors: HPA AxisBehaviors: HPA Axis
• More depression and suicides in Whites and more substance use/unhealthy eating in Blacks
• Americas’ Changing Lives S: 874 B, 1906 W
• Stressors associated with chronic conditions
•Whites: Unhealthy behaviors strengthened stressors leading to more depression
•Blacks: Unhealthy behaviors protective for mental health conditions but overall number of chronic conditions increased
Jackson J, AJPH 2010; 100: 933-39
TB Rate Ratio by EthnicityTB Rate Ratio by EthnicityDemographics and SESDemographics and SES
Acculturation, SES, BirthplaceAcculturation, SES, Birthplace
Effects on Disease and Behavior
Acculturation: Unifying DefinitionAcculturation: Unifying Definition
• Change in behaviors, values, and social identities
• Complex process that involves change toward reference group: Dominant group in society (White middle-class)
• Minority sub-culture/group (ethnic enclave, inner-city ghettos)
• Change varies by context and ethnic group
Segmented AssimilationSegmented Assimilation
• Does not assume linear, one dimensional path
• Classical: mainstream, dominant• Selective: upward social mobility
and preservation of culture• Downward: disadvantage,
poverty, adoption of sub-culture
California Health Interview California Health Interview Survey, 2005Survey, 2005
• 18 years old +, generation, language at home, Census neighborhood
• Outcome: Non-leisure PA: walking at work most of the day and walking/biking for transportation or errands
• Leisure PA: walking, moderate or vigorous activities in free time
• Merge with US Census 2000
Percent college education by Percent college education by immigrant generation: CHIS 2005immigrant generation: CHIS 2005
Afable-Munsuz A, Ponce N, Perez-Stable E, Rodriguez M. Immigrant generation and physical activity among Mexican, Chinese and Filipino adults in the U.S. Soc Sci Med 2010;70(12):1997-2005.
Percent English only at home by Percent English only at home by immigrant generation: CHIS 2005immigrant generation: CHIS 2005
Afable-Munsuz A, Ponce N, Perez-Stable E, Rodriguez M. Immigrant generation and physical activity among Mexican, Chinese and Filipino adults in the U.S. Soc Sci Med 2010;70(12):1997-2005.
Percentage at Recommended non Percentage at Recommended non leisure-time physical activity by leisure-time physical activity by language at home : CHIS, 2005language at home : CHIS, 2005
Afable-Munsuz A, Ponce N, Perez-Stable E, Rodriguez M. Immigrant generation and physical activity among Mexican, Chinese and Filipino adults in the U.S. Soc Sci Med 2010;70(12):1997-2005.
Recommended non-leisure time physical Recommended non-leisure time physical activity among Mexicans: CHIS, 2005activity among Mexicans: CHIS, 2005
Generation Bivariate OR (95% CI)
Odds Ratio (95% CI)
11stst RefRef RefRef
22ndnd 0.80.8 0.6, 0.90.6, 0.9 0.90.9 0.7, 1.10.7, 1.1
33rdrd 0.80.8 0.6, 0.90.6, 0.9 0.80.8 0.6, 1.10.6, 1.1
.Afable-Munsuz A, Ponce N, Perez-Stable E, Rodriguez M. Immigrant generation and physical activity among Mexican, Chinese and Filipino adults in the U.S. Soc Sci Med 2010;70(12):1997-2005.
Immigrant generation and diabetes risk Immigrant generation and diabetes risk in an aging Mexican-origin populationin an aging Mexican-origin population
• Sacramento Area Latino Study on Aging
• 1998-99: in home visits every 12–15 months for a total of 7 follow-up visits
• 60-101 y at baseline, N=1,789 Generation, acculturation scale
• Diabetes: fasting glucose >125 mg/dl, self-report of MD diagnosis or med Rx
• Only 13% self-report alone
Education by immigrant Education by immigrant generation: SALSA 1998-99generation: SALSA 1998-99
Diabetes prevalence by immigrant Diabetes prevalence by immigrant generation: SALSA 1998-99generation: SALSA 1998-99
Diabetes risk among Mexican-origin Diabetes risk among Mexican-origin older adults: SALSA, 1998-99older adults: SALSA, 1998-99
Generation Unadjusted Odds (95% CI)
Adjusted Odds (95% CI)
1st 1.0 1.0
22ndnd 1.81.8 1.4, 2.41.4, 2.4 1.81.8 1.3, 2.31.3, 2.3
33rdrd 2.12.1 1.4, 3.11.4, 3.1 2.02.0 1.3, 3.11.3, 3.1
*Adjusted for BMI, acculturation, sex, age, lifestyle, education, occupation
Immigrant generation, Language, SES Immigrant generation, Language, SES and diabetes risk, HEPESE, 1993-2005and diabetes risk, HEPESE, 1993-2005
• 3050 Mexican Am, 5 states, 65 y at baseline• 58% women, 45% immigrants, 10% HS grad+,
78% Spanish survey, 42% Medicaid/No Insur• 27.7% diabetes at baseline (all self-report),
27% BMI >30• Incident Diabetes: Spanish/low SES/1st to 3rd
generation: HR=1.76 (1.02-3.03)• English/high SES/1st to 3rd generation: HR=
0.45 (0.22-0.91)
Communication of Cancer Risk between Clinicians and Diverse
Women PatientsPerception of Risk
Estimating Risk Using Visual Icon Arrays
Willingness to Take SERM to lower Breast Cancer Risk
Communication of Risk StudyCross-sectional surveys of women recruited
from primary care practices at UCSF, SFGH and SF Community Clinics with physician consent
1160 interviewed by phone and in person29% White, 14% African American, 21%
Latina, 36% Asian (mostly Chinese)51% were 60 to 80 years old, 36% less than
high school education, 19% uninsuredRates of cancer screening: Pap in 2 y 61%
to 74%, mammogram 81% to 92%, colon 23% to 66%
Cancer Risk Perception What would you say is your risk of getting?
Cervical cancer Breast cancer Colon cancer
Response choices: 0 - No risk 1 - Very low risk 2 - Somewhat low risk 3 - Moderate risk 4 - High risk/very high risk
Breast Cancer Risk Perception
White African American
Latina Asian
No risk 2 7 10 48
Very low risk 27 24 20 18
Somewhat/low risk
35 27 33 23
Moderate 27 28 19 8
High/very high risk
8 14 18 3
Here is a blank picture of a wall of 100 women. Each woman represents 1 chance in 100 that something will happen. Roughly, 13% of women will develop breast cancer in their lifetime. This also means that an average woman has a 13% chance of developing breast cancer in her lifetime. Please circle how many chances out of 100 would be an average woman’s chance of developing breast cancer over her lifetime.
Cancer Scenario
58
Race/Ethnicity Breast Colon Cervical
White 81% 86% 67%
African American
33%* 38%* 36%
Latina 24%* 32%* 15%*
Chinese 35%* 50%* 51%
TOTAL 47% 56% 47%
Results: Correct number circled on wall of women
*p<.001
Odds Ratios of Correct/Incorrect Use of Wall of Women VisualsVariable Total
WallWall of 100 Wall of 10k
< High school 0.55 (0.35-0.90)
0.44 (0.25-0.78)
0.52 (0.16-1.69)
African Ams 0.36 (0.22-0.61)
0.30 (0.17-0.54)
0.62 (0.18-2.11)
Chinese 0.68 (0.41-1.13)
0.49 (0.27-0.89)
1.54 (0.55-4.31)
Latinas 0.36 (0.22-0.60)
0.34(0.19-0.61)
0.25(0.07-0.83)
Numeracy Score
1.30(1.21-1.40)
1.29(1.18-1.41)
1.37(1.15-1.64)
Factors Associated with Willingness to take Tamoxifen if at High Risk (Kaplan C, et al. Breast Cancer Research and Treatment 2012; 133: 357-366)
Factor (ref) Percentage Odds Ratio 95% CI
Asian (White) 57 3.0 1.3-6.8
< High School (College) 50 3.2 1.2-8.4
No insurance (private) 59 2.5 1.1-5.7
Numeracy 6-8 (0-2) 36 2.4 1.0-5.6
Less Breast cancer knowledge
40 1.4 1.1-1.9
More Tamoxifen knowledge
29 0.7 0.5-0.9
Implications
•Ability to understand graphic presentations and estimating numbers vary by race/ethnicity
•Educational attainment and numeracy explain part of the difference
•Perception of risk may be a qualitative construct
•Prostate cancer and watchful waiting
•Screening for lung cancer with CT
Communication with CliniciansCommunication with Clinicians
Language
Definition of Limited English Definition of Limited English Proficiency (LEP)Proficiency (LEP)
• 18% of adults LEP in 2010 census; 5% live in linguistically isolated households, 80% increase in 20 y
• Definitions of LEP by US census question–no routine method
• Response to survey, self assess, fluency scales
• Acculturation, education, legal status
LEP Status and Health OutcomesLEP Status and Health Outcomes
• LEP status not associated with less quality of care in Diabetes (tests, A1c, SBP), immunizations for ≥ 65, psychiatric evaluations, perceived care quality in past 12 mo, cancer screening tests and evaluation of abnormal tests
• LEP is associated with less health info on telephone, harder access, longer waits
Identifying LEP Patients: Two Identifying LEP Patients: Two standard questionsstandard questions
• Need systems to use standard Need systems to use standard questions on all patientsquestions on all patients
• US Census question: How well do US Census question: How well do you speak English? Very well, you speak English? Very well, well, well, not well, not at allnot well, not at all
• What language do you prefer to What language do you prefer to receive your medical care?receive your medical care?
Karliner L, Karliner L, J Gen Intern Med. 2008; 23:1555-60Institute of Medicine Report 2009
Census Question Plus PreferenceCensus Question Plus Preference
• 104 spoke English well; 32 spoke English less than “very well”; and 166 spoke “not well or not at all”
• 52% preferred Spanish for health care• Outcome of effective communication--
discuss or understand• Census: 100/99% sens; 73/67% specific• Census + : 99/97% sens;99/97% sens; 92/84% specific92/84% specific
Constructs in Evaluating Constructs in Evaluating Language AccessLanguage Access
• Patient-clinician encounters
• Communication with staff
• Language concordance is best?
• Interpreters: professional or ad hoc?
• Mode: in person or remote
• Effects on quality of care and disease outcomes: What matters?
Language Concordance MattersLanguage Concordance Matters
• • Understand more MD instructions Understand more MD instructions and ask more questions (NY)and ask more questions (NY)
• Trend to better medication Trend to better medication adherence in asthma (NY)adherence in asthma (NY)
• Ask more questions and receive Ask more questions and receive more patient centered care (UCI)more patient centered care (UCI)
• Patients feel better, have less pain, Patients feel better, have less pain, better health outlook (UCSF)better health outlook (UCSF)
Effect of Clinician Language Effect of Clinician Language Concordance on MOS MeasuresConcordance on MOS Measures
Perez-Stable EJ, et al, Medical CarePerez-Stable EJ, et al, Medical Care
MOS MeasureMOS Measure ConcordantConcordant
(n = 44)(n = 44)
DiscordantDiscordant
(n = 29)(n = 29)
AnxietyAnxiety 72.272.2 55.155.1
DepressionDepression 68.168.1 54.754.7
Current Current healthhealth
47.347.3 31.631.6
Effects of Effects of painpain
34.034.0 54.754.7
LEP is a Risk Factor for Poor LEP is a Risk Factor for Poor Control of DiabetesControl of Diabetes
• Kaiser Diabetes Study, n = 6730, Kaiser Diabetes Study, n = 6730, mean age 60 y, 510 LEP Latinosmean age 60 y, 510 LEP Latinos
• A1c > 9%: 10% Whites, 18% Latinos,A1c > 9%: 10% Whites, 18% Latinos,21% LEP-Lat21% LEP-Lat• • Concordant LEP = 16% vs. 28%Concordant LEP = 16% vs. 28%• • LEP discordant c/w Eng-Lat had OR = LEP discordant c/w Eng-Lat had OR =
1.76 (1.04 - 2.97) of A1c > 9% and OR 1.76 (1.04 - 2.97) of A1c > 9% and OR = 1.98 c/w concordant Latinos= 1.98 c/w concordant Latinos
Fernandez A, JGIM online 29 September 2010Fernandez A, JGIM online 29 September 2010
Pew Hispanic Center/RWJF Latino Pew Hispanic Center/RWJF Latino
Health SurveyHealth Survey • 2921 foreign-born respondents, mean age
41 y, 60% insured, 82% had language concordant care
• English proficiency mean score 2.6• Concordant care: less confusion,
frustration, and perceived bias• Concordance, yrs education, insurance
were associated with higher quality of care ratings in previous 12 mo
Gonzalez HM, J Am Board Fam Med 2010; 23:
How Much Fluency is EnoughHow Much Fluency is Enough??
• Language fluency is a gradient and Language fluency is a gradient and patients may avoid discussing patients may avoid discussing complex topics perceiving clinician complex topics perceiving clinician limitations (SFGH)limitations (SFGH)
• Physician self assessment as Physician self assessment as excellent or good verified by excellent or good verified by patients, but patients, but ““fairfair”” was toss-up was toss-up
• Language certifications for cliniciansLanguage certifications for clinicians
English Language Proficiency and English Language Proficiency and Health LiteracyHealth Literacy
• Study of 771 outpatients, mean age 56 y, 58% women, 51% limited literacy
• 53% Eng, 23% concord, 24% discord• 3 types of communication domains:
receptive, proactive, interactive• Limited HL with poor communication:
35%-35%-62% vs. 24%-20%-50%• LEP discordant with poor communication:
43%-46%-73% vs. 25%-21%-48% (English)Sudore RL , Patient Education and Counseling 2009
Ethnicity in Patient-Doctor Ethnicity in Patient-Doctor RelationshipRelationship
• Refusal: whose issue?
• DNR discussions–Race of clinician is an independent predictor
• Cultural competence
• Language factors
• Racism may affect behavior:– Fewer cardiology referrals in Blacks
Outcomes of Communication Outcomes of Communication on Medical Care at EOLon Medical Care at EOL
• Blacks receive more care• 71 B, 261 W pts with advanced cancer• Outcomes: EOL discussions: awareness,
preferences, DNR; and EOL Care: more, hospice, preferences
• Discussions: 35% vs. 38%, Life-prolonging: 20% vs. 7%
• EOL discussions decreased life-prolonging care in Whites (OR=0.11), but not Blacks.
Mack J, et al. Arch Intern Med 2010; 170:1533-40
Ethnicity and Attitudes toward Patient Ethnicity and Attitudes toward Patient Autonomy among Persons ≥ 65 yrsAutonomy among Persons ≥ 65 yrs
Conceptual Framework: Multi-level Conceptual Framework: Multi-level Determinants of Health DisparitiesDeterminants of Health Disparities
Psychosocial - beliefs, attitudes, adherence, coping, personality
Behavior - exercise, diet, alcohol, smoking, sexual behavior, substance use
Health care system
Demographics - age, gender, race, ethnicity, education, income
Physical environment
Social environment
HealthHealth& health care& health care
disparitiesdisparities
Biological - genetics,stress, allostatic load, opiate receptors, metabolism, telomeres
Contextual Individual-level
Technical aspects of health care
Communication with clinicians
Economic resources