U.S.-Mexico Border Health: A Medically Underserved Community

Hector Balcazar, MS., PhD,UT School of Public HealthHealth Science Center HoustonEl Paso Regional Campus

Presenter Disclosures

Dr. Hector Balcazar

No relationships to disclose

Research Training Dissemination

❶Why Is the U.S.- Mexico Border Important For Assuring Health Equity?

❷Assess Unique Social Determinants of Health Within a Social Justice Framework

❸What Interventions To Develop? Presented at the American Public Health Association 140th Annual Meeting

San Francisco, California

Why The U.S.-Mexico Border? Hispanics largest minority Living in Two Worlds (Countries)- Many Worlds Very heterogeneous Moving everywhere in the U.S.- Great contributors

to economy (many not appreciated) Many “invisible populations”, migrant workers,

temporary, unauthorized, bilingual, bicultural Resilient and Active Participants in Decision-

Making Very vulnerable- (low education, low SES, low

social and economic capital/ no wealth)- wear-tear- for how long can this continue?

Paradoxically there are large health systems in the Border and yet large number of uninsured

U.S.-Mexico Border Region

Health Insurance“In the United States, Texas has the highest proportion of residents without health insurance (28.5%); The situation in EI Paso County is even more severe with almost 40% of adults lacking any health insurance. The high rate of uninsured in this region reflects the high rates among Hispanics; over 45% of Hispanics are uninsured as compared to less than 15% of non-Hispanics.”

Ref: A status report on the health of people in El Paso County, TX and Dona Ana County, NM, CBHR BRFSS 2005

2. Overweight and Obesity

Ref: A status report on the health of people in El Paso County, TX and Dona Ana County, NM, CBHR BRFSS 2005

3. Diabetes

Ref: A status report on the health of people in El Paso County, TX and Dona Ana County, NM, CBHR BRFSS 2005

9

Texas Projected Population Increases by Race/Ethnicity, 2000-2040*

0

5,000,000

10,000,000

15,000,000

20,000,000

25,000,000

30,000,000

35,000,000

40,000,000

2000 2010 2020 2030 2040

YEAR *Uses 0.5 migration scenario. Texas State Data Center - Off ice of

the State Demographer, Institute for Demographic and Socioeconomic Research, College of Business, University of

Texas at San Antonio.

Pop

ulat

ion

Hispanic

Black, non-Hispanic

White, non-Hispanic

TOTAL

10

Texas Projected Diabetes Cases 2000 - 2040*

0

500,000

1,000,000

1,500,000

2,000,000

2,500,000

3,000,000

2000 2010 2020 2030 2040

Nu

mb

er

of

Dia

be

tes

Ca

se

s

YEAR *Uses 2007 diabetes prevalence by race/ethnicity from BRFSS and population data from the Texas State Data Center - Office of the State Demographer, Institute for Demographic and Socioeconomic Research. Uses 0.5

migration scenario.

Hispanic (Prevalence = 12.3%) Black, non-Hispanic (Prevalence = 12.9%)

White, non-Hispanic (Prevalence = 8.5%) TOTAL (Prevalence = 10.3%)

CBPR- Tell An Initial Story from Baseline: Family History of Disease

50.8

66.8

44.7

67.2

0

10

20

30

40

50

60

70%

of

Yes

Intervention Group Control Group

Family History of Heart Disease Family History of Diabetes

51% of the intervention group and 45% of the control group reported having a relative with cardiovascular disease. In both groups, 67% of the participants reported having a relative with Diabetes.

Metabolic Syndrome & Diabetes

Metabolic Syndrome is an indicator or risk for cardiovascular disease. It is associated with six characteristics: adbominal obesity, disturbance in the blood fat levels, raised blood pressure, glucose intolerance, proinflammatory state, prothrombotic state.

47.8

31.6

48.4

25.2

0

5

10

15

20

25

30

35

40

45

50

%

Intervention Group Control Group

Metabolic Syndrome (> 3 risk factors) Diabetes (self-reported)

Nearly half of the intervention group and 40% of the control group had more than 3 risk factors for metabolic disease.

Nearly 1/3 of the intervention group and ¼ of the control group reported having diabetes.

Use of Medication

More than 40% of participants in both groups used medication to control blood pressure. Nearly 30% used medication to reduce blood cholesterol, and 25% of the intervention group and 22% of the control group used medication to control diabetes.

25

42.1

29

22.1

41.9

27.3

0

5

10

15

20

25

30

35

40

45

%

Intervention Group Control Group

Use of Diabetes Medication Use of Hypertensive Medication Use of Cholesterol Medication

Data From Cameron County Texas• Data from Cameron County Hispanic

Cohort from 2003-2008, of 2000 Mexican American Adults aged 18 or older

• Close to 70% had 1 or more conditions such as diabetes, hypertension, hypercholesterolemia

• Weighted Prevalence: Diabetes 30.7%, Hypertension 30.5%, Hypercholesterolemia 48.2%

• More than half of participants with diabetes (55.8%) were untreated among whom 29.9% had insurance and 10% had their diabetes diagnosed

• Of the drugs being taken for diabetes, 28% appeared to be of Mexican origin

• Lack of health affected several measures

Research Training Dissemination

❷Assess Unique Social Determinants of Health Within a Social Justice Framework

Presented at the American Public Health Association 140th Annual Meeting

San Francisco, California

Research Training Dissemination

Contextual-level understanding of

determinants

Why We Haven’t Made More Progress in Addressing/Eliminating Health Disparities?

Need Understand Multiple Social & Ecological Determinants

Environmental Factors Biopsychosocial Factors

Epidemiological profile Transborder Mobility Limited or no existing

services Legal and economic

barriers Low SES Immigration issues Lack of infrastructure border culture Low educational

attainment/goals Low community

empowerment/self-efficacy

Acculturation issues

Gender roles Health beliefs Health literacy Religiosity &

Spirituality Health behavior

norms (substance abuse; sexual risk)

Familism Fatalism Stigma

Norms affecting health decision-making

Hispanic Health Paradox (vulnerability and resilience)

Population genetic factors

Positive and negative lifestyle factors (nutrition, exercise, substance abuse, drug use & mode of delivery

Understanding Contextual Factors• Transborder mobility is a fact-

29.9% once a month, 20.4% once a week (324 mobile versus 678 non-mobile)

• Non-mobile respondents have higher social economic status than their mobile counterparts

• Mobile respondents have fewer economic resources, travel to Juarez for various goods and services

• Similar high levels of familismo, ethnic pride

• Mobile more likely to speak Spanish, be educated in Mexico, reside in U.S. for a shorter period

• Border crossing also included accessing services in Mexico and purchasing food and medications

Contextualizing Barriers To Care:Co-Morbidities Along US-Mexico Border

StructuralTransportation

Cognitive BarriersPatient-Provider

How are these factors related to individuals seeking health care when they have a series of co-morbidities? Work submitted for publication!

FinancialDifficulty paying

So- what is the social justice framework? Does it exists?

Not Yet!

How to Ensure Equitable, Sustainable and Long-Range Interventions- Working with New New Paradigms

Greater Demands On Prevention and Intervention Services

Old-Traditional

We Need Change- Real Change in Examining border specific characteristics and elucidate heterogeneity of border Hispanics-

New Paradigms

Research Training Dissemination

“My granddad said that in 1922, they came to study us, they are still studying us…a lot of paper, but no product…research for the sake of research, doesn’t do us any good”

Community Advocate at

Meeting How can we promote

health as a system that connects ethics with new research endeavors in communities?

How can we facilitate translation & dissemination of research?

Challenges

Research Training Dissemination

Empowerment at all levels of social ecological framework

Understand multiple social & ecological determinants

Integrate community representation in all facets of research

EthicalBenchmarks

Ethical Evaluation of Fairness: Equity, Efficiency, AccountabilityEthical Evaluation of Fairness: Equity, Efficiency, Accountability

Scientific Evaluation: Efficacy & EffectivenessScientific Evaluation: Efficacy & EffectivenessScientific

Benchmarks

A combined health disparity framework using ethical & scientific evaluations

Research Training Dissemination

❸What Interventions To Develop?

Presented at the American Public Health Association 140th Annual Meeting

San Francisco, California

New Era Of Ethics,

Efficiency, Effectiveness

Policy

Promote Awareness – Appreciation for Heterogeneity of

Hispanics

Research –Evaluation

Integration of Systems For

Social Change

Make Systems of health care more

accessible, affordable and accountable

Practice-Advocacy

New Paradigm for Health Equity

Strengthening the Community Approach

Build Community Models- Bring Social-Economic PoliciesBegin The Journey of Intersection between health and wellness, prevention-controlOne approach: The Community Health Worker Model, bring costs down, more access, better quality of care

by Paulina Matias, TX

Individuals

CHW Model

Border CommunitiesSociety

Synergy and Cooperation: CHW Model Influencing Change in

Border Communities

Family

The HEART Participant’s EnvironmentBalcazar et al. 2012 Prev Chronic Dis Vol 9 (11_0100)

www.kentonthemove.org/img/Socio-EcologicalMod..

Policy Agents: Policy makers

Community Agents: Community members, leaders

Organizations Agents: YWCA, Parks and Rec Dept., CHALC, UT

—El Paso, UT-SPH, Centro San Vicente, EPCC

InterpersonalAgents: CHWs, family, friends, social networks

IndividualAgents: HEART participant

Evaluation

Interven

tion

CBPR Context

Final Reflections

How do move forward integrated and well-defined community – population health interventions for a variety of Hispanic subgroups?Need to address complexity!Need to move beyond assumptions-border

fluidity- new dynamics i.e. use of health systems in both countries, medicationsLearn from resilience- family dynamics, Social capital, Ethics- Social Justice not a Cliche

THANKS To HHDRC and TEAM

Work Supported by P20MD002287 NIH- NIMHHD