Building Bridges: Improving Health through Program

Integration Ethnic Myths:

Implications for Chronic Care Management

Sharon A. Brown, PhD, RN, FAANProfessor and Associate Dean for ResearchDirector, Cain Center for Nursing Research

The University of Texas at Austin School of Nursing

• List 3 cultural myths related to racial, ethnic, or cultural norms about health…

• Describe 2 strategies for addressing these myths in chronic care management and their ethical implications

• Discuss 3 ethical principles of providing care that is culturally competent

OBJECTIVES

Meta-analysis

Intervention

3

• Recruitment / Retention• Genetic Predisposition /

“Fatalism”• Gender Roles• Acculturation & Dietary Practices• Breaking barriers with

“Promotoras” (CHWs)

CULTURAL MYTHS

RESPECT FOR PERSONSIndividuals are autonomous

Protect those with diminished autonomy

BENEFICIENCEDo no harm

Maximize possible benefits / minimize possible harms

JUSTICE: to each person…an equal share

according to individual needaccording to merit

ETHICAL PRINCIPLES

RESEARCH MOTIVATION

Growing diabetes epidemicTight glucose control reduces complications by 25%-75% (DCCT,

UKPDS)Glucose control —> 6 years of

additional life$174 billion spent annually

Less than 30% achieve glycemic

control

Predicted growth of the Hispanic population

Source: Passel, J.S., & Cohn, D. (2008). U.S. population projections: 2005-2050. Washington, DC: Pew Research Center.

U.S. 296 million (2005)population: 438 million (2050, immigrants)

Latinos: largest minority group (14%)will triple in size

Whites: will become a minority (47%)

Elderly: ≥ double in size

•Prevalence per 100,000 Source: CDC Wonder (the Healthy People 2010 Database)

Diabetes prevalence rates in the U.S.*

GROUPPrevalence Rate (2008)

American Indian or Alaskan Native 109

Black / African American 83

Hispanic / Latino 81

Asian 58

White 55

Gender:FemaleMale

5860

Education:< high schoolHigh school graduateAt least some college

132102

70

by racial

group

•Deaths per 100,000 (only 30% of diabetes death rates documented on death certificates) Source: CDC Wonder (the Healthy People 2010 Database)

Diabetes-related death rates in the U.S.*

Racial / Ethnic Group Death Rate (2006)

Black / African American 127

Hispanic:CubanMexican AmericanPuerto Rican

52104108

American Indian 98

White 69

Asian / Pacific Islander 55

Gender:FemaleMale

6389

Education:< high schoolHigh school graduateAt least some college

614116

by racial

group

2001 2004

Blacks 113 104

Hispanics 63 80

Whites 28 31

• Amputations per 100,000 population Source: Agency for Healthcare Research and Quality, 2008

Diabetes-related amputation rates by

race/ethnicity in the U.S.*

ONLY 38% OF ADULT HISPANICS RECEIVED SCREENINGS

(foot exams, eye exams, A1c) COMPARED TO 47% FOR WHITES

AND 47% FOR BLACKS

Diabetes Prevention Program

Diabetes Prevention Program

Group 1Coaching in healthy lifestyle designed to

promote weight loss(diet & physical activity)

Group 2Metformin

Group 3Placebo

Diet and exerciseDiet & physical activity

(walking) reduced risk of diabetes by 58%

Diabetes drug Reduced risk of diabetes by 31%

Consistent across populations

Highest reduction

achieved by people over age 60 in diet & exercise group –

a 71% reduction

RESULTS

Promoting Weight Loss in Type 2 Diabetes (n=89)

(Brown et al., 1996)

-20# wt. loss -2.4%-age points

Glazier et al. (2006). A systematic review of interventions to improve diabetes care in socially disadvantaged populations. Diabetes Care, 29, 1675-1688.

At least a 1.0%-age point reduction in HbA1c (reduces death by 10%, microvascular end points by 25%)

Consistent positive effects in studies that included:•Cultural tailoring•Community educators / lay people•One-on-one interventions w/ individualized assessment•Treatment algorithms•Behavior-related tasks•Feedback•High-intensity interventions (>10 contacts, ≥6 mos.)

DSME EFFECTS

14

The Starr County Border Health Initiative

STARR COUNTY, TEXAS

SETTING: Starr CountyPopulation: 62,249

97.5% Hispanic Poorest county in Texas - 3rd poorest in U.S.

Unemployment rate 11.9% (2008)Per capita income $10,716 (2008)

Young population — 10% > 65 years of age2,200+ colonias on the border — 400,000 people

Diabetes affects 50% of adults over age of 35 (Hanis, 1983)50% of health care obtained in Mexico

Lower RGV has highest diabetes-related death rateNative American admixture contributes to risk/ethnic differences

Hispanics labeled “noncompliant” — more likely treated with insulin

Population:MD = 7657:1 (3789:1 rest of TX)Population:RN = 851:1 (159:1 rest of TX)

Source: Texas Secretary of State, http://www.sos.state.tx.us/border/colonias/faqs.shtml

SETTING: Starr County

17

SETTING: Starr County

18

COMMUNITY ASSESSMENT

Understanding of diabetes:“Blood sugar” or blood glucose testing / results

“God’s will” (“fatalism” but generational differences) Will “get diabetes” eventually (“fatalism” or reality?)

Previous diabetes-related experiences:Told not to eat cultural food preferences

Previous weight loss “failures”Feared insulin injections

Diabetes care from both sides of the borderFolk remedies (generational differences)

Suggestions for a diabetes intervention:Interested in DSME

No complicated exchange listsNo brochures (low literacy rates among elderly)Involve family members (low levels of support)

Reduce fat intake (lard)

health literacy“a stronger predictor of health than age, income, employment status, education level, and race”

Source: Report of the Council of Scientific Affairs, Ad Hoc Committee on Health Literacy for the Council on Scientific Affairs, American Medical Association, JAMA, Feb 10, 1999

Populations Vulnerable to Poor Health Literacy

• Minority / immigrant populations• Low income: 1/2 Medicare/Medicaid

recipients read <5th grade level• People w/ chronic health conditions• Elderly: 2/3 have inadequate literacy

Source: National Network of Libraries of Medicine (nnlm.gov)Williams, MV. JAMA, December 1995

Consequences of poor health literacy

• Take meds. on erratic schedules• Miss follow-up appointments• Do not understand instructions

(81% of patients ≥ 60 years of age at public hospital could not read or understand basic materials such as prescription labels)

Source: IOM, Health Literacy: A Prescription to End ConfusionWilliams, MV. JAMA, December 1995

Diabetes-Related Knowledge (n=252)

(% that identified the right answers across relevant items)

Diabetes-Related Knowledge (n=252)

(% that identified the right answers across relevant items)

Consequences of poor health literacy in

Starr County

Consequences of poor health literacy in

Starr County Self-prescribing of medications and

other treatments Misinterpretation of symptoms — did

not perceive symptoms as serious Misinterpretation of HCP

recommendations Misunderstanding of health

experiences of family and friends

Self-prescribing of medications and other treatments

Misinterpretation of symptoms — did not perceive symptoms as serious

Misinterpretation of HCP recommendations

Misunderstanding of health experiences of family and friends

• Recruitment / Retention• Genetic Predisposition /

“Fatalism”• Gender Roles• Acculturation & Dietary Practices• Breaking barriers with

“Promotoras” (CHWs)

CULTURAL MYTHS?

Language

Family-centered

Non-judgmental approach

Transportation

Flexible scheduling

Reminders — telephone, calendarsBenefits — feedback, intervention, monitoring, rewards

Snacks of healthy Mexican American foods

STARR COUNTY STUDIESRecruitment: 95% Retention: 81-90% CULTURAL COMPETENCE

Matches superficial characteristics of the culture (e.g., food, music)

Integrates deep structure of the culture (social, historical,

environmental, psychological factors)

SAMPLE CHARACTERISTICS

SAMPLE CHARACTERISTICS

64% female

54 years of age on average (range 35-70)

20% on insulin

38% use alternative remedies (garlic, chaya)

8 years average diabetes duration (range 1-25)

Scored low (1.0) on acculturation scale (0-4)

90% preferred speaking Spanish

• Recruitment / Retention• Genetic Predisposition /

“Fatalism”• Gender Roles• Acculturation & Dietary Practices• Breaking barriers with

“Promotoras” (CHWs)

CULTURAL MYTHS?

INTERVENTIONSCulturally tailored education + group support:

52 contact hours (“extended”)22 contact hours (“compressed”)

Series of Spanish-language videotapesInstructors: RNs & RDs + promotoras

Social support: family members, friends, groupsCommunity-based settings (churches, schools)

1,100+ study participants

“Diabetes y Su Salud”“Diabetes y Su Salud”

MEASURESHbA1c DemographicsFBG Health historyBMI AcculturationCholesterol Diabetes knowledgeBP Health beliefsLeptin Family historyTriglycerides Medication historyMicroalbuminuria Fat intakeComplications Food frequency

Physical activity

Compressed vs. Extended Program (1999-2004)

STUDY STUDY OUTCOME:OUTCOME: HbA1c HbA1c

11.9

10.810.9

11.7

11.3

10.610.4

10.5

10.0

10.5

11.0

11.5

12.0

Baseline 3 Mos. 6 Mos. 12 Mos.

Compressed Extended

MYTHGenetic Predisposition, “Fatalism”

Outcome: HbA1c

Compressed vs.

Extended Program

≥50% attendance(n=110)

Outcome: HbA1c

Compressed vs.

Extended Program

≥50% attendance(n=110)

11.6

10.5 10.5

11.010.9

9.9

9.6

9.29.0

9.5

10.0

10.5

11.0

11.5

12.0

Baseline 3 Mos. 6 Mos. 12 Mos.

Compressed Extended

MYTHGenetic Predisposition, “Fatalism”

Dosage Effects of Program Attendance

Dosage Effects of Program Attendance

• Recruitment / Retention• Genetic Predisposition /

“Fatalism”• Gender Roles• Acculturation & Dietary Practices• Breaking barriers with

“Promotoras” (CHWs)

CULTURAL MYTHS?

MYTH:Gender Roles

HEALTH BELIEFS

Control over diabetes

males (F=4.1, p=.05)

Social support

males (F=6.1, p=.01)

HEALTH BELIEFS

Control over diabetes

males (F=4.1, p=.05)

Social support

males (F=6.1, p=.01)

METABOLICCONTROL

HbA1c levels lower in males (t=3.11, p=.002)

Males with greater attendance achieved greater improvements in HbA1c

METABOLICCONTROL

HbA1c levels lower in males (t=3.11, p=.002)

Males with greater attendance achieved greater improvements in HbA1c

• Recruitment / Retention• Genetic Predisposition /

“Fatalism”• Gender Roles• Acculturation & Dietary Practices• Breaking barriers with

“Promotoras” (CHWs)

CULTURAL MYTHS?

MYTH:Acculturation & Dietary Practices

(weight & type 2 diabetes)

Returning native cultures to traditional cultural diets significantly improves glucose intolerance and insulin resistance

Recommendations:

•Walk 30 minutes per day

•Lose 5-7% body wt ( 500-1000 kcal)

• Recruitment / Retention• Genetic Predisposition /

“Fatalism”• Gender Roles• Acculturation & Dietary Practices• Breaking barriers with

“Promotoras” (CHWs)

CULTURAL MYTHS?

“…a community health safety net and a natural extension of the health and human services agencies, improve health at the neighborhood level.”

•Latin American program-type for underserved populations•peer liaisons — advocacy, interpersonal relations, capacity building, communication, knowledge, organization, teaching, service coordination•beyond community health worker model:

speak the same languagecome from the same neighborhood

•tend to be women

[Nichols et al., Prev Chronic Dis, Nov 2005]

MYTH — Breaking barriers:“Promotoras” (CHW)

Promotoras: a cautionary tale

Focus group input: promotoras not acceptable as group leaders

Anecdotal evidence: individuals consider the use of the promotora model as racial

Starr County promotora role:•Data collection•Recruitment•Telephone contact / reminders•Transportation•Motivation•Logistical support (intervention sites, materials)•Grocery shopping / preparation of snacks

RESPECT FOR PERSONSIndividuals are autonomous

Protect those with diminished autonomy

Best predictor of health — health literacyCultural myths — “fatalism,” generational

differencesPromotora modelHeterogeneity within

culturesUse of focus groupsLanguage issues

ETHICAL PRINCIPLES

Community-based research• takes place in community settings • involves community members in the design and implementation of research projects

Principles:Community involved at the earliest stages

Community influences project Research processes & outcomes benefit communityCommunity hired and trained whenever possible

Community part of data interpretation; input into how results are distributed

Partnerships should last beyond the project Community empowered to initiate their own projects

Source: http://sph.washington.edu/research/community.a

sp

BENEFICIENCEDo no harm

Maximize possible benefits / minimize possible harms

Alarming self-management practicesIntegrate DSME into other aspects of treatmentFamily involvement / social supportHome glucose self-monitoringSocioeconomic constraintsReal environmental barriersPhysiologic barriers to improved glycemia

ETHICAL PRINCIPLES

JUSTICE: to each person…Mexican Americans / Hispanics least studied group

Hispanic health disparities:lower rates of health screenings — 38% vs. 47% for whites and blackshigher diabetes prevalence rates — 1.5 x whiteshigher diabetes-related deaths — 1.5 x whites

Average HbA1c reduction with effective DSME interventions across all groups — 2.4%-age points

Average HbA1c reduction attained with DSME culturally tailored for socially disadvantaged groups — ≥1.0%-age points

Few minority health professionals

ETHICAL PRINCIPLES

Estimated Intervention Costs

Craig Hanis, PhD, Co-PI (Professor, UT-Houston School of Public Health)

Alexandra García, RN, PhD, Co-I (Associate Professor, UT Austin School of Nursing)

Kamiar Kouzekanani, PhD, Co-I(Statistician, UT Austin [previously])

Philip Orlander, MD, Consultant / Co-I (Chair, Division of Endocrinology, UT-Houston Medical

School)

Research AssociatesMaria Winchell, MS Mary Winter, MSN

RESEARCH TEAM

Intervention StaffEvangelina Villagomez, MSN, RNMario Segura, MSN, RNLilia Fuentes, MSN, RNLita Silva, MSN, RN, CDENora Morín Siller, RD, LDMaria Olivia Garza, RD, LDAna Gonzalez, MS, RD, CDENorma Cottrell, RDMila Villareal, MSN, RNJuan Jesús Treviño, BS, LDPatricia Ramírez, RD, LDRogelio Contreras, RNCelia Zuñiga, RNEmiliana Guerra, RDSylvia Cardenas, RN, FNPVentura Huerta, RN, BSN, MPH

Starr County Field OfficeHilda Guerra, ManagerSylvia HinojosaMarie LópezImelda MartínezAlma MartínezJesusa L. SalmónMaricela GarzaMaria CoderUmbelina ReynaMinerva MargoElva Yolanda MoradoMaria GarzaClara TreviñoElizabeth Peña

RIO GRANDE VALLEY STAFF

Funded by...

Funded by...

Office of Research in Minority Health

State of TexasUniversity of Texas at Austin

University of Texas at Houston