Volume 66 Issue 1

In This Issue

Texas Public Health JournalA quarterly publication of the

Texas Public Health Association (TPHA)

Volume 66, Issue 1 Winter 2014

Please visit the Journal page of our website at http://www.texaspha.orgfor author information and instructions on submitting to our journal.

Texas Public Health AssociationPO Box 201540, Austin, Texas 78720-1540 phone (512) 336-2520 fax (512) 336-0533

Email: [email protected]

“The articles published in the Texas Public Health Journal do not necessarily refl ect the offi cial policy or opinions of the Texas Public Health Asso-ciation. Publication of an advertisement is not to be considered an endorsement or approval by the Texas Public Health Association of the product or service involved.

Subscriptions: Texas Public Health Journal, PO Box 201540, Austin, Texas 78720-1540. Rates are $75 per year. Subscriptions are included with memberships. Membership application and fees accessible at www.texaspha.org. Please visit the journal page for guidelines on submitting to the Texas Public Health Journal.”

President’s Message 2

TPHJ Index 2013 3

Commissioner’s Comments 8

Krokodil: An Urban Legend in the United States So Far 9

Youth Suicide in Texas – A Call to Action 10

A Voluntary Approach to Improve Menu Options in Restaurants Through a Local Collaborative Partnership 11

Barriers to Physical Activity Education for Cancer Survivors: A Survey of English and Spanish Speaking Promotores/Community Health Workers in Texas 15

Excessive Alcohol Consumption Among Adults with Chronic Medical Conditions in Texas 20

Spatial Analysis of Cardiovascular Disease Mortality and Exposure to PM2.5 in Harris County, Texas 25

GIS Day, Texas Department of State Health Services, Austin, Texas, November 20, 2013 34

2 TPHA Journal Volume 66, Issue 12

Catherine Cooksley, DrPH - EditorTerri S. Pali - Managing Editor

Editorial BoardKaye Reynolds, MPH - Co-chairCarol Galeener, PhD - Co-chair

Jean Brender, RN, PhDAmol Karmarker, PhDKimberly Fulda, DrPH

Mathias B. Forrester, BSCarolyn Medina, MA, MLIS

Kathryn Cardarelli, PhD

TPHA Offi cersAlexandra Garcia, PhD, RN, FAAN,

PresidentJames Swan, PhD, President-Elect

Cindy Kilborn, MPH, M(ASCP), First Vice President

Melissa Oden, DHEd, LMSW-IPR, MPH, CHES, Second Vice-President

Kaye Reynolds, MPH, MT (ASCP), Immediate Past President

Executive BoardThree Years

Rita Espinoza, MPHDebbie Flaniken

Two YearsCharla Edwards, RN, BSN, MSHP

Robert L. DrummondOne Year

Linda Kaufman, MSN, RN, CSJennifer Smith, MSHPBen G. Raimer, MD

Terri S. Pali, Executive Director

Governing CouncilThree Years

Bobby D. Schmidt, MEdSandra H. Strickland, DrPH, RN

Rachel Wiseman, MPHTwo Years

Patricia Diana BrooksCarol M. Davis, MSPH, CPH

Julie HerrmannOne Year

Marcia Becker, PhD, MPH, PMP, CPHMichael Hill, MPH, MPA, FACHE

Matthew Weaver, PhD

Section Chairs:Vacancy-Administration & Management

Laura Wolfe, PhD-Aging and Public HealthRachel Wiseman, MPH-Epidemiology

Terry Ricks, RS-Environmental & Consumer Health

Deborah Flaniken-Health EducationVacancy-Public Health NursingArianne Rhea-Student Section

ParliamentarianBobby Jones, DVM, MPH, DACVPM

Affi liate Representative to theAPHA Governing CouncilCatherine Cooksley, DrPH

John R. Herbold, DVM, MPH, PhD(Alternate)

Journal TypesettingCharissa Crump

President’s MessageDr. Alexandra Garcia

Many of us have begun the New Year by making resolu-tions to improve our personal health prac-tices in 2014. TPHA members can also take actions to help all our fellow Texans be healthier, because as individuals and as

an organization, we can be, and should be, ad-vocates for healthy policies.

Some of us are not comfortable acting as advo-cates because of the close link advocacy shares with politics. Rightfully, most employees are prohibited from using their work time and re-sources for effecting political changes. How-ever, we can be advocates for public health issues without electioneering.

As advocates, we rely on data – the observa-tions and measurements of health trends and practices. It is vital that we gather, manage, and analyze data. We should interpret the fi ndings for policy makers as well as for the general public – for anyone and everyone who can infl uence policies. Without accurate data gathering and analysis, and data presentation, policies can be enacted based only on personal opinions or political agendas.

Some public health professionals are surprised that policies can be driven by politics rather than facts. Fact-checking is part of our health advocacy work. We don’t want false claims to trump data. Policy makers and media outlets don’t always have the time or the resources to verify news reports and, as a result, listeners/readers/viewers are presented with misinfor-mation that forms the basis for public opinion. Given these circumstances, it is especially im-portant that public health professionals speak out to lay people, community groups, health care professionals, and policy makers and con-vey accurate, data-based information. Rather than lobbying or politicking for one policy or another, public health professionals inform policy makers and the public in general just what the facts show about the impact of pro-posed and enacted policies.

TPHA advocates for healthy policies through its support of the Texas Public Health Coali-tion. But each of us can resolve to be fact gath-erers and promoters when we see the need. All of us have access to credible data sources. For instance, the America’s Health Rankings website (http://www.americashealthrankings.

Mbbtiptimtaalba

org) presents weighted data to allow compari-sons across states. In comparison to all other states Texas ranks 22nd in infant mortality rate (about 6 deaths per 1000 live births), 33rd in low birthweight babies (8.5%), 32nd in obe-sity (29.2% of adults), 42nd in physical inac-tivity (27.2%), 34th in preventable hospitaliza-tions (67.9 per 1000 Medicare enrollees), 43rd in primary care physicians (95.3 per 100,000 population), and 50th in residents lacking em-ployer-sponsored, government-provided, or private health insurance (24.2% in 2013). This sampling of indicators provides a compelling way to examine the impact of health and social policies.

This past November, I attended the American Public Health Association’s annual conference in Boston, MA to represent TPHA as an affi li-ate of the national organization. While there I participated with other state affi liate offi cers and members in advocacy skill-training work-shops. We practiced focusing the information we wanted to present and organizing it into a compelling story. APHA facilitated visits with congressional legislators and their aides and helped us plan strategies for communicating public health messages in blogs and editorials.

In the APHA opening session Sarah Wedding-ton, attorney, professor, and former Texas state legislator exemplifi ed advocacy at the highest level. She rallied the attendees to “leave our thumbprints” on public health through advoca-cy for healthier policies. Many attendees came away with renewed inspiration, knowledge, tools, and new friendships.

We hope that you will fi nd equal inspiration and support at the TPHA Annual Education Conference March 24-26 in Corpus Christi, TX. The program planning committee has invited public health and policy experts who will prepare TPHA members to be informed advocates for Texas.

Please make advocacy part of your 2014 New Year resolutions. Commit to writing at least one letter or email to a legislator or news edi-tor or to make one visit to a State Legislator or community group. Let’s see what happens when every TPHA member uses data to de-scribe impacts of policies on Texans’ health. TPHA is the voice for public health in Texas but we need to be in more conversations. Let’s say what needs to be said for Texans’ health.

TPHA Journal Volume 66, Issue 1 3

Texas Public Health Journal Index for 2008 - 2012

Title Author 1 Volume Issue Year Pages President's Message Reynolds, Kaye M. 64 4 Fall, 2012 p. 2

Commissioner's Comments: State Supports Local Efforts to Battle West Nile

Lakey, David L. 64 4 Fall, 2012 p. 3

West Nile Virus Activity from the Front Lines in Texas Texas Public Health Association 64 4 Fall, 2012 p. 3-5 Public Health Emergency Response to a Massive Wildfire in Texas (2011) Zane, David F. 64 4 Fall, 2012 p. 6-10 Evaluation of a Health Department Sponsored Community Garden in Houston/Harris County

Yang, Biru 64 4 Fall, 2012 p. 10-12

The Texas-Kenya Health Nexus: A Story over Five Decades in the Making Galeener, Carol 64 4 Fall, 2012 p. 13 Changes in Texas Poison Center Call Patterns in Response to H1N1 Influenza Outbreak

Forrester, Mathias B. 64 4 Fall, 2012 p. 14-18

Assessment of a Child Injury Prevention Intervention in the Texas-Mexico Border

Garza, Norma 64 4 Fall, 2012 p. 19-22

College Students' Perceptions of HIV Risk, Importance of Protective Behaviors, and Intentions to Change Behavior after Attending an HIV/AIDS Awareness Event

Smith, Matthew Lee 64 4 Fall, 2012 p. 23-29

The Relationship between Hurricane Ike Residency Damage or Destruction and Intimate Partner Violence among African American Male Youth

Meshack, Angela 64 4 Fall, 2012 p. 30-33

Back to School Poison Control Alert: Adverse Effects from Ingestion of Energy Drinks


Dr. R. Palmer Beasley Remembered Texas Public Health Association 64 4 Fall, 2012 p. 35-36 Texas Public Health Training Center News Crider, Nancy 64 4 Fall, 2012 p. 36 TPHA News and Information Texas Public Health Association 64 4 Fall, 2012 p. 37-39 President's Message Reynolds, Kaye M. 64 3 Summer, 2012 p. 2 Adoption of Information Technology in Texas Nursing Homes Nauert, Rick 64 3 Summer, 2012 p. 5-11 A Rural Local Health Department's Journey toward Selecting an Electronic Health Record

McCullough, Debra 64 3 Summer, 2012 p. 12-17

A Comparative Study of Pesticide Use in Homes of Pregnant Women Living at the Texas-Mexico Border and in New York City

Tapia, Beatriz 64 3 Summer, 2012 p. 18-23

Social Determinants of Health: Implications for Public Health, Medical and Social Interventions; Summary of Audience Discussion

Loe, Hardy 64 3 Summer, 2012 p. 24-29

Radiology and Public Health: Past and Present Wainerdi, Richard E. 64 3 Summer, 2012 p. 30-31 The Evolving Face of Radiation as a Public Health Issue Galeener, Carol 64 3 Summer, 2012 p. 32-33 Women's Work Preparing for Disasters in the United States Medina, Carolyn 64 3 Summer, 2012 p. 33-34 Are Poison Ivy (Toxicodendron Radicans) Exposures Becoming More Serious in Texas

Forrester, Mathias B. 64 3 Summer, 2012 p. 35

Texas Black Widow Spiders Take the Heat Forrester, Mathias B. 64 3 Summer, 2012 p. 36 Potential Pediatric Hazard: New Laundry Detergent Packs or Pods Forrester, Mathias B. 64 3 Summer, 2012 p. 37 Texas Public Health Training Center News Crider, Nancy 64 3 Summer, 2012 p. 38 TPHA News and Information Texas Public Health Association 64 3 Summer, 2012 p. 39-42 TPHA AEC in Pictures Texas Public Health Association 64 3 Summer, 2012 p. 43 President's Message Schmidt, Bobby 64 2 Spring, 2012 p. 2 Commissioner's Comments: Transforming Chronic Disease Prevention in Texas

Lakey, David L. 64 2 Spring, 2012 p. 3

Respiratory and Reproductive Health in Women Near Confined Animal Feeding Operations in the American Southwest

Gibbs, Shawn G. 64 2 Spring, 2012 p. 4-11

Evaluation of Selected Ambient Air Pollutants as a Potential Predictor of Seasonal Fungal and Bacterial Airborne Concentrations in El Paso, Texas

Mota, Linda C. 64 2 Spring, 2012 p. 12-19

Challenges Associated with Assessment and Use of Mammography Screening Rates in Rural West Texas

Zhang, Yan 64 2 Spring, 2012 p. 20-24

The Importance of Data to Public Health: An Introduction Medina, Carolyn 64 2 Spring, 2012 p. 25-28 Data to Action: Reducing Adult Potentially Preventable Hospitalizations in Texas

Gilliam, Mike 64 2 Spring, 2012 p. 29-30

An Assessment of the Distribution of Physicians in Texas King, Brian 64 2 Spring, 2012 p. 31-34 Mortality of Public Mental Health Clients Treated at the Local Mental Health Authorities of Texas

Reynolds, Robert J. 64 2 Spring, 2012 p. 35-40

Potassium Iodide and Its Use in Radiation Protection Forrester, Mathias B. 64 2 Spring, 2012 p. 41 Product Recalls as a Public Health Problem Forrester, Mathias B. 64 2 Spring, 2012 p. 41-42 TPHA News and Information Texas Public Health Association 64 2 Spring, 2012 p. 43

From the Editor: Happy New Year TPHJ Readers! In the Fall 2013 issue we published an index of all the articles publishedin 2013. We now provide another fi ve years of indexed articles dating back through 2008. We hope this will give our readers an overallpicture of the value of this publication for public health professionals. This year we will continue to strive to meet the requirements forPubMed inclusion. We would welcome any assistance from those of you who have experience in this. As always, our goal is to meet yourexpectations and we hope to hear from you.


President's Message Schmidt, Bobby 64 1 Winter, 2012 p. 2 Commissioner's Comments: Healthy Babies, Healthy Texas Lakey, David L. 64 1 Winter, 2012 p. 3 The Evaluation of a Car Seat Installation Education Program: Results of a Pilot Study

Robertson, Brian D. 64 1 Winter, 2012 p. 4-7

The Association between Anti-Energy Drinks and Illicit Drug Use among Fifth Ward Houstonian Youth

Peters, Jr., Ronald J. 64 1 Winter, 2012 p. 8-11

Smallpox Inoculation and the Ottoman Contribution: A Brief Historiography

Aboul-Enein, Basil H. 64 1 Winter, 2012 p. 12-14

Winter 2012 Poison Control Information Forrester, Mathias B. 64 1 Winter, 2012 p. 15-17 TPHA and Future Public Health Professionals Oden, Melissa 64 1 Winter, 2012 p. 18-19 Texas Public Health Training Center News Crider, Nancy 64 1 Winter, 2012 p. 20 TPHA News and Information Texas Public Health Association 64 1 Winter, 2012 p. 20-27 President's Message Schmidt, Bobby 63 4 Fall, 2011 p. 2 Commissioner's Comments: Knowing and Protecting Lakey, David L. 63 4 Fall, 2011 p. 3 Treatment as a Form of HIV Prevention: Commentary White, Margaret H. 63 4 Fall, 2011 p. 4-5 TPHA Scholarship Recipient Essay 2011 Kaufman, Andrea 63 4 Fall, 2011 p. 5 A Review of the Public Health Agency Accreditation Literature Part II McCullough, Debra 63 4 Fall, 2011 p. 6-9 Implementation and Evaluation of a 2-1-1 Texas Awareness Campaign Diep, Cassandra S. 63 4 Fall, 2011 p. 10-13 Home Hazards Assessment among Elderly in South Texas Colonias Zuniga, Carrillo 63 4 Fall, 2011 p. 14-17 Texas Public Health Training Center News Crider, Nancy 63 4 Fall, 2011 p. 29-30 Nutmeg: An Unexpected Substance of Abuse Forrester, Mathias B. 63 4 Fall, 2011 p. 26-27 Potential Hazard of Button Battery Ingestions by Young Children Forrester, Mathias B. 63 4 Fall, 2011 p. 27 American Mistletoe Ingestions: A Potentially Toxic Winter Exposure Forrester, Mathias B. 63 4 Fall, 2011 p. 27-28 Estimating the Cost of Cancer Care for a State Tan, Alai 63 4 Fall, 2011 p. 18-21 African American Teenage Smoking Attitudes and Beliefs toward Cigarette Smoking Cessation Program Advertisements: "Putting Emphasis on the Real"

Peters Jr., Ronald J. 63 4 Fall, 2011 p. 22-25

What's in My Food and Water? Medina, Carolyn 63 4 Fall, 2011 p. 28-29 TPHA News and Information Texas Public Health Association 63 4 Fall, 2011 p. 30-39 President's Message Schmidt, Bobby 63 3 Summer, 2011 p. 2 Commissioner's Comments: The Faces of Disasters Lakey, David L. 63 3 Summer, 2011 p. 3-4 A Review of the Public Health Agency Accreditation Literature Part I McCullough, Debra 63 3 Summer, 2011 p. 5-6 Peanut Butter Recall Calls Received by Texas Poison Centers Forrester, Mathias B. 63 3 Summer, 2011 p. 7-10 Novel Activity Reduces Nursing Home Depression Nauert, Rick 63 3 Summer, 2011 p. 11-14 Not Everything Behaves in Moderation: Drought and Flood in Texas Medina, Carolyn 63 3 Summer, 2011 p. 15-16 Summer Poison Control Alerts Forrester, Mathias B. 63 3 Summer, 2011 p. 16-18 TPHA News and Information Texas Public Health Association 63 3 Summer, 2011 p. 18-27 President's Message Babiak-Vazquez, Adriana 63 2 Spring, 2011 p. 2 Commissioner's Comments: A Healthy Texas Lakey, David L. 63 2 Spring, 2011 p. 3 Community-Based Participatory Approach to Reducing Perinatal Disparities in Tarrant County: the Aintie-Tia Progam

Cardarelli, Kathryn 63 2 Spring, 2011 p. 4-6

Pediatric Brain Injury: A Study of Pre-Hospital Transport in a Rural Texas County

Robertson, Brian D. 63 2 Spring, 2011 p. 7-11

The Social Norms of Texting and Driving among African American Young Adults

Peters, Jr., Ronald J. 63 2 Spring, 2011 p. 12-16

The Texas Public Health Journal Brings You Our Tribute to National Public Health Week, April 4-10, 2011

Texas Public Health Association 63 2 Spring, 2011 p. 17-18

Safety Is NO Accident: Live Injury Free Galeener, Carol 63 2 Spring, 2011 p. 19 How Texas Will Celebrate National Public Health Week April 4-8, 2011 Texas Public Health Association 63 2 Spring, 2011 p. 20-24 A TALHO White Paper (abridged) The Future of Public Health in Texas: A Summary Report

Troisi, Catherine L. 63 2 Spring, 2011 p. 25-29

An Offer Cash-Strapped Lawmakers Can't Refuse: Save Money, Save Lives Texas Public Health Coalition 63 2 Spring, 2011 p. 29-30 Student Opinion/Editorial Pieces Illustrate the Breadth of Public Health Galeener, Carol 63 2 Spring, 2011 p. 31-36 Oleander: A Poisonous Plant that Does Not Live Up to Its Urban Legend Forrester, Mathias B. 63 2 Spring, 2011 p. 36-37 The Long and Winding Road to Automobile Safety Medina, Carolyn 63 2 Spring, 2011 p. 37-38 Around Texas Texas Public Health Association 63 2 Spring, 2011 p. 39 Texas Public Health Training Center News Crider, Nancy 63 2 Spring, 2011 p. 39-40 TPHA News and Information Texas Public Health Association 63 2 Spring, 2011 p. 40-43 Message from TPHA's President and Executive Director Texas Public Health Association 63 1 Winter, 2011 p. 2 Commissioner's Comments: Money Matters Lakey, David L. 63 1 Winter, 2011 p. 3 Health Disparities McLeroy, Kenneth R. 63 1 Winter, 2011 p. 4-7 Rural and Minority Disparities Guidry, Jeffrey J. 63 1 Winter, 2011 p. 7 An Investigative Study on Health Disparities- Related Research at Texas A&M University System Institutions

Arthur, Tya M. 63 1 Winter, 2011 p. 8-11

Dissemination of a Low-literacy Diabetes Education Kiosk Tool in South Texas to Address Diabetes Health Disparities

Bolin, Jane N. 63 1 Winter, 2011 p. 12-15

Geospatial Characteristics of the Chronic Disease Self-Management Program: Reaching Diverse Ethnic Populations in San Antonio, Texas

Salazar, Camerino I. 63 1 Winter, 2011 p. 16-20

Too Sad to Care: The Relationship between Depression-Related Symptoms and Delay in Seeking Medical Care

Hill, Mandy 63 1 Winter, 2011 p. 21-27

Incidence of Breast Cancer in Hispanic and White Women in a Large County on the Texas-Mexico Border

Rajkumar, Lakshmanaswamy 63 1 Winter, 2011 p. 28-34


A Skin Cancer Prevention and Early Detection Program Disseminated through Cosmetologists using Evidence-Based Curriculum: Talkin' about Better Skin (TABS)

Dorman, Melody 63 1 Winter, 2011 p. 35-38

Concept Analysis of Nutritional Literacy: The Association between Nutritional Literacy and Childhood Obesity

Campbell, Lisa A. 63 1 Winter, 2011 p. 39-41

Si yo puedo! (Yes I Can!): Investigating Low-Income Hispanic Caregivers' Consumption of Fruits and Vegetables and Their Knowledge and Efficacy to Feed Them to Their Children

Ettienne-Gittens, Reynolette 63 1 Winter, 2011 p. 42-45

Development and Testing of the Texas WIC's Food and Nutrition Questionnaire

McKyer, E. Lisako J. 63 1 Winter, 2011 p. 46-49

Reaching At-Risk Populations to Improve Clinical Measures of Physical Activity: Delivery of EnhanceFitness to Low-Income African American Adults in Houston, Texas

Smith, Matthew Lee 63 1 Winter, 2011 p. 50-53

Serving Rural Communities for Falls Prevention: The Dissemination of a Matter of Balance in the Brazos Valley Region of Texas


A Brief Report of College Student Health within a Historically Black College and University

Hale, William Davis 63 1 Winter, 2011 p. 59-61

Why Do We Count What We Count? Medina, Carolyn 63 1 Winter, 2011 p. 62-63 Poinsettia Ingestions by Young Children: A Non-Toxic Wintertime Exposure

Forrester, Mathias B. 63 1 Winter, 2011 p. 63-64

Texas Public Health Training Center News Crider, Nancy 63 1 Winter, 2011 p. 64 TPHA News and Information Texas Public Health Association 63 1 Winter, 2011 p. 65-67 President's Message Babiak-Vazquez, Adriana 62 4 Fall, 2010 p. 2 Book Review: Predictably Irrational, Revised and Expanded Edition: The Hidden Forces that Shape Our Decisions

Galeener, Carol 62 4 Fall, 2010 p. 3

Identification of Overweight in Young Children: Is Use of Body Mass Index Percentiles Alone Sufficient?

Boylan, Mallory 62 4 Fall, 2010 p. 4-8

Disaster Preparedness Program Evaluation at a Senior Center: Implications for Community Partnerships Serving Ethnically Diverse Older Adults

Grizzle, Rebecca W. 62 4 Fall, 2010 p. 9-11

Health Care in the Texas Prison System: A Looming Fiscal Crisis Raimer, Ben G. 62 4 Fall, 2010 p. 12-17 Community Outbreak of Acute Hepatitis B Detected by the Infection Control Program at a Public Hospital System

Sreeramoju, Pranavi V. 62 4 Fall, 2010 p. 18-22

An Evaluation of Water Quality Indicators for Cypress Creek, A Major Tributary of Lake Houston

Standlee, Courtney Rose Bock 62 4 Fall, 2010 p. 23-29

Concentrations of Inorganic Chemicals in Cypress Creek, A Major Tributary of Lake Houston

Vigilant, Maximea E. 62 4 Fall, 2010 p. 30-36

Real Talk for Real Girls: Enhancing Communication between Mothers and Daughters about Sexual Health Issues

Oden, Melissa 62 4 Fall, 2010 p. 37-38

Hip Hop for HIV Awareness McNeese-Ward, Marlene 62 4 Fall, 2010 p. 39-40 Mummy Dust: Studying Ancient Diseases in a Modern World Medina, Carolyn 62 4 Fall, 2010 p. 41-42 Change in Glow Product Exposures Reported to Poison Control Centers on Halloween


Ciguatera Poisoning in Texas Forrester, Mathias B. 62 4 Fall, 2010 p. 47 Texas Public Health Training Center News Crider, Nancy 62 4 Fall, 2010 p. 48 News from the University of Texas Health Science Center Lloyd, Angela D. 62 4 Fall, 2010 p. 48 TPHA News and Information Texas Public Health Association 62 4 Fall, 2010 p. 49-51 President's Message Babiak-Vazquez, Adriana 62 3 Summer, 2010 p. 2 Commissioner's Comments: Our Job Is To Prepare, Respond and Recover Lakey, David L. 62 3 Summer, 2010 p. 3 Days of Haze Shah, Umair A. 62 3 Summer, 2010 p. 4-6 My Experiences in Haiti Hudson, Lynne 62 3 Summer, 2010 p. 7 Awareness and Perceived Usefulness of the Website Designed to Facilitate Access and Informed Health Insurance Decisions

Goyal, Ravi K. 62 3 Summer, 2010 p. 8-11

Identification of Overweight in Young Children: Is Use of Body Mass Index Percentiles Alone Sufficient?

Boylan, Mallory 62 3 Summer, 2010 p. 12-15

The Relation between Vitamin D and Depression in a Rural Dwelling Sample; A Projhect Frontier Study

Johnson, Leigh A. 62 3 Summer, 2010 p. 16-19

Dietary Intake and Body Mass Index in a Multi-Ethnic Sample of Adolescent Girls

Solomon, Abida B. 62 3 Summer, 2010 p. 20-24

Infamous Environmental Disasters of the Past Medina, Carolyn 62 3 Summer, 2010 p. 25-26 Potential Toxicity of Hand Sanitizers Forrester, Mathias B. 62 3 Summer, 2010 p. 27 Python: An Unusual Cause of Snake Bites in Texas Forrester, Mathias B. 62 3 Summer, 2010 p. 27-28 Texas Public Health Training Center News Crider, Nancy 62 3 Summer, 2010 p. 30-31 TPHA News and Announcements Texas Public Health Association 62 3 Summer, 2010 p. 31-36 Texas HIV/STD Conference, Awards Ceremonies Attract 850 Attendees Ogle, Shelly 62 3 Summer, 2010 p. 36-37 Building Bridges - Improving Health through Program Integration Loe, Hardy 62 3 Summer, 2010 p. 38 President's Message Brooks, Patricia Diana 62 2 Spring, 2010 p. 2 Commissioner's Comments: Tough Times, Hard Decisions Lakey, David L. 62 2 Spring, 2010 p. 3 How Texas Celebrates National Public Health Week Texas Public Health Association 62 2 Spring, 2010 p. 4-11 Physcial Activity Is Associated with Cognitive and Affective Status among Rural-Dwelling Texans: A Project FRONTIER Study

O'Bryant, Sid E. 62 2 Spring, 2010 p. 12-15

Physical Activity and Senior Centers in Texas Swan, James H. 62 2 Spring, 2010 p. 16-18


Impact of ENHANCE Study on Lipid-Lowering Agent Exposures Reported to Texas Poison Centers

Forrester, Mathias B. 62 2 Spring, 2010 p. 19-21

Body Art and the Primary Care Provider's Responsibilities Miller,. Virginia G. 62 2 Spring, 2010 p. 22-27 Evaluating the Impact of the Fitness in Nutrition and Exercise (FINE) Program within Shared Medical Appointments (SMA) on Reducing Childhood Obesity in a Community-Based Clinic

Gimpel, Nora 62 2 Spring, 2010 p. 28-31

Pertussis among Children and Adolescents with Persistent Cough in El Paso - Cd. Juarez

Dominguez, Delfina C. 62 2 Spring, 2010 p. 32-37

Parent Teacher Organizations as Partners To Reduce Obesity and Prevent Diabetes in a Hispanic Community

Harris, Amy 62 2 Spring, 2010 p. 38-40

The Red Cross: Always There in a Time of Need Medina, Carolyn 62 2 Spring, 2010 p. 41-42 Poisoning among the Elderly in Texas Forrester, Mathias B. 62 2 Spring, 2010 p. 42-43 TPHA News and Announcements Texas Public Health Association 62 2 Spring, 2010 p. 43-50 President's Message from the Editor Cooksley, Catherine 62 1 Winter, 2010 p. 2 Commissioner's Comments: Thanks and Think Lakey, David L. 62 1 Winter, 2010 p. 3 Falls Prevention: Public Health Approaches at the Local, State, and National Levels

Ory, Marcia G. 62 1 Winter, 2010 p. 4

Initiatives to Prevent Falls among Older Americans: A National Perdpective

Beattie, Bonita Lynn 62 1 Winter, 2010 p. 5-6

Falls among Older Adults in Texas; Profile from 2007 Hospital Discharge Data


Building a Statewide Coalition for Falls Prevention: The Texas Experience Parrish, Reuben 62 1 Winter, 2010 p. 14 Addressing Falls in Texas: Evidence-Based Fall Prevention Programming for Older Texans

Ory, Marcia G. 62 1 Winter, 2010 p. 15-20

Local Perspectives on the Implementation of an Evidence-Based Falls Prevention Program: The Brazos Valley Experience

Gipson, Ronnie 62 1 Winter, 2010 p. 21

Commentary: The Primary Care Physician Shortage Calls for an Expanded Role of Physician Assistants and Nurse Practitioners in the Health Care System

Crowell, Eric 62 1 Winter, 2010 p. 22-23

Use of Household Safety Devices among South Texas Colonia Residents Zuniga, Carrillo 62 1 Winter, 2010 p. 24-27 A One Page History of Medicare and Medicaid Medina, Carolyn 62 1 Winter, 2010 p. 28 Books on Health Care Reform Medina, Carolyn 62 1 Winter, 2010 p. 29-30 Texas Public Health Training Center News Crider, Nancy 62 1 Winter, 2010 p. 30-31 TPHA News and Announcements Texas Public Health Association 62 1 Winter, 2010 p. 32-35

President's Message Brooks, Patricia Diana 61 4 Fall, 2009 p. 2-3 Commissioner's Comments: The Time Has Come Lakey, David L. 61 4 Fall, 2009 p. 3-4 Texas Public Health Training Center News Crider, Nancy 61 4 Fall, 2009 p. 4-5 Around Texas Texas Public Health Association 61 4 Fall, 2009 p. 5-6 TPHA News and Announcements Texas Public Health Association 61 4 Fall, 2009 p. 7-11 The Human Side of a Disaster Medina, Carolyn 61 4 Fall, 2009 p. 12-13 Texas Public Health Association APHA Affiliate Capacity-Building Initiative Texas Public Health Association 61 4 Fall, 2009 p. 13 Introduction to Public Health Preparedness Herbold, John 61 4 Fall, 2009 p. 14-21 Syndromic Surveillance in Texas: A Brief Overview of Current Activities Calcote, Joshua C. 61 4 Fall, 2009 p. 22-24

Risk Communication Considerations for Volunteer Surge Capacity Disaster Response Organizations

Emery, Robert J. 61 4 Fall, 2009 p. 25-29

Viral Vector-Borne Diseases in Texas and Effective Surveillance Strategies Grimes, Carolyn Z. 61 4 Fall, 2009 p. 30-32

A Graduate Student Epidemiology Response Program's Partnership with Local Health Departments to Meet H1N1 Surge Capacity Needs

Montealegre, Jane R. 61 4 Fall, 2009 p. 33-34

School Closures as a Mechanism for Interruption of Novel Influenza A H1N1 Transmission: The Denton County Experience

Gullion, Jessica Smartt 61 4 Fall, 2009 p. 35-38

Emergency Preparedness and Response Considerations for the Geriatric Population

Barney, Carolyn E. 61 4 Fall, 2009 p. 39-41

Applying Informatics to Improve Vulnerable Population Registration for Emergency Preparedness in the Gulf Coast Region of Texas

Phosuwan, Akom 61 4 Fall, 2009 p. 42-47

The Pandemic Influenza Preparedness Planning Project: An Evaluation of Strategies for Engaging Rural Community Partners

Artzberger, Jill J. 61 4 Fall, 2009 p. 48-51

Voluntary Infectious Disease Precautions and Non-Pharmaceutical Interventions among Students at a University in Texas during the Spring 2009 Novel H1N1 Outbreak

Zottarelli, Lisa K. 61 4 Fall, 2009 p. 52-57

Assessing Public Health Preparedness in Texas Local Health Departments Langabeer, James R. 61 4 Fall, 2009 p. 58-63 Advocacy in Action - The Public Health Legislative Breakfast Series 2009 Shaw, Sharon 61 4 Fall, 2009 p. 64-66 President's Message Brooks, Patricia Diana 61 3 Summer, 2009 p. 2 Commissioner's Comments: Preparing for the Unpredictable H1N1 Flu Lakey, David L. 61 3 Summer, 2009 p. 3

Trend Analysis of the Supply of Primary Care Physicians in Rural and Urban East, South, and West Texas from 1981 to 2007

Gong, Gordon 61 3 Summer, 2009 p. 4-8

Change in Glow Product Exposures Reported to Poison Control Centers on Halloween

Forrester, Mathias B. 61 3 Summer, 2009 p. 9-11

Evaluation of the Harris County Hospital District Ask Your Nurse Advice Line

Johnson, Jr., Charles D. 61 3 Summer, 2009 p. 12-15

Treatment of Obesity by Herbal Mixtures Containing CNS Stimulants: Public Awareness of the Possible Harmful Effects

Al-Safi, Saafan A. 61 3 Summer, 2009 p. 16-21

Book Review and Interview with Author: Flatlined: Resuscitating American Medicine

Maserang, David 61 3 Summer, 2009 p. 22-24

Strange Epidemics: Human Suffering and Theories of Disease Medina, Carolyn 61 3 Summer, 2009 p. 25-26


Texas Public Health Training Center News Crider, Nancy 61 3 Summer, 2009 p. 26-27 TPHA News and Announcements Texas Public Health Association 61 3 Summer, 2009 p. 27-39 President's Message Hook, Linda 61 2 Spring, 2009 p. 2-3 Commissioner's Comments: A Time for Setting the Course of Public Health

Lakey, David L. 61 2 Spring, 2009 p. 3-4

TPHA News and Announcements Texas Public Health Association 61 2 Spring, 2009 p. 4 Texas Public Health Association Public Health Capacity Government/Policy Affairs

Committee 61 2 Spring, 2009 p. 5-7

A Healthy Texas Depends on Healthy Texans Texas Public Health Coalition 61 2 Spring, 2009 p. 8-15 The PHACT of What's Happening in Texas Troisi, Catherine L. 61 2 Spring, 2009 p. 16 Prenatal Care Adequacy and Adverse Birth Outcomes among Documented and Undocumented Hispanics in Texas

Thurman, Andrea Ries 61 2 Spring, 2009 p. 17-25

Exposures to Lipid-Lowering Agents Reported to Texas Poison Control Centers during 2002-2007

Forrester, Mathias B. 61 2 Spring, 2009 p. 26-28

Effect of Chamomile Tea on Maternal and Neonatal Outcomes in a Hispanic Population Living on the Texas-Mexico Border

Glidden, Ainee J. 61 2 Spring, 2009 p. 29-35

Evaluation of a Community-Driven Program to Reduce Underage Drinking and Driving

Salazar, Camerino I. 61 2 Spring, 2009 p. 36-39

Early Mental Health Interventions following Disasters: What Is the Standard of Practice?

Talbott, William R. 61 2 Spring, 2009 p. 40-41

Book Review: Spin-Free Economics: A No-Nonsense, Nonpartisan Guide to Today's Global Economic Debate

Galeener, Carol 61 2 Spring, 2009 p. 42

Texas Celebrates National Public Health Week Texas Public Health Association 61 2 Spring, 2009 p. 43-61 Health Promotion in the Most Unusual Places Medina, Carolyn 61 2 Spring, 2009 p. 62 Texas Public Health Training Center News Crider, Nancy 61 2 Spring, 2009 p. 63 TPHA News and Announcements Texas Public Health Association 61 2 Spring, 2009 p. 63-66 President's Message Hook, Linda 61 1 Winter, 2009 p. 2 Commissioner's Comments: Remembering HIV Lakey, David L. 61 1 Winter, 2009 p. 3 The Cochran Country Aging Study: A Valuable Investment To Improve the Future of Aging and Health Care in Rural Communities

Waring, Stephen C. 61 1 Winter, 2009 p. 4

The Cochran County Aging Study: Methodology and Descriptive Statistics O'Bryant, Sid E. 61 1 Winter, 2009 p. 5-7 Rural West Texans: Healthcare Implications of "Living the Simple Life" Ashcraft, Alyce 61 1 Winter, 2009 p. 8-12 An Examination of Cardiovascular Disease Risk Factors in a Rural-Dwelling Ethnically Diverse Cohort

Zhang, Yan 61 1 Winter, 2009 p. 13-16

An Examination of Health-Related Gender Differences in a Rural-Dwelling Cohort

Zhang, Yan 61 1 Winter, 2009 p. 17-21

An Evaluation of the Age- and Education-Adjusted MMSE Scores among Rural Dwelling Mexican American Elders: The Cochran County Aging Study (CCAS)

Hobson, Valerie L. 61 1 Winter, 2009 p. 22-24

The Relation between Alcohol and Tobacco Use and Cognitive Function in the Cochran County Aging Study

Schrimsher, Gregory W. 61 1 Winter, 2009 p. 25-28

A Description of Migration Patterns and Disease Prevalence in the Cochran County Aging Study Cohort

Hargrave, Kris 61 1 Winter, 2009 p. 29-35

America the Grayt: A Quick History of Government's Role in Caring for the Elderly

Medina, Carolyn 61 1 Winter, 2009 p. 36-37

Texas Public Health Training Center News Crider, Nancy 61 1 Winter, 2009 p. 37 TPHA News and Announcements Texas Public Health Association 61 1 Winter, 2009 p. 37-46 From the Editor Cooksley, Catherine 60 4 Fall, 2008 p. 2 President's Message Hook, Linda 60 4 Fall, 2008 p. 2 Commissioner's Comments: Summer Storms Leave Their Mark on Texas Lakey, David L. 60 4 Fall, 2008 p. 3 Book Review: The Book of Alzheimer's for African-American Churches Walker, Pastor Thomas 60 4 Fall, 2008 p. 4 Using Collaboration to Develop a Faith Based Alzheimer's Caregiver Intervention in the African American Community

Paul, Janice 60 4 Fall, 2008 p. 4-8

Risk Assessment of Heterotrophic Plate Count (HPC) Bacteria in Potable Water Sources

Bristow, Zuzanne 60 4 Fall, 2008 p. 9-13

Value Organic Vapor Exposures During Drum Bulking at a University Hazardous Waste Facility

Vela Acosta, Martha S. 60 4 Fall, 2008 p. 14-17

North Texas School Health Surveillance: First-Year Progress and Next Steps

Lampman, Dean 60 4 Fall, 2008 p. 18-20

Prolonged Post-Disaster Crisis Intervention O'Brien, Dana 60 4 Fall, 2008 p. 21-23 Impact of Hurricane Dolly on Texas Poison Center Calls Forrester, Mathias B. 60 4 Fall, 2008 p. 24-26 Hurricane IKE Public Health Ready and Responsive Guidry, Harlan 60 4 Fall, 2008 p. 27-28 No New Thing under the Sun Medina, Carolyn 60 4 Fall, 2008 p. 29 Texas Public Health Training Center News Crider, Nancy 60 4 Fall, 2008 p. 30 TPHA News and Announcements Texas Public Health Association 60 4 Fall, 2008 p. 30-35 President's Message Hook, Linda 60 3 Summer, 2008 p. 2 Commissioner's Comments: Building More Community Mental Health Capacity

Lakey, David L. 60 3 Summer, 2008 p. 3

Editorial Introduction: Alzheimer's Disease Research and the Texas Alzheimer's Research Consortium

Petersen, Ronald C. 60 3 Summer, 2008 p. 4-5

The Economic Impact of Alzheimer's Disease in Texas: An Impending Crisis Fairchild, Thomas J. 60 3 Summer, 2008 p. 5-8 The Texas Alzheimer's Research Consortium Longitudinal Research Cohort: Study Design and Baseline Characteristics

Waring, Stephen C. 60 3 Summer, 2008 p. 9-13


Commissioner’s CommentsSunset Review: An Opportunity to Improve Texas Public HealthDavid L. Lakey, M.D.Commissioner, Texas Department of State Health Services

Some companies spend millions of dollars hiring outside consultants to take a hard look at their organizations – and ultimately recommend improvements to keep them moving forward. These are often dollars well spent to bring needed change and ensure they remain strong in the marketplace.

While we operate with different budget constraints, governmen-tal agencies also must demonstrate their relevance, effi ciency and strength.

Agencies in Texas are scrutinized through a process called Sunset review, an intensive review of the operations on a timeline set by the Texas Legislature, generally every 12 years. Since 1977, the Sunset process has been an important part of overseeing state agencies and ensuring state government operates effi ciently and effectively.

The Texas Department of State Health Services is in the midst of being reviewed by the Sunset Advisory Commission to determine if the agency needs to exist and to make recommendations for improve-ments. This is an incredible opportunity to evaluate our work and identify areas of improvement. Before the state’s health agencies un-derwent consolidation in 2004, the Texas Department of Health was reauthorized in 1999 following its Sunset evaluation. DSHS must be formally reauthorized by the Legislature in 2015.

Sunset staff members have been visiting our service sites, such as state hospitals and contractors, to encounter our agency fi rsthand. Along the way, we’ve presented large volumes of information and answered numerous questions about who we are, what we do and the important role public health plays in Texas. We recently completed our self-evaluation report, which is posted on the agency’s website

A Case for the Creation of a Biomarker-Based Algorithm for the Detection of Alzheimer's Disease

O'Bryant, Sid E. 60 3 Summer, 2008 p. 14-17

Hyperinsulinemia Type 2 Diabetes Mellitus and Cognitive Decline Rustveld, Luis O. 60 3 Summer, 2008 p. 17-22 The Relationship between Cardiovascular Risk Factors and Alzheimer's Disease

O'Bryant, Sid E. 60 3 Summer, 2008 p. 22-24

Depression and Alzheimer's Disease Hall, James R. 60 3 Summer, 2008 p. 25-29 Interview with Dr. Rachelle S. Doody Texas Public Health Association 60 3 Summer, 2008 p. 30-31 Resources on Alzheimer's Disease Medina, Carolyn 60 3 Summer, 2008 p. 31-32 Texas Public Health Training Center News Crider, Nancy 60 3 Summer, 2008 p. 32-33 TPHA News and Announcements Texas Public Health Association 60 3 Summer, 2008 p. 33-39 President's Message Hook, Linda 60 2 Spring, 2008 p. 2 Commissioner's Comments: Saving a Life with a Few Keystrokes Lakey, David L. 60 2 Spring, 2008 p. 3 Welcome to the TPHJ Spring 2008 Issue Cooksley, Catherine 60 2 Spring, 2008 p. 4 Practicum Experiences Give Public Health Students an Opportunity to Apply Their Academics


Student Research Highlighted at the Texas Public Health Policy Forum Texas Public Health Association 60 2 Spring, 2008 p. 12-17 Beyond the Genome - the Emergence of Proteomics: An interview of Dr. Robert E. Brown


Barriers to Distance Learning in South Texas: A Case Study Strickland, Sandra 60 2 Spring, 2008 p. 18-20 Pasa la Voz: Healthy Women Spread the Word about HIV Prevention Services

Ramos, Rebeca L. 60 2 Spring, 2008 p. 20-22

A Conference Model: Linking Health Professionals, Health Information and Communities Together

Wade, Ernestine 60 2 Spring, 2008 p. 22-24

The History of Schools of Public Health in Texas: Competition and Cooperation

Medina, Carolyn 60 2 Spring, 2008 p. 25-26

Texas Public Health Training Center News Crider, Nancy 60 2 Spring, 2008 p. 26-27 Highlights from the 2008 Public Health Policy Forum Texas Public Health Association 60 2 Spring, 2008 p. 27-29 TPHA News and Announcements Texas Public Health Association 60 2 Spring, 2008 p. 29-34 President's Message Strickland, Sandra 60 1 Winter, 2008 p. 2-3 Commissioner's Comments: Lakey, David L. 60 1 Winter, 2008 p. 3-4 Early Lessons Learned in the Development of a Childhood Overweight Prevention Program in West Texas Using Community Based Participatory Research

Reed, Debra B. 60 1 Winter, 2008 p. 4-8

Population Growth: An Appropriate Predictor of Water Demand? Vela Acosta, Martha S. 60 1 Winter, 2008 p. 8-12 Basic Statistics and Research Methods Training of Public Health Staff McCullough, Debra 60 1 Winter, 2008 p. 12-13 Organizational Capacity Assessment of Three Local Health Departments McCullough, Debra 60 1 Winter, 2008 p. 13-17 Socioeconomic, Behavioral, and Health-Related Determinants of Self-Reported Depression in the City of Fort Worth

Migala, Witold 60 1 Winter, 2008 p. 17-21

Measuring Board Activity in Governance of Not-For-Profit Healthcare Langabeer, James R. 60 1 Winter, 2008 p. 22-25 Book Review: Redefining Health Care: Creating Value-Based Competition on Results

Galeener, Carol 60 1 Winter, 2008 p. 26

The War on Cancer in America: Private and Public Armies Medina, Carolyn 60 1 Winter, 2008 p. 26-28 Texas Public Health Training Center News Crider, Nancy 60 1 Winter, 2008 p. 28-29 TPHA News and Announcements Texas Public Health Association 60 1 Winter, 2008 p. 29-39


Krokodil: An Urban Legend in the United States So FarMathias B. Forrester1, Jane Carlisle Maxwell2

1Texas Department of State Health Services, Austin, Texas2The University of Texas, Austin, TexasSince September 2013, there has been media coverage in the US about a home-made injectable drug used in Russia and the Ukraine. Known on the street as “Krokodil,” “Krok,” “Crocodile,” “Croc,” and “Russian heroin,”1,2 its primary ingredient is desomorphine, an opioid analogue fi rst synthesized in the US in 1932.3 Desomorphine has sedative and analgesic properties similar to heroin and is ten times as potent as morphine.4-7

It is cheap to make and can be synthesized at home from easily ob-tained ingredients such as codeine, iodine, lighter fl uid, paint thin-ner, hydrochloric acid, or red phosphorus.2,8-10 Since no fi ltering is involved in the production process, the fi nal product is a suspension containing desomorphine and contaminants comprised of the other agents involved in the production process. Because of the contami-nants, Krokodil use leads to serious adverse effects: skin in the loca-tion of the injections becoming grey and green, scabrous, and fl aky resembling a crocodile’s scales, hence its street name; damage to blood vessels, muscles, and bones resulting in abscesses; thrombo-phlebitis; gangrene; and necrosis.2,8,9

Krokodil abuse fi rst appeared in Russia around 2002.9 While im-ported Afghan heroin has gradually replaced home-produced drugs in many Russian cities, the practice of home cooking remained com-mon in the Ukraine, where availability of heroin was low.11 With its rapid onset and short duration of its action, frequent injections are necessary to prevent withdrawal, and sharing needles increases the chances of infection. In addition, opiate substitution programs that use methadone or buprenorphine to treat opiate addiction are not available in Russia.

In September 2013, Arizona health offi cials reported two cases in one week, but these cases were considered “anecdotal” by the Drug Enforcement Administration (DEA).12 Additional cases were report-ed around the US during September and October 2013; however, as of October 2013, no cases of desomorphine have been identifi ed by the DEA’s National Forensic Laboratory Identifi cation System since four cases were identifi ed in 2004.13 As of December 2013, no clini-cally confi rmed exposures to desomorphine have been reported to Texas poison centers.

Krokodil abuse may not become a serious problem in the US be-cause over-the-counter codeine is not available, and the US has other

cheap opioids such as South American heroin, black tar heroin, and oxycodone. This is not to say that healthcare providers in the country might not encounter the consequences of Krokodil use. Obtaining samples and submitting them immediately to a forensic laboratory can minimize the anecdotal sightings and provide health offi cials with the creditable information that is needed to avoid another round of urban rumors.

Because of the serious adverse affects associated with injecting drugs, healthcare providers in the US need to be aware that injection wounds due to heroin or other drugs can look like Krokodil wounds. Healthcare providers need to obtain confi rmation of what drugs were injected, determine if they were “home-made,” the name of the sub-stance the user thought they were injecting, and what other drugs are present in the area where the user lived. Pathology tests can be used to determine if the wound is due to Methicillin Resistant Staphylo-coccus aureus (MRSA), sepsis, gangrene, necrosis, etc. The dangers of needle-sharing should be understood not only as a serious health risk for transmission of HIV/AIDS but also for other health conse-quences.

REFERENCES1. Gahr M, Freudenmann RW, Hiemke C, Gunst IM, Connemann BJ, Schön-feldt-Lecuona C. 2012. “Krokodil”-revival of an old drug with new problems. Subst Use Misuse 2012;47:861-863.2. Skowronek R, Celinski R, Chowaniec C. 2012. “Crocodile” - new danger-ous designer drug of abuse from the East. Clin Toxicol (Phila) 50:269.3. Small L, Yuen K, Eilers L. 1933. The catalytic hydrogenation of the ha-logenomorphides: Dihydrodesoxymorphine-D1. J Am Coll Cardiol 55:3863-3870.4. Casy A, Parfi tt R. 1986. Opioid analgesics: chemistry and receptors (1st ed.). New York: Plenum Press, p. 32.5. Sargent L, May E. 1970. Agonists-antagonists derived from desomorphine and metopon. J Mineralogy 13:1061–1063.6. Janssen P. 1962. A review of the chemical features associated with strong morphine-like activity. Br J Anaesth 34:260–268.7. Nathan EB, Homer HA. 1935. Studies of morphine, codeine and their de-rivatives X. Desoxymorphine-C, Desoxycodeine-C and their hydrogenated derivatives. J Pharmacol Exp Therapeut 55:257-267.8. Grund JP, Latypov A, Harris M. 2013. Breaking worse: The emergence of krokodil and excessive injuries among people who inject drugs in Eurasia. Int J Drug Policy 24:265-274.9. Shuster S. June 20, 2011. The curse of the crocodile: Russia’s dead-ly designer drug. Time. Available at http://www.time.com/world/arti-

and identifi es potential areas that could be addressed by Sunset. Do certain functions of DSHS detract from our public health focus? Do we have enough fl exibility in our ability to oversee the people and facilities we regulate? Are there ways to further integrate the health and human services system to improve effi ciency? The ultimate goal is to improve agency operations and service delivery and maintain focus on our mission to improve health and well-being in Texas.

As we go through this process, it is vital to continue to tell the story of what we do and why. We always recognize and emphasize our work with local health departments across the state. Whether it’s respond-ing to the recent dengue outbreak in the Rio Grande Valley, helping out with epidemiological injury analysis after the West explosion or fi ghting the fl u, supporting the local community’s response is mis-sion critical for DSHS and public health in Texas.

Local organizations have a major stake in the health of their com-munities, and Sunset staff members are soliciting input from stake-holder groups and the public about DSHS services and processes. We

welcome any and all feedback. I encourage local health department representatives to weigh in. The easiest way to do this is via the “Pro-vide Input for Staff” link at www.sunset.state.tx.us.

Between now and early 2014, Sunset staff will continue to meet with agency staff, request additional information as needed and gather in-put from stakeholders and the general public. We anticipate its fi nal report and recommendations will be published in mid-2014 followed by a public hearing. DSHS and members of the public will be able to respond to Sunset recommendations at that time, answering ques-tions and providing explanations and context for what we do and why. The Sunset Commission’s recommendations will be considered during the 84th Legislative Session.

DSHS is an extremely complex agency with a broad mission, and this is an opportunity to take a close look at ourselves and cast a wide net for feedback. It’s an opportunity to move forward. With the thoughtful feedback of those we serve, we’ll strengthen our public health mission in Texas.


cle/0,8599,2078355,00.html. Accessed on April 17, 2012.10. Savchuk S, Barsegyan S, Barsegyan I, Kolesov G. 2008. Chromatograph-ic study of expert and biological samples containing desomorphine. J Anal Chem 63:361–370.11. Booth RE. 2013. ‘Krokodil’ and other home produced drugs for injection: A perspective from Ukraine. Int J Drug Policy 24:277-278.12. United States Customs and Border Protection. October 23, 2013. Nogales POE Situational Alert: Krokodil/Crocodile Drug. PowerPoint Informational Alert.

Public Health Commentary: Youth Suicide in Texas – A Call to ActionLauren Gambill, MD“I was trying to kill myself.”

I’ve heard these words fi ve times from Texas children in the last month. As a physician, I have been fortunate enough to hear these words spoken by children more times than I ever imagined. I say “fortunate” in that these teens are still alive to speak, unlike the more than three hundred Texans under age 24 who succeed in committing suicide each year1. Obviously, however, there is nothing fortunate about the fact that in the last 12 months 15.8% of teens report they have seriously contemplated suicide and up to 7.8% of Texas high school students have attempted suicide2. Suicide is the third leading cause of death in people aged 15 to 24 (1). These are staggering sta-tistics indicating a huge public health problem that we must change.

There is also nothing “fortunate” about the devastation that a suicide attempt leaves in its wake. A suicide attempt means terrifi ed families sobbing at the bedside of a child who is barely recognizable; covered in tubes, IVs and loudly beeping monitors and machines. This lasts for days or weeks. Next, there is the rehabilitation and the re-integra-tion back into work and school, which often includes isolation and stigmatization. Finally, there is the paralyzing and very reasonable fear that this might all happen again. These are the “lucky” ones. Many successful suicides never even make it to the hospital.

Beyond the personal devastation, youth suicide impacts our entire society fi nancially. It is estimated that youth suicide deaths cost our country $6 billion annually3. So outside of the obvious reasons we need to worry about this public health issue, economically, it is criti-cal that something be done to aid in prevention.

Through all of this gloom, there is hope. Many individuals in our state are working diligently to continue to fi ght this huge public health problem. During the 2013 legislative session, two important bills were passed. Senate Bill 460 and Senate Bill 831 mandate in-creases in public school teacher’s training regarding the detection and education of students at risk for suicide4. This will hopefully improve our safety net, rescuing many of our children who might have otherwise fallen victim to suicide. However, with an average of three students per high school classroom attempting suicide, we should not sleep easy just yet.

The problem of teen suicide is complex but there are simple steps we can all take to help prevent one of the most common killers of our teens. There is no better time than now to join the fi ght, but how?

We must educate ourselves – By making ourselves aware of the defi -nite presence of teen suicide in our community and the risk factors associated with suicide, we may be able to identify an adolescent that no one else has realized is at risk. A few of the risk factors that place teens at a higher risk for suicide include: mental illness of any kind, previous suicide attempts, family history of suicide, history of abuse, stressful life events, identifying as LGBQT, having access to lethal

means, drug or alcohol use as well as, chronic illness or learning disability1,5. Many wonderful resources for education exist. We just have to look for them. www.TexasSuicidePrevention.org and www.MHATexas.org are great places to start.

We must talk openly – Many people are uncomfortable talking about suicide and mental health. With this huge stigma in our society, it is no wonder so many teens and families do not seek help. Promot-ing open dialogue within our workplaces, schools, churches, social groups and most importantly our own homes, is key to eliminating the stigma that prevents so many individuals from seeking life saving treatments for depression and other mental health illness.

We must advocate for more - 1 in every 5 children suffers from a diagnosable mental health disorder. As 90% of teens that commit suicide have a mental health disorder, treatment for these true medi-cal problems is vital to the prevention of suicide. Only about 21% of children with a mental health disorder actually receive treatment. This is not surprising given the fact that Texas has a critical short-age of child and adolescent psychiatrists. Our current health care system does not meet the substantial need of our community6. As a society, we must advocate for the expansion of mental health provi-sion. Contact your legislative representatives to fi nd out how they are fi ghting for the expansion of mental health availability for our youth and express how important it is to you.

For every suicide death that occurs, it is estimated that 50-100 more teens attempt suicide. This means that TODAY, in Texas alone, somewhere between 40 and 80 children and adolescents will attempt to end their lives7. We must take action before they succeed.

REFERENCES1. Center for Disease Control and Prevention. Injury Center Suicide Preven-tion – Youth Suicide http://www.cdc.gov/violenceprevention/pub/youth_sui-cide.html Page last reviewed 20122. Ready by 21. Outcome: Socially and Emotionally Healthy and Safe – Teen Suicide Rate. http://www.centex-communitydashboards.org/socially-and-emotionally-healthy-and-safe/teen-suicide-rate.php Last reviewed 20133. Center for Disease Control and Prevention. Suicide Briefs. Youth and Suicide http://www.cdc.gov/Features/SuicideBriefs/ Page last reviewed 20124. Texas Legislature Online http://www.capitol.state.tx.us/5. Committee on School Health. The Potentially Suicidal Student in the School Setting. Pediatrics 1990:86;4816. American Academy of Pediatrics Promoting Children’s Mental Health http://www.aap.org/en-us/advocacy-and-policy/federal-advocacy/Pages/mentalhealth.aspx. 7. American Academy of Pediatrics. Suicide and Suicide Attempts in Adoles-cents. Pediatrics. vol. 105 No. 4 April 2000

13. Drug Enforcement Administration. October 2013. Desomorphine (di-hydrodesoxymorphine; dihydrodesoxymorphine-D; street name: krokodil, crocodil). Available at http://www.deadiversion.usdoj.gov/drug_chem_info/desomorphine.pdf. Accessed on November 26, 2013.


ABSTRACTBackground: Restaurants are uniquely positioned to equip patrons so they can make nutritionally informed food selections. Community collaborations aim to promote healthy selections to restaurant patrons dining out in order to step forward in the efforts against obesity. This study shows a collaborative restaurant initiative to feature healthier food options in restaurants in a large urban city. The Healthy Res-taurants Coalition (HRC) was developed as a partnership between public health personnel, food professionals, registered dietitians and other important stakeholders. The ¡Por Vida! initiative was launched in 2010 by the Healthy Restaurants Coalition.Methods: Three sub-committees of the Healthy Restaurants Coali-tion (HRC) convened to develop the ¡Por Vida! initiative. One sub-committee developed healthy menu item criteria, based on national dietary guidelines; the second developed the logo and marketing plan; and the third selected and recruited restaurants. Participation and outcomes were tracked from 2008 to 2010. Results: Seven restaurant brands with more than 75 locations par-ticipated in the fi rst wave of the initiative. Five additional restaurants joined the initiative following the launch. Restaurants worked with HRC registered dietitians to analyze and modify their recipes to meet healthy menu item criteria. The HRC collectively determined mar-keting strategies and restaurant recruitment needs. The ¡Por Vida! initiative received attention from a wide-range of media outlets and was commended for its collaborative approach. Discussion: Partnerships including restaurants and registered dieti-tians are key in communities addressing the obesity epidemic. Res-taurants and food service professionals were found to be willing to partner with public health personnel when they are able to actively participate in the development of initiatives.Keywords: Food Industry, Community Networks, Public Health Practice, Nutrition Policy, Eating

BACKGROUNDThe restaurant food environment can infl uence patrons’ diets through multiple factors, including portion sizes and availability of nutrition information. Although research results are mixed,1,2 providing nutri-tion information at restaurants may enable consumers to choose low-er calorie foods.3,4 Given consumers’ tendency to underestimate the calories in less-healthful items by more than 600 calories,5 and the increasing dependence on foods consumed away from the home,5-7

interventions that increase consumer access to nutrition information are critical for obesity prevention.

Partially due to research recommendations for additional nutrition interventions in restaurants,5 The Patient Protection and Affordable Care Act, Section 4205, requires all restaurant and food vendors with more than 19 locations to disclose the caloric information on food items on menus by 2014.8,9 Community partnerships can complement these efforts and help maximize community outreach.10,11 Through an infusion of public health personnel and restaurant owners, a partner-ship effectively addresses these policy efforts aimed at restaurants.

San Antonio’s Healthy Restaurant Coalition (HRC) is a community partnership that aims to: 1) implement a community initiative high-

lighting healthier menu options among multiple restaurants through-out San Antonio and 2) create local support for the initiative as dem-onstrated through a diverse HRC and media hits at the time of the initiative launch. The HRC membership joins 3 spheres of partners including restaurants and food industry, marketing, and nutrition and health promotions. The purpose of this paper is to explore the for-mation of this community partnership initiative and review lessons learned.

POPULATIONApproximately 65 percent of the Bexar County adult population is overweight or obese.12 Furthermore, 13 percent of Bexar County adults have been diagnosed with diabetes13. The HRC was formed in 2009 to address these issues and included partners from the San Antonio Metropolitan Health District (Metro Health), the San Anto-nio Restaurant Association (SARA), and the San Antonio Dietetic Association (SADA).

METHODSState and local-level political leaders identifi ed and convened res-taurant partners, nutrition experts, food journalists, and the local public health authority to discuss restaurants’ role in addressing in-creasing rates of diabetes in San Antonio. Metro Health was charged with organizing and facilitating the community approach to diabetes prevention within the restaurant setting. As a partnership, HRC de-veloped the ¡Por Vida! (PV) (Spanish for “For Life!”) initiative and these activities are illustrated in Figure 1.

The PilotThe HRC conducted a pilot project to modify the children’s menu of a local iconic Mexican food restaurant. Five registered dietitians (RDs) analyzed the existing menu, developed practice-based menu criteria and identifi ed items to replace less healthy children’s menu items. Leaner options were added, portion sizes were decreased and high sugar items, like sweetened beverages, were minimized. Res-taurant menu changes included a total of 20 healthy menu items and two portion sizes offered on the children’s menu for children of dif-ferent age groups with different energy requirement.

CommitteesAfter the pilot, the HRC shifted its focus to adult menus and develop-ing a city-wide restaurant initiative. Members collaboratively iden-tifi ed priority tasks and 3 committees were established - Nutrition Criteria, Marketing/Logo, and Restaurant Selection and Implementa-tion, led by Metro Health staff. Members self-selected workgroups based on the strengths of their organizations.

The Nutrition Criteria committee reviewed the literature and other community restaurant initiatives when developing the PV guide-lines.14 Qualifying nutrition criteria for PV was developed by SADA based on the 2005 Dietary Guidelines for Americans, which recom-mend a balanced diet consisting of fruits, vegetables, whole grains, low-fat dairy, and lean protein.15 Menu items for the initiative also had to be free of trans-fats and low in saturated fats and sodium. Three types of nutrition criteria were developed for the PV menu items. The committee used an estimate based on one-third of the

A Voluntary Approach to Improve Menu Options in Restaurants Through a Local Collab-orative PartnershipLesli Biediger-Friedman, PhD, MPH, RD1, Erica T. Sosa, PhD, MCHES2, Kathleen Shields, CHES3, Alexa Shutt, PhD, MPH, RD4

1 School of Family and Consumer Sciences, Texas State University, San Marcos, TX2 Department of Health and Kinesiology, University of Texas at San Antonio, San Antonio, TX3 Chronic Disease Prevention Section, San Antonio Metropolitan Health District, San Antonio, TX4 Department of Health and Sport Science, University of Memphis, Memphis, TN


2,000 calorie diet used in the Dietary Guidelines, Daily Values and other government recommendations.15 The fi rst category was an en-trée with 2 sides. The full meal had to be 700 or fewer calories, <23 grams of fat, <8 grams of saturated fat, <0.5 gram of trans-fat, and <750 milligrams of sodium. The second category was a single entrée item, which must contain 300 or fewer calories, <10 grams of fat, <3.5 grams of saturated fat, <0.5 gram of trans-fat, and <325 mil-ligrams of sodium. The last category was a side item, which must be 200 or fewer calories, <7 grams of fat, <2 grams of saturated fat, <0.5 gram of trans-fat, and <215 milligrams of sodium. Water was recommended as the beverage of choice.

The Marketing/ Logo committee designed the fi rst logo in 2009. The artwork was designed by a pro-bono marketing fi rm. The HRC in-vited the Dallas Restaurant Partner Program with Medical City Heart Hospital to share strategies (e.g., staff training model, communica-tion agreement) and materials from their program (e.g., marketing materials).16 The marketing efforts of the HRC were supplemented by Metro Health staff.

The Restaurant Selection and Implementation committee was com-prised of representatives from Metro Health and SARA. In February 2010, four restaurants volunteered to be part of the PV adult menu pi-lot, and three completed the process. To become PV approved, each restaurant engaged in a 4 to 6 month process with an RD, at no cost to the restaurant. The fi rst month the RD provided a recipe analysis questionnaire to the restaurant. Secondly, the RD completed nutrition analysis of the recipes using The Food Processor: Nutrition Analysis & Fitness Software, (version 10.7.0, 2010, ESHA, Salem, OR). In the third month, the RD developed options to modify the recipes to

meet PV criteria. Next, the restaurant worked with the RD to adjust, test, and fi ne-tune the recipe. Finally, the restaurant could use the PV logo to label the specifi c menu items that met the criteria. Moreover, 4 new restaurants became involved, leading to an initiative launch with 7 participating restaurants in October 2010.

LaunchA kick-off event for PV was held for all seven restaurant brands, comprising more than 75 restaurant locations. The goals of the launch event included: gaining media exposure; visible support from city, county, and state elected offi cials; and stakeholder support. Ad-ditionally, the HRC aimed to generate interest from other local res-taurants and attract potential funders through the launch.

RESULTSPilotAfter the new children’s menu was implemented, a satisfaction sur-vey of 95 restaurant patrons revealed that 98.9% of patrons liked the new look of the children’s menu. Of those patrons who chose a healthy item (n=62), 83.6% reported that the logo helped them choose the item, 96.8% reported that they liked the portion size and 98.4% reported their children liked the food. These promising results suggested an expansion of PV was feasible and likely to be accepted by the community.

LaunchOver 80 individuals attended the launch, representing a diverse group of stakeholders and community members. HRC partners were well-represented, including public health staff from the state and lo-cal levels, SADA, SARA, and food service distributors. Numerous

2010 20112009Healthy Kids

Healthy Communities

Funding Secured (Dec 2009) CPPW6 Funding

Secured (March 2010)

DSHS7 Funding Secured

(March 2010)

July 2010 –Presentation on

Dallas Restaurant

Partner Program

May 2011 – Por Vida expands! Local hospital on board, Parks and Recreation Summer Food

Program become Por Vida

Feb - Logo developed!

Figure 1. Timeline for San Antonio Healthy Restaurants Coalition and Por Vida program. aSARA: San Antonio Restaurant Association; bHRC: Healthy Restaurants Coaltion; cMetro Health: San Antonio Metropolitan Health District; dRD: Registered Dietitian; eUTSA: Univeristy of Texas at San Antonio; fCPPW: Communities Putting Prevention to Work; gDSHS: Department of State Health Services.


organizations, including the food bank; members of academia; lo-cal businesses; and marketing agencies attended. Several city and county elected offi cials, including the mayor, county judge, and a senator, attended and spoke in support of the initiative.

HRC members made great efforts to ensure the initiative received at-tention from a wide-range of media outlets (Figure 2). Metro Health also released an offi cial media advisory, alerting news outlets and community members of the initiative. In addition, First Lady Mi-chelle Obama praised and recognized the efforts of the San Antonio partnership in her remarks at the Congressional Hispanic Caucus Ini-tiative. Immediately following the launch of PV, a number of news outlets, including the major local paper and ABC television affi liate, provided coverage. This represents a commitment by HRC members from Metro Health to increase the reach, impact, and adoption of PV. Largely because of the collaboration, PV receives continued recogni-tion by federal agencies and fi gureheads. The Let’s Move! campaign spotlighted the PV initiative during a call to action for city mayors across the country, and was featured on the Health and Human Ser-vice’s (HHS) Recovery website. In addition, HHS Secretary Kath-leen Sebelius visited San Antonio to learn more about PV, and later featured it during her news briefi ng.

At present, the HRC has approximately 50 members. Public health partners include members from local and state public health pro-grams such as Metro Health, WIC, the food bank, and the state obe-sity prevention program. Dietetic partners include RDs and nutrition students throughout the greater San Antonio area. The food provider partners include restaurants, food service companies, food distribu-tors, and food brokers. The last category of membership includes the marketing and communications partners, who have helped brand PV and spread awareness throughout the community.

DISCUSSIONThe development of the HRC has resulted in an innovative initiative that can be implemented throughout Bexar County and similar com-munities. Though it is too soon to evaluate its impact on the com-munity’s overall purchasing behaviors, its creation and implementa-tion offer a number of lessons learned. First, PV demonstrates how collaborative efforts can increase effi ciency and reduce barriers in achieving community health goals. In the early discussions regarding how restaurants could help patrons make healthier choices, “menu labeling” terminology was a barrier to moving forward with restau-rants. To circumvent controversial discussions, the local health de-partment quickly partnered with restaurants to fi nd alternative solu-tions. The HRC and resulting initiative have greatly benefi tted from the contributions of the restaurants, RDs, researchers and public health partners. With each entity’s unique perspective, the HRC was able to creatively identify effective approaches to provide restaurant patrons with healthier food options.

The initiative has some limitations. The criteria developed for the PV initiative are based on general dietary recommendations and may not be appropriate for all adults. However, the intent is to provide options that are generally healthier than those usually offered in restaurants. Another potential limitation is the cost of implementa-tion due to the initiative’s comprehensive, community-wide focus. However, the HRC has identifi ed several ways to address issues as-sociated with costs, such as staffi ng, dietary analysis and marketing. Metro Health was also able to secure a number of grants from diverse funding sources to support the development and implementation of the project. Additionally, the restaurants are able to share resources to complete menu modifi cations, and in turn, receive the item analysis and marketing benefi ts provided through the local health department at no cost to the restaurants. Finally, the restaurants are able to pool demand for healthier menu items to food brokers and distributors.

This pooled demand is also a benefi t for restaurants, schools, senior centers and other food providers in other communities.

The PV initiative has implications for practice, research, and policy. Practitioners can use this information as a model for developing similar initiatives in their communities. School districts, hospitals, worksites, university campus food service, and distributors are just a few of the other potential partners who can be instrumental in an initiative similar to PV. The local dietetic association’s unique con-tribution will benefi t communities interested in developing similar initiatives to consider such partnerships.

Future research on the impacts and outcomes of PV will be important not only for the current initiative, but for other communities inter-ested in restaurant initiatives. Currently, there is limited research on the effectiveness of restaurant initiatives. At the time of this paper, a thorough evaluation is being conducted on PV to assess the initia-tive’s effectiveness and ability to reach its goals and objectives. Pre-liminary fi ndings thus far are promising.17 These types of communi-ty-driven efforts can complement current policy efforts to modify the food environment and equip patrons with the information they need to make healthier food decisions. Efforts to increase the availability and visibility of healthier food options can empower patrons to live healthier lives. With strong collaborations, communities can move forward in preventing the health issues that commonly impact them.

AcknowledgementsThis publication was supported by a cooperative agreement for the Texas Department of State Health Services. Its contents are solely the responsibility of the authors. We appreciate the multiple funding agencies that helped support ¡Por Vida! development and implemen-tation, such as: Communities Putting Prevention to Work (grant # 1U58DP002453-01 ) through the Centers for Disease Control and Prevention; Healthy Kids, Healthy Communities Program through The Robert Wood Johnson Foundation (grant # 66763 ); The Texas Department of State Health Services Community Diabetes Program (grant # 2011-037885-001 ); and the Texas Department of State Health Services, Community Based Obesity Prevention Grant (grant # 2010-034870 ). We also appreciate the collaboration and com-mitment from the following organizations: San Antonio Restaurant Association; San Antonio Dietetic Association; The Bexar County Health Collaborative and all partners who have made this collabo-ration possible.

REFERENCES1. Girz L, Polivy J, Herman CP, Lee H. The effects of calorie information on food selection and intake. Int J Obes July 21, 2011.2. Elbel B, Kersh R, Brescoll V, Dixon B. Calorie labeling and food choices: A fi rst look at the effects on low-income people in New York City. Health Aff 2009; 28(6):1110-1121.3. Roberto CA, Agnew H, Brownell KD. An observational study of con-sumers’ accessing of nutrition information in chain restaurants. Am J Public Health 2009; 99(5):820.4. Pulos E, Leng K. Evaluation of a voluntary menu-labeling program in full-service restaurants. Am J Public Health 2010; 100(6):1035.5. Burton S, Creyer EH, Kees J, Huggins K. Attacking the obesity epidemic: The potential health benefi ts of providing nutrition information in restaurants. Am J Public Health 2006; 96(9):1669-1675.6. Acharya R, Patterson P, Hill E, Schmitz T, Bohm E. An evaluation of the “TrEAT Yourself Well” restaurant nutrition campaign. Health Educ Behav 2006; 33(3):309-324.7. United States Department of Agriculture. Economic Research Service. Food expenditures. Available at: http://www.ers.usda.gov/data-products/food-expenditures.aspx#26636. Accessed November 8, 2012.8. Stein K. A national approach to restaurant menu labeling: The Pa-tient Protection and Affordable Care Act, Section 4205. J Am Diet Assoc 2010;110(9):1280-1286.9. Congress H.R. 3590: Patient Protection and Affordable Care Act. Database of federal legislation: GovTrack.us; 2009.


10. King G, Servais M, Kertoy M, Specht J, Currie M, Rosenbaum P, et al. A measure of community members’ perceptions of the impacts of research partnerships in health and social services. Eval Program Plann 2009; 32 (3):289-299.11. Wolff T. A practitioner’s guide to successful coalitions. Am J Community Psychol 2001; 29(2):173-191.12. CDC. Behavioral Risk Factor Surveillance System Survey Data. 2010; Available at: http://apps.nccd.cdc.gov/brfss-smart/SelMMSAPrevData.asp. Accessed September 18, 2013.13. City of San Antonio Metropolitan Health District. Type two diabetes in Bexar County. 2013; Available at: http://www.sanantonio.gov/health/pdf/2013_Fact_Sheet_Diabetes.pdf. Accessed September 27, 2013.14. City of San Antonio Metropolitan Health District. ¡Por Vida! San An-tonio’s Healthy Menu Initiative. 2012; Available at: http://www.sanantonio.gov/health/PorVida%20Nutritional%20Criteria.html. Accessed November 8, 2012.

15. U.S. Department of Health and Human Services and U.S. Department of Agriculture. Dietary Guidelines for Americans, 2005. 6th Edition, Washing-ton, DC: U.S. Government Printing Offi ce, January 2005.16. Medical City Heart. Restaurant partner program participating restau-rants. 2011; Available at: http://medicalcityhospital.com/about/community-involvement/restaurant-program.dot. Accessed November 8, 2012.17. Sosa ET, Biediger-Friedman L, Banda M. Associations between a volun-tary restaurant menu designation initiative and patron purchasing behavior. Health Promot Pract. 2012. DOI: 10.1177/1524839912469535.

0 2 4 6 8 10 12 14 16

Other

Recognition by federal agencies and figureheads

Community events

City media advisory

Blog

Newsletter (print, online)

Radio

Television

Magazine

Newspaper

Types of media

Number of media hits

Pre-launch (October 12, 2010 and earlier)Launch and one week following (October 13-19, 2010)Post-launch (October 20, 2010-present)

Figure 2. Immediate and long-term media and publicity for ¡Por Vida!


ABSTRACTBackground: Recent systematic reviews confi rm that physical ac-tivity can be effective in enhancing health-related quality of life among cancer survivors. Older and ethnic minority cancer survivors frequently experience environmental, social, and cultural barriers to physical activity interventions. Promotores/Community Health Workers (P/CHWs) are an effective way to reach underserved and diffi cult to reach cancer survivor populations. Methods: A survey of Texas P/CHWs explored barriers to delivering health promotion for physical activity and examined the P/CHWs' use of Internet and social networking. An email with links to either an English or Spanish language survey was distributed to 287 P/CHWs living in Texas. Among 254 respondents, 168 selected the English and 86 selected the Spanish language surveys. Results: Of the Spanish language survey respondents, 92.9% were of Latino/Hispanic ethnicity, as were 55.2% of the English language re-spondents. Pearson’s chi-square tests showed signifi cant differences by choice of survey language in types of service to cancer survivors, barriers to physical activity, and Internet use for health information and social networking. Conclusions: This research highlights the need for greater consid-eration of cultural, social, and environmental characteristics in de-veloping culturally and linguistically specifi c P/CHW training and interventions to promote physical activity and healthy lifestyles in order to improve survivorship outcomes. Key Words: cancer, survivorship, community health workers, lay health workers, physical activity, exercise, barriers

INTRODUCTIONAs of January 2012, the American Cancer Society estimated that there are 13.7 million cancer survivors living in the United States (U.S.), a number that is expected to grow to 18 million by 2022.1

People are living longer after a cancer diagnosis, and cancer survi-vors are at greater risk of cancer recurrence, of developing second cancers, and of having other chronic health conditions due to the effects of their treatment. Recent and mounting evidence suggests physical activity may be effective in reducing negative outcomes and improving Health Related Quality of Life (HRQOL) among cancer survivors.2 Past concerns about contraindications for physical activ-ity are now challenged by clinical evidence that physical activity is good, perhaps even necessary, for improving survivors’ HRQOL. The American College of Sports Medicine (ACSM) and the Ameri-can Heart Association (AHA) guidelines for moderate physical ac-tivity is 30 minutes per day for fi ve or more days per week, or 20 minutes per day of vigorous activity for three days per week.3 Ac-cording to a recent study of adherence to physical activity guidelines among older Texas cancer survivors, approximately 48% of older cancer survivors adhere to physical activity guidelines.4

The stressors of cancer diagnosis and short and longer-term side ef-fects of treatment may partially account for the lack of physical ac-

tivity among survivors.5-11 However, research indicates that cancer survivors are interested in learning more about physical activity and its benefi ts. In a descriptive study, cancer survivors indicated that they would prefer to receive exercise counseling during their cancer experience. Perhaps not surprisingly, only 16% of the survivors in this study reported exercising at recommended levels.12 In a more recent study, researchers looked at physical activity across six ma-jor cancer survivor groups (i.e., breast, prostate, colorectal, bladder, uterine, and skin melanoma). In this study, 9,105 survivors complet-ed a national, cross-sectional survey that revealed only 30–47% of cancer survivors are meeting the recommendations of 150 minutes of weekly physical activity.13

Thus, while cancer survivorship has been identifi ed as a “teach-able moment” wherein survivors can be motivated to make lifestyle changes to improve health outcomes, few are actually making these changes.14 Given the general statistics documenting lower rates of physical activity among older, minority, or rural populations due to a host of behavioral, social, and environmental factors, rates are likely to be even lower among this population of cancer survivors.15-20 This highlights the importance of fi nding ways to identify and disseminate more effective interventions to promote adoption and maintenance of physical activity, especially among populations with traditionally low rates of physical activity.

Promotores/Community Health Workers (P/CHWs) offer a novel and culturally appropriate model for educating cancer survivors about the benefi ts of physical activity in the communities where they live and work. Historically, Promotoras/es have addressed health disparities in Latino/Hispanic communities. Today, the terms Promotoras (fe-males) and Promotores (males) and Community Health Workers are used interchangeably in many communities and among various cul-tures. For the purpose of this paper, we use the acronym “P/CHW” to describe this group of workers. Examples of P/CHW roles include providing health education, cancer and chronic disease patient navi-gation, and directly delivering medical services, such as immuniza-tion and health screening for diabetes, cancer, cardiovascular disease, asthma, and maternal and child health. P/CHWs frequently address health disparities in underserved populations such as older, rural, and minority cancer survivors.15 These are the populations that may ex-perience the most barriers to engaging in regular physical activity.16

A literature review of P/CHW education programs in the U.S. reveals that P/CHW interventions are most prevalent in Hispanic communi-ties, and the same review reported that cancer screening was the most common focus of P/CHW programs.17-20

As part of a project to develop a Texas Department of State Health Services (DSHS) accredited continuing education program for P/CHWs, we conducted a brief survey to learn more about factors af-fecting PCHWs’ engagement in cancer prevention and control efforts, including work with cancer survivors. The purpose of this paper is to

Barriers to Physical Activity Education for Cancer Survivors: A Survey of English and Spanish Speaking Promotores/Community Health Workers in TexasDeborah Vollmer Dahlke, MPAff, CHW1, Jinmyoung Cho, PhD2, Venus Gines, MA,CHWI3, Julie St. John, MA, MPH, CHWI, Doctoral Candidate4, Marcia Ory, MA, MPH, PhD5

1Texas A&M Health Science Center, School of Rural Public Health, College Station, 2Center for Applied Health Research, Texas A&M Health Science Center, School of Rural Public Health, College Station, TX 3CEO Dia de la Mujer Latina, Manvel, TX 4South Texas Regional Director, Center for Community Health Development, Texas A&M School of Rural Public Health, San Benito, TX 5Health Promotion and Community Health Sciences, School of Rural Public Health, Texas A&M Health Science Center, Col-lege Station, Texas


describe what we learned about P/CHWs’ barriers and opportunities regarding educating older cancer survivors to increase engagement in physical activity and the likelihood that P/CHWs would access and use information on physical activity available on the Internet. We were particularly interested in learning if there are any systematic differences between P/CHWs who requested the surveys in English versus those who requested the surveys in Spanish. This information will contribute to the limited knowledge of factors that might affect P/CHWs’ ability to deliver information about and recommendations for increasing cancer survivors’ physical activity.

METHODSSetting and Population: The survey of P/CHWs was conducted in Texas, which is one of fi ve states (Texas, Massachusetts, Oregon, Rhode Island, and Minnesota) that have state legislation regarding P/CHW certifi cation. There are a number of other states with legis-lation pending or proposed. Texas certifi cation requires completion of either an approved 160-hour, competency-based training program certifi ed by the Texas DSHS or at least 1000 cumulative hours of community health work services within the most recent six years. As of February 2013, Texas had 2,830 certifi ed P/CHWs.21

Instrument DevelopmentPilot work for this study included interviews with bilingual English and Spanish speaking P/CHWs and certifi ed P/CHW instructors. The P/CHWs and instructors were engaged in the preparation of the sur-vey instrument by suggesting and reviewing the questions and also in reviewing translations. The instrument was developed fi rst in Eng-lish and then translated into Spanish using a professional translator. Back-translation and testing was accomplished with fi ve bilingual (English and Spanish speaking) members of the Dia de La Mujer Latina (DML) P/CHW organization. The DML reviewers included P/CHWs of Puerto Rican, Mexican, Mexican American, Columbian, and El Salvadorian heritage. The fi ve reviewers all had to agree on the resolution not only of the English to Spanish translation but also in resolving any country or regionally specifi c idiomatic expressions in the Spanish language survey.

InstrumentDemographic information (e.g. gender, age, country of birth, years in the United States languages spoken, educational level, etc.) was extracted for each respondent. Information on types of P/CHW training and work experience as a P/CHW was also collected. We wanted to explore the P/CHWs’ request for the survey in English language versus Spanish language in terms of education, place of birth, and as a potential indicator of the types of populations with which they might be working. Information on the P/CHWs’ experi-ence in working with cancer survivors and barriers to older cancer survivors engaging in physical activity was collected. Participants were asked to check applicable items (e.g., “There are no safe places to walk outside”, “There is the belief that physical activity is harmful to cancer survivors”). Details of the P/CHWs’ access to the Inter-net and use of social networking (e.g., texting, Facebook, LinkedIn) and amount of time for health information seeking using the Internet were also collected. In order to assess if P/CHW themselves were physically active, the survey asked about participation in activities such as walking, stretching, dancing, and muscle strengthening. The Internet-based survey included single choice, multiple choice, and fi ll-in-the-blank type questions. The survey was designed to be anonymous, but if respondents wanted to receive additional informa-tion or the results of the survey, they were asked to share their contact information on a form separate from the survey.

Survey DisseminationEligibility criteria for participation in the survey included the fol-

lowing: participants had to live in Texas and consider themselves P/CHW, they could be of any race/ethnicity, and were not required to have Texas DSHS certifi cation. We did not ask the P/CHWs to pro-vide citizenship status, but did ask how many years they had lived in the U.S. We initiated the survey using an email list of 165 P/CHW provided by DML; this list served as our seed for the non-ran-domized sample. Snowball sampling techniques were employed by asking P/CHW trainers to forward the survey to other Texas-based P/CHW. The email text was provided in both English and Spanish and included links to both an English language and a Spanish language survey. During the snowball sampling process, a copy of each email invitation sent out from P/CHW trainers was shared with the project team. This allowed the team to determine how many surveys were distributed. The survey itself was anonymous. A total of 287 surveys were emailed and resulted in 254 respondents (88.5%). Of these, 168 English language surveys and 86 Spanish language surveys were re-turned.

AnalysisThe analysis and evaluation of the de-identifi ed survey data was con-ducted under a Texas A&M University Institutional Review Board protocol (IRB 2012.0500). Descriptive statistics, including percent-ages, means, and standard deviation, were used to analyze the data. Differences between English and Spanish language survey respon-dents were analyzed using Pearson’s chi-square (χ2) test. A p-value of less than 0.05 was considered to indicate statistical signifi cance. Survey analyses were performed using the SPSS statistical software (version 21.0).

RESULTSRespondentsA total of 287 surveys were emailed starting with a seed convenience sample of 165 email addresses drawn from the DML contact list. An additional 122 surveys were emailed out using referrals from P/CHW instructors from across the state of Texas. All forwarded copies of the email were copied to the project team in order to maintain control of the numbers of surveys disseminated. As indicated in Table 1, the majority of respondents were middle-aged (44.0%), female (89.9%), and 53.8% spoke both English and Spanish languages. Respondents of Latino/Hispanic ethnicity predominated (68%).

Services and Health Education to Cancer SurvivorsOverall, more than half of the respondents (52.4%) reported that they provide health services to cancer patients and survivors. The ma-jority (60%) of the Spanish language survey respondents said that they provided health services to cancer survivors with fewer than half (45.5%) of the English language respondents providing such services. When asked about their interest in providing education to cancer survivors on the benefi ts of physical activity, 89.5% stated an interest in providing such education. Nearly all of the all participants (93.5%) indicated they would participate in a free P/CHW continu-ing education module for physical activity among cancer survivors.

Barriers to Physical Activity for P/CHW Cancer Survivor ClientsThe research team explored the P/CHWs’ participation in physical activity as a potential barrier or enabler to educating their cancer sur-vivor clients. As shown in Table 2, the P/CHWs reported engaging in different amounts of physical activity with only 15% reporting that they engaged in physical activity fi ve or more times per week. There was a signifi cant difference between the Spanish and English language survey respondents regarding the benefi ts of physical activ-ity for cancer survivors. The majority of the Spanish language sur-vey respondents (61.6%) indicated a belief “that physical activity is harmful to cancer survivors” as compared with 15.5% of the English language survey respondents.


Table 1. Summary of Promotores/Community health worker (PCHW) Participant Characteristics

Total

(n = 254)

Spanish

(n = 86)

English

(n = 168)

2 p

Age groups 8.73 0.013

19-35 years 21.6% 12.3% 26.3%

36-50 years 44.0% 55.6% 38.1%

51 years and over 34.4% 32.1% 35.6%

Sex 1.34 0.248

Male 10.1% 7.1% 11.7%

Female 89.9% 92.9% 88.3%

Speaking languages 119.12 < 0.001

English 29.3% 0.0% 44.5%

Spanish 16.9% 49.4% 0.0%

Both 53.8% 50.6% 55.5%

Education 24.26 < 0.001

Less than high school 4.8% 10.7% 1.8%

High school graduate 21.4% 32.1% 15.9%

Some college 40.3% 25.0% 48.2%

College graduate 19.8% 16.7% 21.3%

Post college 13.7% 15.5% 12.8%

Ethnicity 37.58 < 0.001

Non-Hispanic White 14.6% 6.0% 19.0%

Latino/Hispanic 68.0% 92.9% 55.2%

Black/African American 13.0% 0.0% 19.6%

Other 4.5% 1.2% 6.1%

Years in the U.S. 150.48 < 0.001

Less than 1 year 0.8% 2.4% 0.0%

1-10 years 7.7% 20.2% 1.2%

10+ years 37.9% 77.4% 17.7%

Born in the U.S. 53.6% 0.0% 81.1%

Frequency of participation in physical activity 9.26 0.026

No physical activity 5.7% 2.4% 7.4%

1-2 times per week 37.0% 30.1% 40.5%

3-4 times per week 42.3% 44.6% 41.1%

5 or more times per week 15.0% 22.9% 11.0% Table 2. Barriers to Physical Activity Among P/CHWs’ Cancer Survivor Clients

Total

(n = 254)

Spanish

(n = 86)

English

(n = 168)

2 p

No safe places to walk outside 57.69 < 0.001

Yes 40.6% 73.3% 23.8%

No 59.4% 26.7% 76.2%

No safe inside places for walking or participating in

healthy activities

39.44 < 0.001

Yes 29.5% 54.7% 16.7%

No 71.5% 45.3% 83.3%

High costs for healthy physical activities 0.05 0.828

Yes 39.8% 40.7% 39.3%

No 60.2% 59.3% 60.7%

No public transportation 41.28 < 0.001

Yes 37.8% 65.1% 23.8%

No 62.2% 34.9% 76.2%

Limited services of public transportation to facilities for

healthy physical activity

28.55 < 0.001

Yes 30.7% 52.3% 19.6%

No 69.3% 47.7% 80.4%

No groups or organizations for healthy physical activity 14.73 < 0.001

Yes 39.4% 55.8% 31.0%

No 60.6% 44.2% 69.0%

Belief that physical activity is harmful to cancer

survivors

56.54 < 0.001

Yes 31.1% 61.6% 15.5%

No 68.9% 38.4% 84.5%


Internet Use for Health Information and Social Networking Par-ticipationThe survey included questions about P/CHWs’ use of the Internet for accessing health information, including questions about use of different devices and participation in online social networking. One approach being considered for the design of the P/CHW training pro-gram included the use of mobile and online systems for survivor goal setting and tracking of physical activity. As shown in Table 3, nearly half of the survey respondents (45.2%) accessed the Internet every day. Use of mobile and smart phones to search for health information on the Internet was moderate among all survey respondents, with 40.0% of the Spanish language respondents and 53.6% of the Eng-lish language survey respondents accessing the Internet using mobile technology.

DISCUSSION This study documented many signifi cant differences by survey lan-guage preference in terms of P/CHWs’ basic demographic charac-teristics, interest in providing education to cancer survivors on the benefi ts of physical activity, personal levels of physical activity and perceived barriers to physical activity, and access to and use of the Internet for health information. Recognition of the similarities and differences across the two study population groups can provide use-ful insights and information for the design and dissemination of P/CHW training programs on increasing physical activity among can-cer survivors.

Several major fi ndings emerged from this study. The response rate to the Spanish language survey choice reinforced the research team’s plan to develop and deliver the training in both English and Span-ish. The fi nding among the Spanish language survey respondents that there is belief that survivors should not engage in physical activity indicates the importance of being aware of both the P/CHWs’ and their clients’ cultural beliefs about physical activity after a cancer diagnosis. Such fi ndings also point to the need for culturally sensi-tive approaches in the design of any training programs in order to attempt to respectfully shift such underlying cultural beliefs among

Latino/Hispanic cancer survivors.22 The survey results documenting concerns about the physical environment indicate that educating P/CHWs to assess local community resources and locations for safe walking and other indoor and outdoor physical activity would be helpful in the curriculum design, as also is indicated in recent study of factors promoting physical activity among Latino/Hispanics at the Texas/Mexico border.23

The study confi rmed previous research that the P/CHW do indeed access the Internet on personal computers and actively use the In-ternet to seek health information.24 However, trainers using educa-tional resources on physical activity may need to identify resources that are available via traditional web-based services in addition to resources that only can be accessed using mobile devices. The lack of use of email among the Spanish language respondents is striking and indicates that the developers of training programs and those dis-seminating information about physical activity resources may need to explore alternative methods to reach P/CHW who are primarily Spanish speaking.

LimitationsAmong the limitations of this study are the uses of a seed conve-nience sample of the P/CHWs from the DML mailing list and the snowball strategy based in forwarded emails to P/CHWs. Such sam-pling strategy, while cost effective, may have led to underrepresenta-tion or over representation of particular groups in the sample, which could be source of bias. Snowball sampling, while not providing a random sample, does allow for the inclusion of members of popula-tions that have not been previously identifi ed, such as P/CHWs who are in practice but who are not certifi ed. The way that snowball sam-pling relies on social networks, as did the reliance of PCHW trainers in this study, may present a bias due to personal network size as those member of the population with the largest networks and higher so-cial visibility are more likely to be referred. Individuals with smaller networks and isolated individuals are likely to be omitted from the sample because they are less likely to be included or referred.24 The use of a survey instrument that was not tested for validity or reliabil-

Table 3. P/CHW Internet Use for Health Information and Social Networking Participation

Total

(n = 254)

Spanish

(n = 86)

English

(n = 168)

2 p

Frequency of access Internet 17.03 0.001

Daily 45.2% 23.2% 53.9%

1-2 times per week 29.2% 34.1% 26.7%

1-3 times per month 20.8% 29.4% 16.4%

Rarely 4.8% 8.2% 3.0%

Internet use for health information

Using a personal/family computer 78.7% 83.7% 76.2% 1.93 0.165

Using a work computer 58.3% 34.9% 70.2% 23.24 < 0.001

Using a public computer (library) 7.1% 7.0% 7.1% 0.00 0.961

Using cell phone 49.1% 40.0% 53.6% 4.16 0.041

Asking for others 9.4% 5.8% 11.3% 2.01 0.156

Participation in social networking activities

Texting with friends and family 73.2% 77.9% 70.8% 1.45 0.228

Facebook 63.4% 60.5% 64.9% 0.48 0.489

Twitter 11.8% 12.8% 11.3% 0.12 0.729

LinkedIN 14.6% 7.0% 18.5% 6.02 0.014

Blogs 9.8% 4.7% 12.5% 3.95 0.047

Email 45.3% 15.1% 60.7% 47.73 < 0.001

Other 5.5% 1.2% 7.7% 4.72 0.03


ity may limit the generalizability of this research.

We also do not know why some P/CHW agreed to take part in the survey while others did not. Since the sampling frame was not deter-mined prior to the study and the sample was not chosen at random, there may also be an inherent bias in the study’s convenience sample, which again undermines the ability to make generalizations. An ad-ditional limitation is the limited geography of one state. While Texas is a geographically large and diverse state, the study refl ects only the opinions of P/CHW active and/or certifi ed in Texas.

Implications for Research and PracticeDeveloping training and interventions for cancer survivors to engage in increased physical activity interventions must be linguistically and culturally congruent both for the P/CHWs and their clients. Given the evidence base that engaging in moderate levels of physical activ-ity (i.e., 150 minutes per week) provides improvements in health-related quality of life among cancer survivors suggests the need for additional research on Latino/Hispanic cancer survivors’ barriers and enablers for physical activity.25 Utilizing outcome research to test the efficacy of P/CHW training and delivery of education to increase physical activity among cancer survivors will enable the training to be evaluated and refi ned.

Acknowledgements This research was developed with support of CTxCARES, one of ten Cancer Prevention and Control Research Networks supported by a grant from Centers for Disease Control and Prevention Research Center Program to the Center for Community Health Development at the Texas A&M Health Science Center School of Rural Public Health under cooperative agreement number 1U48 DP001924. We appreciate the support of Venus Gines and Dia de la Mujer Latina and Julie St. John in the dissemination of the surveys. REFERENCES1. Siegel R, DeSantis C, Virgo K, et al. 2012. Cancer treatment and survivor-ship statistics, 2012, A Cancer Journal for Clinicians 62(4):220–241.2. Mishra S, Scherer R, Topaloglu O, Gotay C, Snyder C. 2012. Exercise interventions on health-related quality of life for cancer survivors. Cochrane Database of Systemic Reviews 8:1. 3. Nelson M, Rejeksi J, Blair S, et al. 2007. Physical activity and public health in older adults: Recommendation from the American College of Sports Medicine and the American Heart Association. Medicine & Science in Sports and Exercise 39(8):1435–1445. 4. Rogers LQ, McAuley E, Anton PM, et al. 2012. Better exercise adherence after treatment for cancer (BEAT Cancer) study: Rationale, design, and meth-ods. Contemporary Clinical Trials 33(1):124‒137.5. Meyerhardt JA, Hesseltine D, Neidzwiecki D, et al. 2006. Impact of Physi-cal Activity on cancer recurrence and survival in patients with stage III colon cancer: fi ndings from CALGB 89803. Journal of Clinical Oncology 24:3535-3541. 6. Sander AP, Wilson J, Izzo N, Mountford SA, Hayes KW. 2012. Factors that affect decisions about physical activity and exercise in survivors of breast cancer: A qualitative study. Physical Therapy 92(4):525‒536.7. Courneya KS, McKenzie DC, Reid RD, et al. 2008. Barriers to supervised exercise training in a randomized controlled trial of breast cancer patients receiving chemotherapy. Annals of Behavioral Medicine 35;(1):116‒122.8. Rogers LQ, Markwell S, Hopkins-Price P, et al. 2011. Reduced barriers mediated physical activity maintenance among breast cancer survivors. Jour-nal of Sport and Exercise Psychology 33(22):235‒254.9. Lees FD, Clarke PG, Nigg CR, Newman P. 2005.Barriers to exercise be-havior among older adults: a focus-group study. Journal of Aging and Physi-cal Activity 13;(1):23‒33.10. Schwartz AL.1998. Patterns of exercise and fatigue in physically active cancer survivors. Oncology Nursing Forum 25(3):485‒491.11. Calle EE, Rodriguez C, Walker-Thurmond K, et al. 2003. Overweight, obesity and mortality from cancer in a prospectively studied cohort of U.S. adults. New England Journal of Medicine 348:1625-1638.12. Jones LW, Courneya KS. 2002. Exercise counseling and programming

preferences of cancer survivors. Cancer Practice10(4):208–215.13. Blanchard CM, Courneya KS, Stein K, American Cancer Society's SCS-II. 2008.Cancer survivors’ adherence to lifestyle behavior recommendations and associations with health-related quality of life: results from the American Cancer Society’s SCS-II. Journal of Clinical Oncology 26(13):2198–2204.14. Ganz PA. 2005. A teachable moment for oncologists: cancer survivors, 10 million strong and growing! Journal of Clinical Oncology 23(24):5458-5460.15. Lewin SA, Dick J, Pond P, et al. 2005. Lay health workers in primary and community health care. Cochrane Database of Systemic Reviews 25;1. 16. Wilcox S, Castro C, King AC, Housemann R, Brownson RC. 2000. Deter-minants of leisure time physical activity in rural compared with urban older and ethnically diverse women in the United States. Journal of Epidemiology and Community Health 54(9): 667–672. 17. Lewin SA, Dick J, Pond P, et al. 2005. Lay health workers in primary and community health care. Cochrane Database of Systemic Reviews 25; 1. 18. Perez L, Martinez J. 2008. Community health workers: Social justice and policy advocates for community health and well being. American Journal of Public Health 98(1):11–14.19. Love M, Gardner K, Legion V. 1997. Community health workers: What they are and what they do. Health Education & Behavior 24(4):510–522.20. Viswanathan M, Kraschnewski J, Nishikawa B, Morgan LC, Thied P, Honeycutt A, Lohr KN, Jonas D. 2009. Outcomes of Community Health Worker Interventions. Evidence Report/Technology Assessment No. 181. AHRQ Publication No. 09-E014. Rockville, MD: Agency for Healthcare Re-search and Quality. 21. Garcia A. 2013. Current number of Certifi ed CHW in Texas. Email to Julie St. John. February 27, 2013.22. Mier N, Ory MG, Medina AA. 2010. Anatomy of Culturally Sensitive Interventions Promoting Nutrition and Exercise in Hispanics: A Critical Ex-amination of Existing Literature. Health Promotion Practice 11(4):541–554.23. Florez-Arango JF, Iyengar MS, Dunn K, Zhang J. 2011. Performance fac-tors of mobile rich media job aids for community health workers. Journal of the American Medical Informatics Association 18:131-137.24. Biernacki P, Waldorf D. 1981. Snowball sampling: Problems and tech-niques of chain referral sampling. Sociological Methods Research 10:141-163. 25. Sander AP, Wilson J, Izzo S, Mountford SA, Hayes KW. 2012. Factors that affect decisions about physical activity and exercise in breast cancer sur-vivors: a qualitative study. Physical Therapy 9(42):525-536.


ABSTRACT Background: More than 1,500 persons died due to excessive alcohol consumption in Texas in 2010. Texas has a high burden of chronic diseases, including those related to excessive alcohol consumption. The purpose of this study was to explore the population-based pat-terns of excessive alcohol consumption and chronic diseases that can be either caused or exacerbated by excessive drinking among Texas adults. Methods: Texas 2011 Behavioral Risk Factor Surveillance System (BRFSS) survey data were analyzed. The sample size was 14,973 adults aged >18 years; data were weighted to be representative of the Texas adult population. Analysis was performed using SAS 9.2 software for three measures of excessive alcohol consumption (binge drinking, heavy drinking, and usual consumption in excess of U.S. Dietary Guidelines limit); these measures were related to eight chronic diseases and selected socio-demographic characteristics. Results: Among Texas adults with the chronic diseases assessed, 29.6% reported one of the three measures of excessive drinking, in-cluding 27.4% of those who had a routine checkup in the past two years. Current smokers had the highest (48.1%) and adults with dia-betes (14.5%) had the lowest prevalence of excessive drinking. Ex-cessive drinking was lower among racial minorities or those with low educational or income levels. Subpopulations who tended to have a higher prevalence of excessive drinking included men, those aged 18-44 years, unmarried persons, employed persons, those with at least some college education, and those with annual household income $50,000 or more. Among excessive drinkers, 69.4% reported having one or more chronic diseases. Conclusions: The prevalence of excessive alcohol consumption is high among Texas adults with alcohol-associated chronic diseases, and many alcohol policies can effectively reduce excessive drinking. Similar fi ndings among those with a recent checkup underscore the importance of routine alcohol screening and brief counseling inter-ventions in accordance with national guidelines.

INTRODUCTIONChronic diseases are a major cause of morbidity and mortality in Texas. In 2011, seven of the ten leading causes of death were from chronic diseases, and chronic diseases accounted for 87% of all Tex-as deaths. Many of these chronic diseases are lifestyle-related and could be prevented or mitigated through behavior modifi cation in areas such as smoking, excessive alcohol consumption, physical in-activity, and overeating.1 Approximately 70% of adult Texans have at least one of the following eight chronic conditions or risk factors that can be caused or exacerbated by excessive drinking: obesity, diabetes, hypertension, cardiovascular disease, cancer, depression, smoking, and fi ve or more mentally unhealthy days. In 2010, ex-cessive alcohol consumption caused 1,579 deaths in Texas, and on average each alcohol-attributable death accounted for approximately 30 years of potential life lost.2,3 The economic cost of excessive al-cohol consumption in Texas was $16.5 billion, second to California nationwide, out of which 40.7% was paid by the state government.4

Excessive drinking is typically defi ned either on the basis of per-oc-casion consumption (e.g., binge drinking) or on the basis of average daily consumption (e.g., heavy drinking). In Texas, approximately 18.9% of adults report binge drinking and 7% report heavy drink-ing.5 Consequences of excessive per-occasion consumption include unintentional injuries such as alcohol-related motor vehicle crashes, homicide, suicide, interpersonal violence, child neglect, pancreatitis,

hepatitis, and gastritis.6

In addition to these immediate effects of alcohol stemming from in-toxication, there are a number of chronic diseases that can be caused or exacerbated by excessive drinking. These include alcohol use dis-orders (e.g., alcohol dependence), chronic liver disease (e.g., cirrho-sis), hypertension, ischemic heart disease, hemorrhagic and ischemic stroke, certain types of cancer, and several mental health conditions including depression and anxiety.3, 7-10

The effect of alcohol on chronic diseases has been explored in previ-ous research but has not been fully examined or appreciated in the context of public health or clinical medicine.11 Furthermore, the pat-terns of excessive drinking and a range of chronic conditions that can be caused or exacerbated by excessive drinking have not been explored previously. Therefore, the objective of this study was to explore the population-based patterns of excessive alcohol consump-tion and a variety of chronic diseases that can be either caused or exacerbated by excessive drinking among Texas adults.

METHODSTexas 2011 Behavioral Risk Factor Surveillance System (BRFSS) survey data were analyzed for this study. The BRFSS is a random-digit-dial telephone survey among non-institutionalized adults age 18 years and older. The BRFSS is administered in each state and partially funded by the Centers for Disease Control and Prevention and is the largest continuously conducted telephone survey in the world. In 2011, the survey was administered through landline as well as cell phones and used an improved weighting methodology result-ing in more precise estimates. The sample size for the 2011 survey in Texas included 14,973 respondents. Additional details about BRFSS methods are available at http://www.cdc.gov/brfss/about/index.htm.

Three measures of excessive alcohol consumption were assessed in this study, including binge drinking, heavy drinking, and usual con-sumption in excess of U.S. Dietary Guidelines limits.12 Binge drink-ing was defi ned as consuming >5 drinks for men or >4 drinks for women on one or more “occasions” during the past 30 days. Heavy drinking was defi ned as men having an average consumption of >2 drinks per day and women having an average consumption of >1 drink per day during the past 30 days. Consumption in excess of the U.S. Dietary Guidelines limit was defi ned as usual average consump-tion of three or more drinks for men or two or more drinks for women during drinking days during the past 30 days.

The chronic conditions assessed included obesity (body mass index or BMI ≥30), diabetes, hypertension, cardiovascular disease, cancer, current smoking, depression, and ≥ 5 mentally unhealthy days in the past 30 days. All conditions, including height and weight used to calculate BMI, were based on self-report. For diabetes, hyperten-sion, cardiovascular disease, cancer, and depression, respondents were told to report only if the conditions were diagnosed by a doctor.

Data were analyzed using SAS 9.2 and weighted to represent the Texas general population on the basis of age, sex, race/ethnicity, re-gion, telephone ownership, education level, marital status, and home ownership to account for differences in the probability of selection due to nonresponse and non-coverage.13

RESULTSTable 1 shows the prevalence of excessive drinking (binge drinking, heavy drinking, or drinking in excess of Dietary Guidelines limit)

Excessive Alcohol Consumption Among Adults with Chronic Medical Conditions in TexasNimisha Bhakta, MPH1, Lisa Wyman, PhD, MPH1, Timothy S. Naimi, MD, MPH2 1Health Promotion and Chronic Disease Prevention Section, Texas Department of State Health Services, Austin, TX 2Section of General Internal Medicine, Boston Medical Center, Boston, MA


among individuals with chronic conditions in which alcohol can play a causal or contributory role in disease progression. Among Texas adults with the chronic diseases assessed, 29.6% reported excessive drinking. (See also Figure 1.) By condition, the three patterns of excessive drinking tended to be correlated with one another (i.e., a relatively high prevalence of one alcohol consumption measure was generally associated with a high prevalence of other measures). The prevalence of binge drinking was highest among current smokers (35.3%) and lowest among adults with diabetes (7.7%). Drinking in excess of the Dietary Guidelines was highest among current smokers and lowest among adults with diabetes. More than one in four adults with one or two chronic conditions drank alcohol in excess of the Dietary Guidelines. Current smokers also had the highest prevalence for heavy drinking.

In an analysis restricted to Texas adults who consumed alcohol in past 30 days and who had any of the chronic conditions, the preva-lence of any pattern of excessive alcohol consumption was 56.3%. Among drinkers, almost three in four current smokers (74.9%) and more than one in two adults with fi ve or more mentally unhealthy days (60.3%) reported excessive drinking (data not shown).

Among Texas adults with chronic conditions but restricted to those who had a routine checkup within two years, results were generally

similar to those for the general population (data not shown). The prevalence of any excessive drinking was 27.4% for those with a recent checkup vs. 29.6% for the general population. The prevalence of binge drinking (16.5% vs.19.1%), drinking in excess of Dietary Guidelines limits (23.9% vs. 25.8%), and heavy drinking (6.9% vs. 7.7%) were also similar. By condition, the prevalence of any exces-sive drinking among those with a recent checkup was 22.7% for those with hypertension, 13.3% for those with diabetes, 25.9% for those with depression, and 47.0% among smokers. Among adults with chronic diseases and a recent medical checkup, males had a higher prevalence of excessive drinking than females for all condi-tions except for cancer (Figure 2).

We further assessed the prevalence of excessive drinking among those with chronic diseases by demographic and social character-istics (Table 2). Subpopulations who tended to have a higher preva-lence of excessive drinking included males, those aged 18-44 years, unmarried persons, employed persons, those with at least some col-lege education, and those with annual household income $50,000 or more. Males had a higher prevalence of excessive drinking for all in-dividual conditions except cancer. By age, 18-44 year-old adults were more likely to drink excessively compared with other age groups for all diseases. Unmarried adults were more likely to drink excessively compared with married adults, and employed adults had almost twice

Table 1. Prevalence of excessive alcohol consumption measures among Texas adults with chronic diseases that can be caused or exacerbatedby excessive alcohol consumption, BRFSS, 2011

Chronic Diseases Binge Drinking1 Usual Consumption Exceeding U.S. Dietary Guidelines limits2

Heavy Drinking3 Any one of three excessive alcohol consumption behaviors4

Prevalence (%)(95% CI)




Any chronic condition present (out of 8)

19.1(17.5-20.7)

25.8(24.1-27.5)

7.7(6.6-8.8)

29.6(27.8-31.3)

Obesity 16.1(14.0-18.3)

22.6(20.1-25.0)

5.1(3.9-6.3)

25.7(23.1-28.3)

Diabetes 7.7(5.3-10.2)

12.7(9.6-15.7)

3.9(1.8-5.9)

14.5(11.3-17.8)

Hypertension 14.3(12.2-16.3)

19.7(17.5-22.0)

6.0(4.8-7.2)

23.3(20.9-25.6)

Cardiovascular disease (CVD)

7.8(5.1-10.6)

16.0(12.2-19.9)

6.1(3.2-8.9)

17.5(13.5-21.5)

Cancer 12.2(5.8-18.6)

17.1(10.8-23.4)

7.7(1.5-14.0)

19.0(12.7-25.3)

Depression 16.4(13.1-19.8)

23.8(20.3-27.4)

9.0(5.9-12.1)

27.2(23.6-30.9)

Current smoker 35.3(31.6-39.1)

43.2(39.2-46.9)

15.5(12.7-18.3)

48.1(44.3-51.9)

>5 Unhealthy mental days 19.0(16.4-21.7)

26.0(23.1-28.9)

6.8(5.3-8.4)

30.2(27.1-33.3)

Hypertension and/or CVD and/or diabetes

13.8(11.9-15.6)

19.5(17.4-21.5)

5.9(4.8-7.1)

22.8(20.6-24.9)

Depression and/or 5 or more mental unhealthy days in a month

18.7(16.2-21.3)

25.9(23.3-28.6)

8.1(6.1-10.2)

29.9(27.1-32.7)

Cancer and/or current smoking

30.1(26.7-33.4)

37.1(33.7-40.4)

13.6(11.0-16.3)

41.5(38.2-44.8)

Number of Conditions (out of 8)No conditions 18.3

(16.0-20.6)25.1

(22.6-27.6)5.5

(4.2-6.8)29.6

(27.0-32.2)1-2 conditions 20.7

(18.7-22.6)27.8

(25.7-29.9)8.2

(6.8-9.5)31.8

(29.6-33.9)3+ conditions 15.0

(12.4-17.5)20.4

(17.7-23.2)6.3

(4.6-8.1)23.7

(20.9-26.6)1 Binge Drinking was defined as >1 occasions of consuming >5 drinks for men or >4 drinks for women during the past 30 days.2 U.S. Dietary Guidelines Limit for Alcohol is that if consumed, it should be up to one drink per day for women and two drinks per day formen on the days the respondent drank within past 30 days.

3 Heavy Drinking was defined as an average of >2 drinks per day for men or >1 drink per day for women during the past 30 days.4 Any one of three excessive alcohol consumption patterns (binge drinking, drinking in excess to U.S. dietary guideline or heavy drinking).

BRFSS = Behavioral Risk Factor Surveillance System


Figure 1.

TX BRFSS – Texas Behavioral Risk Factor Surveillance System

Figure 2.

TX BRFSS – Texas Behavioral Risk Factor Surveillance System CVD – Cardiovascular Disease

the prevalence of excessive drinking than unemployed adults. Adults with some college or more education with chronic conditions had higher prevalence of excessive drinking than adults who had high school education. Finally, adults with chronic conditions who had $50,000 or more annual household income had a higher prevalence of excessive drinking than adults with incomes of less than $50,000 per year.

We also assessed the prevalence of chronic conditions among those who drank excessively (Table 3). Among Texas adults who reported any of the three excessive drinking measures, 69.4% reported having one or more chronic diseases (see also Figure 1).

DISCUSSIONExcessive drinking can cause or exacerbate a variety of important chronic medical conditions.3, 7-10 We performed the fi rst-ever popu-lation-based assessment of excessive alcohol consumption among Texas adults with alcohol-associated chronic medical conditions. Overall, we found a robust intersection of chronic diseases and ex-cessive drinking, such that approximately 30% of those with one or more chronic conditions drink excessively, and 70% of those who drink excessively have one or more chronic conditions. The preva-lence of excessive drinking was particularly high among adults with

hypertension, depression, and who were current smokers.

To our knowledge, this study was unique in assessing the overlap be-tween a range of chronic conditions and several patterns of excessive alcohol consumption. A study of drinking patterns among Medicare benefi ciaries with chronic diseases by Ryan et al found that almost one-third of Medicare benefi ciaries with chronic diseases consume alcohol.14 Furthermore, the prevalence of “at-risk” drinking (defi ned as more than seven drinks per week or more than three drinks on any single day) was 6.5% among those with hypertension, which was similar to our study (9.5%).6,14 Even though the study by Ryan et al was among adults with one or more chronic conditions, it was restricted to Medicare benefi ciaries and used National Institute on Alcohol Abuse and Alcoholism’s (NIAAA) defi nition of excessive drinking.14

Excessive alcohol drinking is an important cross-cutting risk factor for many chronic diseases, and excessive drinking is largely prevent-able through policy interventions.15 However, the prevention of ex-cessive drinking through the implementation and promulgation of effective, population-based, environmental strategies has not been a focus of state and federal health agencies. Public health professionals should continue surveillance and active dissemination of data on the


Table 2. Prevalence of excessive drinking1 among Texas adults with selected chronic diseases, by socio-demographic characteristics, BRFSS, 2011

Characteristic Any chronic condition present

Obesity Diabetes Hypertension Cardiovascular disease

Cancer Depression Smoker >5Unhealthy mental days

Prevalence(%)

(95% CI)

Prevalence(%)

(95% CI)

Prevalence(%)

(95% CI)

Prevalence(%)

(95% CI)

Prevalence(%)

(95% CI)

Prevalence(%)

(95% CI)

Prevalence(%)

(95% CI)

Prevalence(%)

(95% CI)

Prevalence(%)

(95% CI)SexMale 35.0

(32.3-37.7)29.9

(26.0-33.9)18.2

(13.0-23.3)29.5

(25.8-33.2)23.2

(16.9-29.4)13.6

(8.3-18.8)29.4

(22.9-35.8)52.8

(47.7-58.0)36.0

(30.4-41.5)Female 24.2

(21.9-26.5)21.1

(18.0-24.2)10.6

(7.1-14.0)17.2

(14.4-20.0)10.7

(6.5-14.8)21.9

(13.0-30.9)26.1

(21.7-30.5)40.9

(35.3-46.5)26.2

(22.8-29.7)

Age Groups (years)18 to 44 43.2

(40.0-46.4)36.9

(32.3-41.6)26.8

(15.6-37.9)45.0

(38.5-51.6)45.2

(28.6-61.8)38.4

(17.4-59.4)41.4

(34.8-48.0)57.5

(52.0-62.9)38.7

(34.0-43.4)45 to 64 22.5

(20.2-24.7)18.8

(15.4-22.1)14.7

(10.0-19.3)21.1

(18.2-24.0)20.8

(13.9-27.6)16.5

(10.6-22.3)18.8

(14.8-22.9)37.2

(31.8-42.7)22.3

(18.3-26.4)65+ 10.3

(8.8-11.8)8.4

(5.8-10.9)8.3

(5.2-11.4)9.5

(7.8-11.1)7.7

(5.2-10.1)11.1

(7.4-14.8)8.9

(5.6-12.2)23.5

(16.2-30.7)7.5

(4.2-10.9)

Race/EthnicityWhite 29.5

(27.2-31.7)24.7

(21.4-28.0)12.7

(8.8-16.5)22.2

(19.4-24.9)15.7

(11.7-19.7)19.8

(11.7-27.9)28.5

(23.8-33.3)45.9

(41.1-50.7)33.8

(29.5-38.0)Black 23.8

(18.3-29.3)23.3

(16.0-30.6)26.3

(12.8-39.8)20.1

(13.1-27.1)17.1

(1.0-33.2)29.4

(12.2-46.7)25.0

(13.3-36.6)36.1

(24.1-48.1)22.3

(13.9-30.7)Hispanic 32.6

(29.2-36.0)28.4

(23.5-33.2)14.3

(9.2-19.4)27.7

(22.2-33.2)25.2

(15.0-35.3)12.5

(5.1-19.8)25.4

(18.5-32.2)59.8

(52.4-67.2)27.8

(22.4-33.2)Other 24.0

(14.5-33.4)25.8

(6.1-45.5)- 17.7

(5.9-29.5)- - 26.3

(6.1-46.5)35.9

(18.0-53.7)28.4

(11.9-45.0)

Marital StatusMarried 24.9

(22.9-26.9)22.8

(19.6-26.0)12.8

(9.1-16.4)20.6

(17.9-23.3)14.4

(10.3-18.4)14.9

(10.7-19.1)23.0

(18.8-27.2)42.8

(37.4-48.1)28.0

(23.7-32.2)Not married 34.4

(31.6-37.3)29.1

(25.0-33.3)16.7

(11.2-22.3)26.6

(22.6-30.6)21.0

(14.1-28.0)24.7

(11.8-37.6)30.0

(24.8-35.3)52.0

(46.8-57.2)31.9

(27.5-36.2)

Employment StatusEmployed 37.6

(35.0-40.2)32.2

(28.5-35.9)18.3

(12.5-24.0)32.6

(28.7-36.4)27.2

(18.3-36.1)29.9

(14.6-45.1)38.3

(31.8-44.9)57.5

(52.6-62.5)40.5

(35.6-45.3)Not employed 20.3

(18.0-22.5)17.3

(13.9-20.7)12.3

(8.4-16.1)15.4

(12.7-18.1)14.6

(10.2-19.0)13.2

(9.4-17.0)19.9

(16.1-23.6)34.6

(28.7-40.5)20.7

(17.0-24.3)

Education Status

graduate26.8

(24.3-29.3)20.7

(17.0-24.3)13.9

(8.9-18.8)20.1

(16.8-23.5)15.5

(9.4-21.6)10.6

(5.7-15.5)23.8

(18.6-28.9)44.7

(39.7-49.8)25.1

(20.8-29.4)Some college or more

32.3(29.8-34.7)

30.6(27.0-34.2)

15.1(11.1-19.1)

26.0(22.7-29.3)

19.6(14.5-24.7)

24.8(15.4-34.3)

30.3(25.3-35.4)

52.8(47.1-58.5)

35.7(31.5-40.0)

Annual Household Income<$50,000 28.8

(26.5-31.2)23.8

(20.4-27.3)14.4

(9.9-18.8)22.0

(18.8-25.2)17.6

(12.2-23.0)15.4

(10.5-20.3)25.6

(21.4-29.7)46.1

(41.3-50.8)27.9

(24.1-31.6)$50,000 or more 33.5

(30.4-36.5)32.0

(27.5-36.5)18.3

(12.5-24.1)27.2

(23.4-31.0)23.2

(15.9-30.5)29.5

(13.5-45.4)33.7

(25.4-42.0)57.0

(50.0-64.0)40.6

(34.0-47.2)1At least one of three excessive alcohol consumption (binge drinking, drinking in excess to U.S. dietary guidelines limit or heavy drinking) behavior present. Binge Drinking was defined as >1 occasions of consuming >5 drinks for men or >4 drinks for women during the past 30 days.U.S. Dietary Guidelines Limit for Alcohol is that if consumed, it should be up to one drink per day for women and two drinks per day for men on the days the respondent drank within past 30 days. Heavy Drinking was defined as an average of >2 drinks per day for men or >1 drink perday for women during the past 30 days.BRFSS = Behavioral Risk Factor Surveillance System

Table 3. Prevalence of selected chronic diseases among Texas adult excessive drinkers, by alcohol consumption measure1, BRFSS 2011

Excessive drinking pattern

Any chronic condition present (out of 8)

Obesity Diabetes Hypertension Cardiovascular disease

Cancer Depression Current Smoker

>5Unhealthy mental days

Prevalence(%)

(95% CI)

Prevalence(%)

(95% CI)

Prevalence(%)

(95% CI)

Prevalence(%)

(95% CI)

Prevalence(%)

(95% CI)

Prevalence(%)

(95% CI)

Prevalence(%)

(95% CI)

Prevalence(%)

(95% CI)

Prevalence(%)

(95% CI)Binge drinking 70.4

(66.8-73.9)25.6

(22.3-29.0)4.2

(2.8-5.5)23.7

(20.4-27.1)3.1

(2.0-4.3)4.1

(1.8-6.4)14.8

(11.6-17.9)35.3

(31.5-39.2)20.6

(17.6-23.5)Drinking more than dietary guideline limit

70.1(67.1-73.0)

26.2(23.3-29.1)

5.1(3.8-6.4)

24.5(21.7-27.3)

4.7(3.4-6.0)

4.3(2.5-6.1)

15.6(13.1-18.2)

31.8(28.6-34.9)

20.7(18.2-23.1)

Heavy drinking 76.1(70.8-81.3)

21.7(16.9-26.5)

5.7(2.7-8.7)

27.1(21.9-32.3)

6.5(3.4-9.6)

7.1(1.3-12.8)

21.5(14.9-28.1)

41.5(35.1-47.8)

19.8(15.4-24.2)

Any one of three excessive alcohol consumption behavior

69.4(66.6-72.1)

25.9(23.2-28.6)

5.0(3.8-6.2)

24.7(22.1-27.3)

4.4(3.3-5.5)

4.1(2.5-5.6)

15.5(13.2-17.8)

31.0(28.1-33.9)

20.7(18.4-23.0)

1At least one of three excessive alcohol consumption (binge drinking, drinking in excess to U.S. dietary guidelines limit or heavy drinking) behavior present. Binge Drinking was defined as >1 occasions of consuming >5 drinks for men or >4 drinks for women during the past 30 days.U.S. Dietary Guidelines Limit for Alcohol is that if consumed, it should be up to one drink per day for women and two drinks per day for menon the days the respondent drank within past 30 days. Heavy Drinking was defined as an average of >2 drinks per day for men or >1 drink per dayfor women during the past 30 days.BRFSS = Behavioral Risk Factor Surveillance System


burden of excessive drinking and chronic conditions and promote ef-fective policy interventions to reduce excessive drinking.16 Examples of effective environmental policy interventions to reduce excessive drinking and related harms include raising alcohol taxes, reducing alcohol outlet density, restricting days and hours of sale, implement-ing “dram shop” laws, and enforcing minimum legal drinking age laws.17-19

Contrary to popular belief, our results are consistent with those from other studies that fi nd that excessive drinking is not particularly concentrated among racial minorities or those with low educational or income levels. For example, a study by the Centers for Disease Control and Prevention showed that annual household income was positively correlated with binge drinking prevalence.20 Midanik et al in their study reported that any alcohol consumption in past year was higher among respondents with college or higher education.21

Fone et al found that respondents who never worked or were long-term unemployed and respondents with no educational qualifications showed substantially lower levels of both excessive alcohol con-sumption, including binge drinking, compared with respondents who were employed or who had higher educational attainment.22

In the U.S., studies demonstrate that few patients are routinely screened about their alcohol consumption in accordance with nation-al guidelines.23 Although it might be assumed that those who drink excessively would be unlikely to come for routine preventive care (i.e., a checkup), we found that the prevalence of excessive drink-ing among those with a recent checkup was similar to that for the population as a whole. This is consistent with fi ndings from a study by Town et al and supports other research demonstrating that low alcohol screening rates in the general population are primarily at-tributable to missed opportunities, rather than a lack of screening opportunities.24

This study is subject to caveats and limitations. Although the Texas BRFSS survey is weighted to be representative of the general Texas population, BRFSS is subject to non-coverage and non-response biases. Furthermore, self-reported data on alcohol use is under-re-ported to some extent and also subject to recall bias.25, 26 Taken to-gether, these factors suggest that our estimates of the prevalence of excessive consumption among those with chronic diseases are likely conservative. Furthermore, some respondents may have chronic con-ditions such as diabetes and hypertension that were not diagnosed by a doctor, resulting in underestimation of their prevalence based on the BRFSS questions.

In summary, Texas adults with chronic diseases that can be caused or exacerbated by alcohol have a high prevalence of excessive drinking. This could be addressed by improved clinical and public health inter-ventions to detect and prevent this important risk factor for medical morbidity and mortality, social problems, and economic costs.4

Acknowledgements: We appreciatively acknowledge the support from National Association of Chronic Disease Directors (NACDD) to provide the opportunity and funding for this project. Confl ict of Interest: All authors have no confl ict of interest to report.

REFERENCES1. Mokdad AH, Marks JS, Stroup DF, Gerberding JL. Actual causes of death in the United States, 2000. JAMA 2000;291(10):1238-1245.2. National Center for Health Statistics (NCHS). National Vital Statistics Report. 2013. Available from: http://www.cdc.gov/nchs/data/nvsr/nvsr61/nvsr61_04.pdf.3. Centers for Disease Control and Prevention (CDC). Excessive Alcohol Use - Addressing A Leading Risk For Death, Chronic Disease, and Injury: At A Glance 2011, 2013. Available from: http://www.cdc.gov/chronicdisease/resources/publications/aag/alcohol.htm#aag [Accessed on July 24, 2013].4. Sacks JJ, Roeber J, Bouchery EE, Gonzales K, Chaloupka FJ, Brewer RD. State costs of excessive alcohol consumption, 2006. Am J Prev Med

2013;45(4):474-485.5. Texas Behavioral Risk Factor Surveillance System, 2011. Center for Health Statistics, Texas Department of State Health Services.6. National Institute on Alcohol Abuse and Alcoholism. Overview of Alco-hol Consumption, Available from: http://www.niaaa.nih.gov/alcohol-health/overview-alcohol-consumption [Accessed on July 29, 2013].7. Arria AM, Van Thiel DH. The epidemiology of alcohol-related chronic disease. Alcohol Health & Research World 1992;16(3):209.8. Moushmoush B, Abi-Mansour P. Alcohol and the heart. The long-term effects of alcohol on the cardiovascular system. Arch Intern Med 1991;151(1):36-42.9. Macmahon S. Alcohol consumption and hypertension. Hypertension 1987;9(2):111-112.10. Lucenteforte E, Vecchia CL, Silverman D, Petersen GM, Bracci PM, Ji BT, Bosetti C, Li D, Gallinger S, Miller AB, Bueno-de-Mesquita HB, Tala-mini R, Polesel J, Ghadirian P, Baghurst PA, Zatonski W, Fontham E, Bamlet WR, Holly EA, Gao YT, Negri E, Hassan M, Cotterchio M, Su J, Maison-neuve P, Boffetta P, Duell EJ. Alcohol consumption and pancreatic cancer: a pooled analysis in the International Pancreatic Cancer Case–Control Consor-tium (PanC4). Ann Oncol 2012;23:374–382.11. Eckardt MJ, Harford TC, Kaelber CT, Parker ES, Rosenthal LS, Ryback RS, Salmoiraghi GC, Vanderveen E, Warren KR. Health hazards associated with alcohol consumption. JAMA 1981;246(6):648-666.12. U.S. Department of Agriculture and U.S. Department of Health and Hu-man Services, Dietary Guidelines for Americans. 2010, U.S. Government Printing Offi ce: Washington, DC.13. Centers for Disease Control and Prevention (CDC). The BRFSS Data User Guide, 2013. Available from: http://www.cdc.gov/brfss/data_documen-tation/PDF/UserguideJune2013.pdf [Accessed on August 6, 2013].14. Ryan M, Merrick EL, Hodgkin D, Horgan CM, Garnick DW, Panas L, Ritter G, Blow FC, Saitz R. Drinking patterns of older adults with chronic medical conditions. J Gen Intern Med 2013;28(10):1326-1332.15. The Community Guide. Preventing Excessive Alcohol Consumption, 2013. Available from: http://www.thecommunityguide.org/alcohol/index.html [Accessed on October 25, 2013].16. Centers for Disease Control and Prevention (CDC). Alcohol-Related Pub-lic Health Objectives and Guidelines, 2012. Available from: http://www.cdc.gov/alcohol/ph_objectives.htm [Accessed on August 16, 2013].17. Rammohan V, Hahn RA, Elder R, Brewer RD, Fielding J, Naimi TS, Toomey T, Chattopadhyay S, Zometa C. Effects of dram shop liability and enhanced overservice law enforcement initiatives on excessive alcohol con-sumption and related harms. Two community guide systematic reviews. Am J Prev Med 2011;41(3):334-343.18. Elder RW, Lawrence B, Ferguson A, Naimi TS, Brewer RD, Chattopad-hyay SK, Toomey TL, Fielding JE. The effectiveness of tax policy interven-tions for reducing excessive alcohol consumption and related harms. Am J Prev Med 2010;38(2):17-29.19. Campbell CA, Hahn RA, Elder R, Brewer RD, Chattopadhyay S, Field-ing J, Naimi TS, Toomey T, Lawrence B, Middleton JC. The effectiveness of limiting alcohol outlet density as a means of reducing excessive alcohol consumption and alcohol-related harms. Am J Prev Med 2009;37(6):556-569.20. Centers for Disease Control and Prevention (CDC). Sociodemographic Differences in Binge Drinking Among Adults --- 14 States, 2004. 2009,Avail-able from: http://www.cdc.gov/mmwr/preview/mmwrhtml/mm5812a1.htm.21. Midanik LT, Room R. Epidemiology of alcohol consumption. Alcohol Health and Research World 1992;16(3):183-190.22. Fone DL, Farewell DM, White J, Lyons RA, Dunstan FD. Socioeconomic patterning of excess alcohol consumption and binge drinking: a cross-sec-tional study of multilevel associations with neighbourhood deprivation. BMJ open 2013;3(e002337).23. U.S. Preventive Services Task Force. Screening and Behavioral Counsel-ing Interventions in Primary Care to Reduce Alcohol Misuse. Topic Page., 2013. Available from: http://www.uspreventiveservicestaskforce.org/uspstf/uspsdrin.htm [Accessed on September 10, 2013].24. Town M, Naimi TS, Mokdad AH, Brewer RD. Health care access among U.S. adults who drink alcohol excessively: missed opportunities for preven-tion. Prev Chronic Dis 2006;3(2):A53.25. Stockwell T, Donath S, Cooper-Stanbury M, Chikritzhs T, Catalano P, Mateo C. Under-reporting of alcohol consumption in household surveys: a comparison of quantity-frequency, graduated-frequency and recent recall. Addiction 2004;99(8):1024-1033.26. Midanik L. The validity of self-reported alcohol consumption and alcohol problems: A literature review. Addiction 1982;77(4):357-382.


ABSTRACTBackground: There is a strong and well-established link between fi ne particulate matter air pollution (PM2.5) exposure and cardio-vascular disease (CVD) mortality, yet no studies have looked at the association of these in major metropolitan areas in Texas, such as Harris County. Harris County has the dubious distinction of having some of the worst air quality in the United States (US). With this in mind, we explored the spatial association between PM2.5 and CVD in Harris County, Texas, at the Census tract level. The objective was to assess how increased ambient PM2.5 exposure related to CVD mortality rates in the study area, while controlling for race, income, education, and age. Methods: An estimated exposure raster was created for Harris County for two seasonal periods (February and September 2002), representing the minimum and maximum exposure levels for PM2.5, respectively. Exposure was estimated using a Kriging model at the Census tract level. PM2.5 exposure and CVD mortality rates were analyzed using an Ordinary Least Squares (OLS) regression model. Results: Controlling for race, income, and age, each 1 μg/m3 in-crease in PM2.5 exposure was associated with an increase in CVD mortality of 16.57 deaths per 100,000 for February 2002 and 14.47 deaths per 100,000 for September 2002. Conclusion: These fi ndings support previously published studies as-sociating PM2.5 exposure with CVD mortality rates. This study fur-ther identifi ed the areas of greatest PM2.5 exposure in Harris County as being the geographical locations of populations with the highest risk of CVD (i.e., predominantly older, low-income populations with a predominance of African Americans). The magnitude of the effect of PM2.5 exposure on CVD mortality rates in the study region indi-cates a need for further community-level studies in Harris County to address disproportionate exposure in vulnerable populations.

BACKGROUNDIt is estimated that in 2010 (the most recent data available) over 27 million Americans had some form of cardiovascular disease (CVD).1

The Centers for Disease Control and Prevention (CDC) listed heart attack as the leading cause of death in the US and stroke as the third leading cause of death in 2010.2 Death from CVD accounted for 30.1% of all deaths in the US in 2010.2

While genetic factors and lifestyle choices involving diet and exer-cise affect CVD risk, there is increasing scientifi c evidence for the role of environmental pollution in CVD mortality. Epidemiologi-cal studies have explored the association between particulate matter and CVD mortality and found a strong association between ambient air pollution and CVD mortality.3-5 Some studies indicate a relation-ship so strong as to suggest causality.6,7 While multiple air pollutants may infl uence CVD mortality, toxicological and epidemiological evidence strongly implicate fi ne particulate matter with an average aerodynamic diameter of less than 2.5 μm (PM2.5) as increasing CVD mortality risk.

Industrial combustion and vehicle exhaust are two primary sources of particulate matter.8 PM2.5 can form in the atmosphere with gases including sulfur dioxide, nitrogen oxide, and other volatile organic compounds. Most monitoring systems in the US focus on particulate matter with an aerodynamic diameter of less than 2.5 μm (PM2.5) or less than 10 μm (PM10). Hazardous levels of particulate matter

are most commonly found in urban areas, placing a larger popula-tion at risk of exposure. In 2006, the National Ambient Air Quality Standards (NAAQS) guidelines, required by the Clean Air Act of 1990, set maximum recommended annual exposure levels to PM2.5 at 15 μg/m3.

Spatial and temporal models have made it possible to estimate vari-ability in exposure to particulate matter across metropolitan areas more accurately and to link more precisely the level of exposures to health effects; 9,10 both of these studies revealed higher rates of CVD mortality in areas of Los Angeles with higher PM2.5 concentrations. More recently research suggests an increased risk of mortality even at concentrations below the 2006 NAAQS recommended maximum. Analysis of American Cancer Society data using a fl exible regres-sion spline model indicated that most of the increase in mortality risk from PM2.5 occurs at exposure levels between 9.5 and 16 μg/m3.11 An extension of the Harvard Six Cities study revealed that while long-term average concentrations did not exceed 13.4μg/m3, a linear dose-response association between total mortality and PM2.5 concentrations still persisted.12 The California Air Resources Board (CARB) has suggested that estimates for a threshold should be based on a range of 2.5 to 7 μg/m3.13

Studies to date on mortality risks from particulate matter exposure have led the Environmental Protection Agency (EPA) to lower the 24-hour standard for fi ne particulate concentrations in communi-ties.14 In 2008, an expert panel convened by the EPA agreed that chronic exposure to PM2.5 increased cardiovascular disease mortal-ity and suggested that the risk may be greater than previous analyses had indicated.15 In December of 2012, the EPA responded by low-ering the annual standard for PM2.5 exposure to 12 μg/m3 while maintaining the 24-hour standard at 35 μg/m3.16

The Texas Commission on Environmental Quality (TCEQ) monitors particulate matter in Harris County and other metropolitan areas in Texas, but little is known about the association between air pollu-tion and cardiovascular disease mortality in major Texas cities. The major industries in and around Harris County are the oil and other petrochemical industries, making the analysis of PM2.5 exposure in the area a prime topic for research. Annual average Harris County PM2.5 exposures often exceed the NAAQS standards.17 Previous re-search estimating PM2.5 trends in Southeast Texas, including Harris and surrounding counties, concluded that sulfate ions (32%), organic carbon (30%), and ammonium ions (9%) are the largest components of the region’s PM2.5, by mass.17 Diurnal patterns in the region show a consistent morning peak and a slightly less consistent peak in the late afternoon or early evening. High hourly average PM2.5 mass concentrations (over 40 μg/m3) tended to be associated with daily averages above the 2012 NAAQS annual standard of 12 μg/m3. Moreover, in Southeast Texas the mass concentrations and par-ticle size distributions of particulate matter were not spatially ho-mogenous.16 The placement of industrial sites and the concentrations of vehicular traffi c vary across the region, affecting the distribution of pollutants in the atmosphere.

Despite the high concentrations of airborne PM2.5 in Southeast Tex-as, little research has been done to spatially assess the potential as-sociation between CVD mortality and PM2.5 exposure in this region.

Spatial Analysis of Cardiovascular Disease Mortality and Exposure to PM2.5 in Harris County, TexasMary Ford, MS1; Linda Highfi eld, PhD2; Philomene Balihe, MPH1; D. Michael Hallman, PhD3 1Center for Community-Based Research, St. Luke's Episcopal Health Charities, Houston, TX 2Division of Management, Policy and Community Health Practice, University of Texas School of Public Health, Houston, TX3Division of Epidemiology, University of Texas School of Public Health, Houston, TX


With this in mind, the objective of this study was to spatially model PM2.5 exposure and associated cardiovascular disease mortality in Harris County, Texas, from 2002–2008 using an OLS regression model in this previously unexplored area. To the authors’ knowledge this is the fi rst study to address the associations between CVD mor-tality and PM2.5 air pollution in Harris County, Texas, at the census tract level.

METHODSStudy SiteThe study site was Harris County, Texas (Figure 1). Harris County is located in Southeast Texas near the Gulf of Mexico; the city of Hous-ton is located within Harris County. Houston is the fourth largest city in the US and continues to experience rapid population growth and shifting demographics.18 This study was conducted using data on PM2.5 exposure and CVD mortality for Harris County from 2002 through 2008. In 2002, the population of Harris County was approxi-mately 3.65 million people, which increased to approximately 3.98 million in 2008.17 Data for Harris County for the years 2002-2008, included data on population counts, proportions by race/ethnicity, and other socio-demographic variables for each census tract, were purchased from GeoLytics, Inc. (East Brunswick, NJ, USA). Geolyt-ics creates annual estimate data based on the decennial US Census data. This study received institutional review board (IRB) approval through University of Texas School of Public Health.

Data CollectionCVD mortality data for this study were obtained from the Texas De-partment of State Health Services (DSHS) Bureau of Vital Statistics for the State of Texas. The DSHS collects vital statistics from hos-pitals and medical offi ces, inclusive of national to census tract level data. As opposed to census information, vital statistics records are limited to medical conditions such as births, deaths, and accidents. The raw death data were obtained for census tracts within Harris County, Texas. We used the CDC defi nitions of CVD (International Classifi cation of Diseases, Tenth Revision or ICD-10);19 ICD-10 codes between 1 and 78 were used to identify CVD deaths in Harris County for analysis. Due to the small number of deaths in any given census tract over the period of the study, it was necessary to create an aggregate mortality count (Figure 2 – categorized as quantiles). The crude six-year average rates for CVD mortality between 2002 and 2008 were used based on previous studies that have considered chronic exposure to PM2.5 and CVD mortality outcomes.20,21 The crude six-year average rates for CVD mortality were used with co-variates added to the model during the statistical analysis to control for factors such as age, ethnicity, and income.

Data on fi ne particulate matter exposure levels were taken from both the TCEQ and EPA websites (www.tceq.state.tx.us and www.epa.gov, respectively). TCEQ is the State of Texas’ environmental regulatory body and is monitored by the EPA. EPA maintains its own air quality (AQ) monitoring systems in addition to TCEQ’s throughout Texas. Despite the presence of dozens of AQ monitors in the Harris County area, the two organizations together had only 15 sites with continuous PM2.5 monitoring stations, and only 12 of these were within Harris County. The exposure data was vastly in-consistent across years, as well as the monitor sites, thus 2002 was chosen due to the greatest availability of monitoring sites and data on PM2.5 exposure during that year. Additionally, the use of 2002 as the exposure time period allowed for a six year total lag between the measured exposure and outcome (CVD mortality rate), which was intended to capture the potential effects of chronic exposure to PM2.5 in the study area. While PM2.5 has been linked to both short and long-term CVD mortality, fewer studies have considered chronic exposure and its relationship to CVD mortality.22,23 In the few stud-ies that have considered more chronic exposure, six years was the

minimum used and was therefore adopted for this study based on these previous studies and the availability of suffi cient monitoring data in the study area.20 Hourly values were collected by both organi-zations and are available as raw data on the two websites via TCEQ’s Texas Air Monitoring Information System (TAMIS) database and the EPA’s AQS Data Mart. Monitor locations were downloaded from the TCEQ and EPA websites and imported into ArcGIS.

Monthly average PM2.5 exposure values collected at each monitor-ing site (n=15) were used to create a surface interpolation of PM2.5 exposure for seasonal highs and lows representing the months of September and February 2002 (peak and lowest exposure time points, respectively), to contrast the summer and winter effect on exposure. The use of summer and winter effect of PM2.5 exposure is consistent with the seasonal variability used in many studies.22,23 Due to the small number of PM2.5 monitors across Harris County (n=12), only a portion of Harris County (approximately 2/3 of the county) was considered eligible for surface interpolation (Figure 1). To miti-gate the potential for edge effects, interpolation was done outside the boundary identifi ed in Figure 1. The surface interpolation was sub-sequently overlaid with and cropped to the selected Harris County census tracts, using a centroid point to assign a value to each tract.

Kriging MethodThe maximum and minimum exposure measurements for each season were fi tted to two separate spherical models in Variowin, capturing the range, nugget, and sill values before being imported into ArcGIS. The exposure pattern (affected by wind direction and the location of the major PM2.5 polluters, such as the Houston Ship Channel) in Harris County resulted in a 112-degree angle on the variogram, based on a visual assessment of the direction of PM2.5 exposure. The var-iogram cloud and omni-directional variogram were evaluated.

The shapefi les containing the exposure values were imported into ArcGIS to complete the Kriging model. Within ArcGIS, the Vari-owin values of the range, nugget, and sill were entered into the Spa-tial Analyst Kriging tool, along with the directional angle. Seven spatial lags, the minimum number allowable in ArcGIS, were used. This produced a predicted raster of PM2.5 exposure in Harris County which was categorized into quantiles for mapping (Figure 3 and Fig-ure 4).

Covariate SelectionA literature review of common demographic associations with CVD mortality resulted in selection of four covariates that could serve as potential confounders or mediators of PM2.5 exposure in the anal-ysis model. Selection of covariates for inclusion in the model was based on both the literature review and data available in the Geo-lytics dataset to model confounders and mediators.24,25 Data in the Geolytics dataset was aggregate in nature (e.g., at a Census Tract level) and therefore did not include any data on individual level con-founders such as smoking status, diabetes, or physical activity. Based on the literature review and data availability, covariates evaluated for inclusion in the model included age, race, education level, and median household income at the Census tract level for 2002 to 2008 (Table 1). Because the majority of CVD mortality cases occur in the population 55 years of age and older, quartiles of the proportions of residents age of 55 years and over in each census tract were used as the measure indicating age; the fi rst quartile was used as the refer-ence category. Based on discussion in the literature, the proportion of Hispanics, Whites, and African Americans within each census tract was scaled as a continuous variable and evaluated for inclusion in the fi nal model as described in the model building process be-low.24 Education level was a categorical variable including less than a high school education, high school graduate, some college, college graduate and beyond (e.g., graduate school). Within each category,


Figure 1: Texas Commission on Environmental Quality and Environmental Pro-tection Agency air quality monitoring sites in and surrounding Harris County, Texas, 2002.

Figure 2: Crude cardiovascular disease mortality rates in Harris County, Texas, 2002–2008.


education level was treated as a proportion of the residents attaining that education level in each Census tract. Median household income within each census tract was also treated as a continuous variable after evaluation for linearity using the ladder command in Stata 11. The median household income was centered by subtracting the low-est median household income value among the included census tracts from the median household income value for each census tract. This

value was then divided by 1,000, so that a unit increase in income denoted an increase of $1,000 in median household income.

Proportions for each covariate (age, race and household income) were calculated in Stata 11, based on the annual population per cen-sus tract (Table 1).


Table 1. Summary Table for Covariate Selection.

Min Max Mean Std. DevMedian Household Income

$6,793.86 $175,283.60 $43,725.32 $23,928.22

Proportion of African-American

.0003 .9848 .2305 .2846

Proportion of Age 55 and Over

.0457 .4866 .1934 .0678

PM2.5 High 12.72 16.87 15.40 .8882

PM2.5 Low 8.01 11.29 9.912 .5974

*Observations: 478

Table 2. Seasonal High and Low Effect of Fine Particulate Matter (PM2.5) on Cardiovascular Disease Mortality.

Seasonal HighEffect

Seasonal Low Effect

Parameter Estimate-coefficient

95% Confidence Interval

Parameter Estimate -coefficient

95% Confidence Interval

PM2.5 14.47 (5.1-23.9) 16.58 (2.3-30.9)Proportion African American 117.85 (85.1-150.6) 114.57 (81.8-147.3)Median Household Income -1.5 (-1.9--1.06) -1.57 (-2--1.1)Proportion 55 and Over 81.82 (73.8-89.9) 82.78 (74.7-90.8)Intercept 99.86 (63.9-135.8) 109.52 (-72.2-146,8)

Statistical ModelingCVD mortality rate was treated as a continuous variable for statisti-cal modeling. Prior to analysis, it was evaluated for linearity both statistically and graphically using the ladder and gladder commands in Stata 11. An Ordinary Least Squares (OLS) Model was used to test the association between CVD mortality and exposure to the sea-sonal highs and seasonal lows of fi ne particulate matter. A separate model, including the covariates of age, race, education, and median household income, was built for each season to test for a difference in the association between PM2.5 exposure levels and CVD mor-tality rates. Models were built for each season independently using forward selection, starting with a bivariate model which included only CVD mortality and PM2.5 exposure and adding additional co-variates (e.g., age, race, education, and income) sequentially. After each model, the -2 log likelihood value was calculated to evaluate goodness of fi t. The model with the lowest -2 log likelihood value was selected as the best fi tting model for each season. In addition, multicollinearity was considered in each model via the assessment of a variation infl ation factor (VIF) test. Ability of the models to explain the variation in CVD mortality in each season was evaluated using the adjusted r-squared value.

RESULTSSeasonal HighsFour variables were included in the fi nal model: PM2.5 exposure, race (African American only), median household income, and age (p<0.05) (Table 2). The PM2.5 exposure coeffi cient indicated that an increase of one μg/m3 in PM2.5 exposure was associated with an in-crease of 14.47 CVD deaths per 100,000, adjusting for race, median household income, and age. The race coeffi cient predicted a one-unit increase in the proportion of African Americans per census tract re-sulted in an increase of 117.85 per 100,000 CVD mortality rate. The median household income coeffi cient predicted a decrease in CVD mortality of 1.5 deaths per 100,000 per census tract for every $1,000 increase in income. The age coeffi cient indicated that there was an increase of 81.82 CVD deaths per 100,000 per census tract for each change in quartile of the proportion of those aged 55 years and over. Cumulatively, an increase of 245.46 CVD deaths per 100,000 were predicted between the lowest and highest quartiles of the proportion of residents aged 55 years and over. The predicted CVD mortality when all of the centered covariates were equal to zero was 99.86 deaths per 100,000. The adjusted R-Squared for the resulting model was 0.5997.

Seasonal LowsFour variables were included in the fi nal model: PM2.5 exposure, race, median household income, and age (p<0.05) (Table 2). The PM2.5 beta coeffi cient indicated that an increase of one μg/m3 in seasonal PM2.5 exposure was associated with an increase of 16.57 per 100,000 in CVD mortality, adjusting for race and age. The race

coeffi cient indicated that a one-unit increase in the proportion of Af-rican Americans per census tract was associated with an increase of 114.57 CVD deaths per 100,000. The coeffi cient for median house-hold income predicted a decrease in CVD mortality of 1.57 deaths per 100,000 per census tract for every $1,000 increase in income. The age coeffi cient predicted an increase of 82.78 CVD deaths per 100,000 per census tract for each increase in the quartile of resi-dents aged 55 years and over, with an increase of 248.32 deaths per 100,000 between the lowest and highest quartiles. The predicted value of CVD mortality when all of the centered covariates were equal to 0 was 109.52 deaths per 100,000. The adjusted R-Squared for the model was 0.5997.

Spatial pattern of exposureThe spatial patterns of PM2.5 exposure in the Harris County study site indicated geographic proximity to the most at-risk populations for CVD mortality for both the seasonal highs and lows. Areas with the highest proportions of residents aged 55 years and older and those with the highest PM2.5 exposure tended to be co-located in the central portion of Harris County. Figures 5-8 show the distribution of modeled covariates in the study area, with the maps categorized into quartiles.

DISCUSSIONThe present study found a signifi cant association (p<0.05) between fi ne particulate matter exposure and CVD mortality. The results in-dicated that for every one unit increase in PM2.5 μg/m3, holding race, income, and age variables constant, there was a predicted in-crease of 14.5 deaths per 100,000 in the CVD mortality rate for the PM2.5 maximum exposure values and a predicted increase of 16.6 deaths per 100,000 for the PM2.5 minimum exposure values. This is a signifi cant fi nding, with PM2.5 having an impact on CVD mortal-ity rates in the study area. This fi nding is consistent with previous spatial analyses of PM exposure and CVD rates.11,24 These studies found a similar increase in CVD-related deaths associated with each unit increase in PM2.5. In these studies, CVD-related deaths were confounded by individual level factors such as smoking, which were not assessed in this community-level study.

The majority of the interpolated values in this study were above the EPA guidelines of allowable PM2.5 exposure levels, 15 μg/m3 an-nual ambient exposure in 2011, and the 2012 revised standard of 12 μg/m3 (Figures 3 and 4). Using the average monthly values from September 2002, in the case of the maximum exposure, did reduce some of the variability in PM2.5 exposure occurring daily during the month. Many days showed maximum exposure readings of two or three times the annual exposure limit.

The measured exposure values in February and September had a very similar effect on CVD mortality, suggesting that the current EPA stan-dard does not truly set a threshold for the impact of exposure. This


fi nding is supported by the most recent research from the American Heart Association and associated research on fi ne particulate matter, stating that there may be “no safe level” of PM2.5 exposure.26 Even at lower levels, the continuous and year-long effect of PM2.5 ex-posure may have a signifi cant impact on increasing CVD mortality.

The slightly higher effect of the seasonal low model was not ex-pected and may have been observed for a number of reasons. First, studies have shown that the exposure response relationship between PM2.5 and CVD mortality occurs at very low levels (between 9.5 and 16 μg/m3), so while ambient PM2.5 concentrations were higher in the September 2002 time period in this study, the concentrations observed in February 2002 were still more than suffi cient to lead to increased CVD mortality and could have resulted in the higher mortality rates as observed in our data.20 Table 1 and Figures 3 and 4 show the seasonal variability of PM2.5 exposure across the census tracts, which, on the average, are similar, both in spatial patterning as well as in exposure level by tract. This suggests that, considering the lack of a threshold effect, chronic exposure to fi ne particulate matter may be more important than short-term variability. Second, while the overall ambient concentration level was lower in September than February, it is possible that more people were engaged in outdoor activities in February due to the cooler weather and therefore may have received higher ambient exposures than in September when the weather in Houston is notoriously hot. Third, studies have shown that PM2.5 toxicity is related to its component species (for example, nickel) and that these components and their concentrations vary over time and are not spatially homogenous.17,18,27-28 It is possible that the component species of PM2.5 in the Houston area vary season-ally and this may have infl uenced the observed CVD mortality rates in our study leading to the higher mortality rates in February even though the overall ambient PM2.5 concentration was lower. Future studies that consider the specifi c component species of PM2.5 in the study area would be required to evaluate this possibility. Finally, it is possible that individual level factors that were not accounted for in this ecological study (e.g., smoking status, diabetes) could have contributed to the higher mortality rate observed in the low PM2.5 exposure season. This is a limitation of our study design and an area for future research. The spatial pattern of PM2.5 exposure in the Harris County study site indicated geographic proximity to the most at-risk populations for CVD mortality. Both the areas with the high-est proportions of residents aged 55 years and older and those with the highest PM2.5 exposure tended to be co-located in the central portion of Harris County, meaning that this population was receiving a disproportionate amount of exposure. The geographic areas with the lowest median household income were also located in this “hot zone” of PM2.5 exposure in central Harris County. The census tracts with the highest proportion of African Americans were also located in this area, indicating that the populations at highest risk of CVD mortality were receiving the greatest amounts of PM2.5 exposure. This may have implications for the health disparities experienced in Harris County as a result of air pollution in the county and City of Houston. Populations with already poorer health outcomes appear to be having these risks compounded by air pollution exposure, which in most cases is beyond individual control.

The Kriging methodology used in this study, despite using a mini-mum number of monitoring sites, was able to create a picture of the PM2.5 exposure in a large part of Harris County, allowing census-tract level exposure to be related to CVD mortality. We elected to use Kriging to model the exposures surfaces for PM2.5 within Harris County as opposed to a dispersion plume model such as AERMOD or CMAQ.29 While dispersion models such as these account for a variety of important factors related to ambient air pollution, such as plume height, mixing, and dispersion, the data required to param-eterize these models is complex and not easily acquired. AERMOD

requires data on not just wind direction and temperature, but also on the Bowen Ratio, surface roughness and albedo.30 CMAQ requires three-dimensional data on wind, temperature, humidity, cloud cover/precipitation and boundary layers.31 Data for Texas related to these parameters was not readily available at the time of our study. Ad-ditionally, plume dispersion models have been criticized for the un-realistic use of Gaussian distributions to model dispersion patterns and their limitations in short spatial scale modeling (such as in this study).20,32 Our Kriging approach used data directly from each moni-toring site specifi cally on PM2.5 and allowed for variation in mea-sured values to occur at a local spatial level and within a short spatial scale (e.g., February and September 2002). Additionally, we were able to address wind direction through the use of our model. Finally, in a review of previous studies comparing the effectiveness of Krig-ing to dispersion modeling for particulate matter, comparable results were found between the modeling approaches in an urban environ-ment such as the one in this study.32 The lack of previous studies on PM2.5 and CVD mortality in Harris County make this study a good fi rst step toward understanding the associations between these in Harris County, Texas. Future studies that compare the predictions from dispersion models such as AERMOD or CMAQ to Kriging es-timates would provide valuable insights.

Study Limitations The greatest limitation of this study was the small number of air quality monitors in and surrounding Harris County. This study used a minimum of necessary monitoring points (n=15) to create the ex-posure surface interpolation. The inconsistency across years when PM2.5 exposure data was collected limited the monitors and years available to use, requiring the study to use older data. The poor spatial coverage of the monitors in and surrounding Harris County meant that Kriging estimates covered only about two-thirds of Harris County, despite having CVD and covariate data for the whole area. This limited the ability of this study to analyze the effects of PM2.5 on the entire county. Considering the strong association between PM2.5 and CVD mortality that has been supported by previous stud-ies,14,21 it was surprising that the monitoring of this air pollutant was so limited in such a large metropolitan area. Air quality monitors collecting data on ozone, for example, are plentiful in the region, making analysis of this pollutant much easier to conduct.

Additionally, the data and modeling approach used in this study limit our ability to establish a cause-effect relationship between PM2.5 exposure and CVD mortality in Harris County. Our regression re-sults indicate an association between ambient PM2.5 exposure and CVD mortality when controlling for confounders such as race, age, and income, however we cannot assess causality in this study pri-marily due to the study design (ecological study), the short period of exposure assessed, the unknown “true” lag time between exposure to PM2.5 and CVD mortality, and the lack of data on other impor-tant confounding variables that occur in individuals, such as smoking status. This is the fi rst study to consider ambient PM2.5 exposure in Harris County as it relates to CVD mortality. Future studies that as-sess PM2.5 exposure and CVD mortality in this region can further contribute to our understanding of the association between these and begin to build the evidence base for causality in our local area.

The data used in this study were all aggregate, leading to the possibil-ity that the study could suffer from the ecological fallacy, in which aggregate-level fi ndings may not refl ect individual-level associa-tions.33 While the ecological fallacy is a danger in studies such as this, it is widely accepted that there are certain studies in which pop-ulation-level data may be more appropriate. If the variability of the exposure among the population of interest is low, but between popu-lation variation is high, then associations may be missed by looking at individual data. In the case of PM2.5 exposure, the variability of


exposure was small within census tracts and greatest across census tracts, making aggregate analysis suitable. Additionally, in targeting potential interventions for PM2.5 exposure, census tract level data would be very relevant to identifying small neighborhoods and com-munities with the highest risk, making the use of this level of analysis appropriate. It is likely that any intervention would be implemented at the group level rather than the individual level.

Recommendations for Future StudiesFuture studies assessing the impact of PM2.5 exposure in Harris County, Texas, on CVD mortality or related outcomes will experi-ence many of the same limitations in terms of lack of available air quality data. Future studies may consider the use of dispersion mod-els or comparison of various approaches to modeling PM2.5 in the study area over time. It may be valuable to consider assessing the PM2.5 exposure in a different way than looking at the maximum and minimum monthly averages. Seasonal trends in PM2.5 or capturing more extreme (daily or weekly) values may reveal interesting results. Further research on the lag-time associated with chronic exposure to PM2.5 may reveal a more accurate procedure for analyzing its effects.

List of AbbreviationsCVD – Cardiovascular DiseasePM2.5 – Fine particulate matterEPA – Environmental Protection AgencyTCEQ – Texas Commission on Environmental Quality

Competing InterestsThere are no competing interests to declare.

Authors ContributionsWe attest that 1) each named author contributed to the conception, design, analysis, and interpretation of the project as well as the writ-ing of the paper, and 2) each has approved the version being submit-ted.

AcknowledgementsThe authors would like to acknowledge St Luke’s Episcopal Health Charities’ for funding this study. The funder had no role in the study design. Only the authors were responsible for study design, data col-lection, analysis, interpretation, and writing.

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11. Abrahamowicz M, Schopfl ocher T, Leffondre K, et al. 2003. Flexible Modeling of Exposure-Response Relationship Between Long-Term Average Levels of Particulate Air Pollution and Mortality in the American Cancer So-ciety Study. J Toxicol Environ Health. 66:1625-1654. 12. Laden F, Schwartz J, Speizer F, et al. 2006. Reduction in Fine Particulate Air Pollution and Mortality: Extended Follow-up of the Harvard Six Cities Studies. Am J Resp Crit Care Med. 173:667-672. 13. California Environmental Protection Agency. May 22, 2008. Air Re-sources Board, Methodology for Estimating Premature Deaths Associated with Long-term Exposures to Fine Airborne Particulate Matter in California. 14. Dockery DW, Stone PH. 2007. Cardiovascular Risks from Fine Particu-late Air Pollution. N Engl J Med 365:511-513.15. American Lung Association. 2008. Highlights of Recent Research on Par-ticulate Air Pollution: Effects of Long-Term Exposure. 16. Environmental Protection Agency. 2012. EPA’s Revised Air Quality Stan-dards for Particle Pollution: Monitoring, Designations and Permitting Re-quirements. Available: http://www.epa.gov/pm/2012/decfsimp.pdf 17. Russell M, Allen DT, Collins DR, et al. 2004. Daily, Seasonal, and Spatial Trends in PM 2.5 Mass and Composition in Southeast Texas. Aerosol Sci Tech. 38:14-26. 18. U.S. Census Bureau. 2011. Harris County QuickFacts From the US Cen-sus Bureau. Available: http://quickfacts.census.gov/qfd/states/48/48201.html 19. Centers for Disease Control and Prevention. 2010. International Classifi -cation of Diseases, Tenth Revision, Clinical Modifi cation. 20. Brook RD, Franklin B, Cascio W, et al. 2004. Air pollution and cardiovas-cular disease A statement for healthcare professionals from the expert panel on population and prevention science of the American Heart Association. Cir-culation. 109(21):2655-2671.21. Pope CA, Burnett RT, Thurston GD, et al. 2004. Cardiovascular Mortal-ity and Long-Term Exposure to Particulate Air Pollution: Epidemiological Evidence of General Pathophysiological Pathways of Disease. Circulation. 109:71-77.22. Nawrot TS, Torfs R, Fierens F, et al. 2007. Stronger associations between daily mortality and fi ne particulate air pollution in summer than in winter: evidence from a heavily polluted region in Western Europe. J Epidemiol Commun H. 61:146-149.23. Shen, Z. Arimoto, R. Cao, J. et al. 2008. Seasonal Variations and Evidence for the Effectiveness of Pollution Controls on Water-Soluble Inorganic Spe-cies in Total Suspended Particulates and Fine Particulate Matter From Xi’an China. J Air Waste Ma. 58(12)1560-1570. 24, Thomas AJ, Eberly LE, Smith GD, et al. 2005. Race/Ethnicity, Income, Major Risk Factors, and Cardiovascular Disease Mortality. Am J Public Health. 95(8):1417-1423.25. Diez- Roux AV, Link BG, Northridge ME. 2000.”A multilevel analysis of income inequality andcardiovascular disease risk factors. Soci Sci Med. 50(5):673-687.26. Brooke RD, Rajagopalan, S, Pope CA. 2010. Particulate Matter Air Pollu-tion and Cardiovascular Disease. An Update to the Scientifi c Statement From the American Heart Association. Circulation. 21:2331-2378. 27. Huang,W, Junji Y, Lingzhen D, et al. 2012. Seasonal variation of chemi-cal species associated with short-term mortality effects of PM2. 5 in Xi’an, a Central City in China. Am J Epidemiol. 175(6):556-566.28. Ito K, Robert M, Zev R, et al. 2011. Fine particulate matter constituents associated with cardiovascular hospitalizations and mortality in New York City. Environ Health Perspect. 119(4):467.29. U. S. Environmental Protection Agency, Offi ce of Air Quality Planning and Standards, Air Quality Assessment Division. 2009. AERMOD Imple-mentation Guide. Available at: http://www.epa.gov/ttn/scram/7thconf/aer-mod/aermod_implmtn_guide_19March2009.pdf30. Cimorelli AJ, Wilson RB, Perry SG, et al. 1998. Minimum Meteorologi-cal Data Requirements for AERMOD -- Study and recommendations. Avail-able at: http://epa.gov/scram001/7thconf/aermod/degrade.pdf31. U.S. Environmental Protection Agency, Atmospheric Modeling and Anal-ysis Research. 2013. Community Multi-scale Air Quality Model (CMAQ). Available at: http://www.epa.gov/AMD/Research/RIA/cmaq.html32. Jerrett M, Arain M, Kanaroglou, P, et al. 2005. A review and evaluation of intraurban air pollution exposure models. J of Expo Sci Environ Epidemiol. 15:185-204.33. Rothman, KJ. Modern Epidemiology: Second Edition. Lippincott-Raven Publishers, Philadelphia, PA. 1998;p. 469.


On November 20, 2013, the Department of State Health Services in Austin, Texas, hosted GIS Day, where presentations were given and posters displayed that described the importance and utility of GIS (Geographic Information Systems) analyses in public health.

Following is a list of presentations from GIS Day. For more informa-tion on particular presentations, please contact Tracy Haywood at [email protected].

1. Global Incident MapSuzanne Burnham, DVM, State Agro-terrorism /Bioterrorism Coor-dinator, Adjunct Assistant Professor Texas A&M

2. Comparison of Rural and Urban Concentrated Laundry De-tergent Pack Exposures among Young Children Mathias Forrester, BS, Epidemiologist

3. GIS Analysis and ArcGIS onlineKaren Lizcano, BS, ESRI Solutions Engineer

4. Dynamic GISDavid Gruber, Director Regional and Local Health Services

5. A Basic Data Map in Epi Info 7Gary Heseltine, MD, Emerging and Infectious Disease Branch

6. Rabies - ORVPLaura Robinson, DVM, Zoonosis Control Branch

7. GIS and the Seafood and Aquatic Life GroupMichael Tennant, MS, BS, Environmental Specialist, Seafood and Aquatic Life Group

8. GIS Response to West Nile VirusDuke Ruktanonchai, MD, Epidemic Intelligence Service Offi cer, Centers for Disease Control and Prevention

Following are abstracts of some of the posters from GIS Day. For more information on particular abstracts, please contact the corre-sponding author at the email provided.

1. Local Spatial Autocorrelation of People Living with HIV and Socioeconomic Indicators in Selected Metropolitan Areas in TexasSonia Arbona, Jennifer Chase, Miranda Fanning, Praveen Pannala, Sharon MelvilleTexas Department of State Health Services, Austin, Texas, United Statessonia.arbona@ dshs.state.tx.us

Introduction: Disease mapping has been used in spatial epidemio-logical studies for visualization and hypothesis generation. Maps of HIV distribution accompanied by socioeconomic variables may lead to a better understanding of the relationship among the variables. A further step investigates the type and extent of their spatial cor-relation. Background: Texas has a large population; six of its cities have more than 500,000 people. Five of these cities and surround-ing counties have been designated as Eligible Metropolitan Areas (EMAs) because of the size of their populations of people with HIV. Infection with HIV, like many other health conditions, is embedded

in the larger environment in which we live. Purpose/Objectives, Hy-potheses or Research Questions: This analysis examines the spatial distribution of people living with HIV (PLWH) as of 2010 in the area comprising the fi ve EMAs in the context of three socioeconomic variables. Specifi cally, we sought to understand how varying mag-nitudes of these socioeconomic variables (i.e., low or high poverty rate) are related spatially to varying proportions of PLWH (i.e., low or high rate). Methods: The analysis uses a Local Indicator of Spatial Association (LISA) to derive localized estimates of association between rates of PLWH and one of three indicators of socioeconomic conditions ag-gregated at the census tract level: percent living in poverty, percent unemployed, and percent whose education never reached 9th grade. Statistical signifi cance association is determined by Monte Carlo randomization of the LISA value. Only those associations with a level of signifi cance at < 0.05 are used in this analysis. Results: In all fi ve EMAs, the broad tendency is for clusters of cen-sus tracts with high rates of PLWH to associate with high rates of one the socioeconomic variables being examined (HH) within the major city of the EMA. Counties surrounding the major city within the EMA have clusters of predominantly low rates of PLWH in as-sociation with clusters of low rates of the socioeconomic variable (LL). Some sectors of the EMAs also have mixed associations of clusters of low rates of socioeconomic variables and high rates of PLWH (LH) or high rates of socioeconomic variables and low rates of PLWH (HL). Discussion: By and large, the LISA maps tended to confi rm studies on the association between socioeconomic disadvantage and HIV. The choices people have to improve their health conditions may be limited by the inequality in available resources where they live. One expression of this inequality is a comparatively high rate of disease. Limitations: The examination of just three socioeconomic variables runs the risk of producing oversimplifi ed conclusions about their re-lationship to one another. Conclusions: This analysis identifi ed neighborhoods in the EMA that combined socioeconomic disadvantage and high rates of PLWH. The LISA method provides an effi cient way to detect and visual-ize these types of correlations at the local level that are not readily discernible when pooling data at the state or regional level. Implica-tions: Future studies must continue to identify local level trends in order to support policy development, resource planning and care for improved health outcomes.

2. Fluoride in Drinking Water and Childhood and Adolescent Osteosarcoma in TexasNatalie Archer, Tom Napier, John VillanacciTexas Department of State Health Services, Austin, Texas, United [email protected]

Background: The purpose of this study was to examine the asso-ciation between fl uoride levels in drinking water and osteosarcoma among children and adolescents in Texas; to date, such studies ex-amining this relationship have been equivocal. Using areas in Texas with high and low naturally-occurring fl uoride, as well as areas with optimal fl uoridation, we were able to examine a wide range of fl uo-ride levels in drinking water. Methods: This was a population-based case-control study, with both cases and controls obtained from the Texas Cancer Registry. Eligible cases were Texas children and adolescents <20 years old diagnosed

GIS Day, Texas Department of State Health Services, Austin, Texas, November 20, 2013Tracy Haywood, Mathias B ForresterTexas Department of State Health Services, Austin, Texas


with osteosarcoma between 1996-2006. Controls were sampled from children and adolescents diagnosed with either brain cancer or leu-kemia during the same time frame, at a 4:1 control/case ratio. Us-ing geocoded patient addresses at time of diagnosis, we estimated each patient’s fl uoride exposure level based on the fl uoride level of their residence’s public water supply (PWS). Unconditional logistic regression models were used to assess the association between os-teosarcoma and fl uoride level in drinking water, adjusting for several demographic risk factors. Results: A total of 308 osteosarcoma cases, 598 leukemia controls, and 604 brain cancer controls met selection criteria and were able to be assigned a corresponding PWS fl uoride level. Fluoride level was not associated with osteosarcoma, either when analyzed in a univari-able analysis or when adjusting for age, sex, race, and poverty in-dex. We also conducted stratifi ed analyses by sex, and no association between PWS fl uoride level and osteosarcoma was observed either among males or females. Conclusions: Our study did not fi nd a rela-tionship between the fl uoride level in drinking water and childhood/adolescent osteosarcoma in Texas.

3. Comparison of Rural and Urban Concentrated Laundry Detergent Pack Exposures Among Young ChildrenMathias B ForresterTexas Department of State Health Services, Austin, Texas, United Statesmathias.forrester@ dshs.state.tx.us

Background: In early 2012, products consisting of small, single-dose “packs,” “pods,” or “pouches” that contain concentrated liquid laundry detergent in a water-soluble membrane appeared on the mar-ket in the US. Poison centers soon began to receive calls about po-tentially serious exposures to these products among young children. An initial investigation using Texas poison center data noticed that the reported pediatric exposure rate was much higher in rural than urban counties. Methods: Cases were all laundry detergent pack exposures among patients age 5 years or less reported to Texas poison centers dur-ing January 1, 2012-September 15, 2013, where the caller county was known and was within the state. Each county in the state was designated as rural or urban based on US Offi ce of Management and Budget defi nitions of metropolitan and non-metropolitan, and the counties were grouped into rural and urban counties. The distribution of exposures was determined for selected demographic and clinical factors, and comparisons were made between the two groups. Results: There were 226 rural exposures (rate per 100,000 popula-tion age 5 years or less - 90.9) and 1,048 urban exposures (rate per 100,000 population age 5 years or less - 50.7). (In comparison, the rate for all other laundry detergent products was 38.2 for rural and 35.4 for urban counties.) The distribution by most common laundry pack brands was Tide (76% rural vs 77% urban), All (14% rural vs 12% urban), and Purex (8% rural vs 7% urban). Fifty-two percent of rural and 54% of urban patients were male; the mean age was 1.86 for rural and 1.90 for urban patients. The distribution of exposures by most common reported route was ingestion (89% rural vs 90% ur-ban), ocular (13% rural vs 13% urban), and dermal (11% rural vs 9% urban). The management site was on site (58% rural vs 57% urban), already at/en route to a healthcare facility (25% rural vs 29% urban), and referred to a healthcare facility (15% rural vs 13% urban). Nine percent of rural and 11% of urban patients had serious outcomes. Discussion: The reported exposure rate for concentrated laundry detergent packs among young children in rural counties was 79% higher than in urban counties (as compared to 8% higher for all other laundry detergent products). This may be due to differences between

rural and urban counties with respect to use of the laundry detergent packs, occurrence of potentially adverse exposures, and/or the ten-dency to report such exposures to poison centers. The patient demo-graphics and circumstances of the exposure were similar between the areas. In spite of this, Texas poison centers were slightly more likely to refer rural patients to healthcare facilities, although these exposures were slightly less likely to be serious.

4. Geographic Distribution of Exposures to Selected Products Illegal in the United States but Available in MexicoMathias B ForresterTexas Department of State Health Services, Austin, Texas, United Statesmathias.forrester@ dshs.state.tx.us

Background: There are a number of products that are illegal in the United States but available in other countries. Miraculous Insecti-cide Chalk is manufactured in China; although illegal in Mexico, it is available there. Dipyrone (metamizole) is an analgesic and antipyret-ic agent banned in the United States but legal in Mexico. Redotex is a weight loss supplement not approved in the United States but is legal in Mexico. Since Texas shares a long border with Mexico and has a large Hispanic population, it is possible that products such as these might be purchased in Mexico and brought into the United States. Methods: Cases were all insecticide chalk, dipyrone, and Redotex exposures reported to Texas poison centers during 2000-2012 where the caller county was known and was within the state. The number of calls from each county was determined. The rate for each Public Health Region (PHR) was calculated based on Census 2000 data. Results: There were 233 insecticide chalk, 104 dipyrone, and 31 Redotex exposures meeting study criteria. For insecticide chalk, the rate per 1,000,000 population ranged from 25.56-51.78 in the PHRs in southern and western Texas to 0.00-0.98 in PHRs in northeastern Texas. For dipyrone, the rate per 1,000,000 population ranged from 12.08-32.86 in the PHRs in southern and western Texas to 0.00-2.92 in PHRs in northern and eastern Texas. For Redotex, the rate per 1,000,000 population ranged from 13.81 in the PHR in southernmost Texas to 0.00-0.18 in PHRs in northern and eastern Texas. Discussion: Comparatively few insecticide chalk, dipyrone, and Redotex exposures were reported to Texas poison centers. The ex-posure rate tended to be highest closest to the Mexico border and declined north and east from the border. This suggests that the source for many of these products is likely to be Mexico, either directly or indirectly. Although exposures tended to be concentrated close to the Mexico border, they were reported from throughout the state. This suggests that exposures to substances illegal in the United States but available in Mexico might occur far from the border, so even health-care providers far from the Mexico border might need to be aware of these products.

Texas Public Health AssociationPO Box 201540Austin, Texas 78720-1540

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1948 V. M. Ehlers*1949 George W. Cox, MD*1951 S. W. Bohls, MD*1952 Hubert Shull, DVM*1953 J. W. Bass, MD*1954 Earle Sudderth*1956 Austin E. Hill, MD*1957 J. V. Irons, ScD*1958 Henry Drumwright1959 J. G. Daniels, MD*1960 B. M. Primer, MD*1961 C. A. Purcell*1962 Lewis Dodson*1963 L. P. Walter, MD*1964 Nell Faulkner*1965 James M. Pickard, MD*1966 Roy G. Reed, MD*1967 John T. Warren*1968 D. R. Reilly, MD*1969 James E. Peavy, MD*1970 W. Howard Bryant*1970 David F. Smallhorst*1971 Joseph N. Murphy, Jr.*1972 Lola Bell*1972 B. G. Loveless*1973 Barnie A. Young*

1974 Ardis Gaither*1975 Herbert F. Hargis*1975 Lou M. Hollar*1976 M. L. McDonald*1977 Ruth McDonald1978 Maggie Bell Davis*1978 Albert Randall, MD*1979 Maxine Geeslin, RN1979 William R. Ross, MD*1980 Ed L. Redford*1981 W. V. Bradshaw, MD*1981 Robert E. Monroe*1982 William T. Ballard*1983 Mike M. Kelly, RS1983 Hugh Wright*1984 Hal J. Dewlett, MD*1984 C. K. Foster1985 Edith Ehlers Mazurek1985 Rodger G. Smyth, MD*1986 Helen S. Hill*1986 Henry Williams, RS*1987 Frances (Jimmie) Scott*1987 Sue Barfoot, RN1988 Jo Dimock, RN, BSN, ME1988 Donald T. Hillman, RS*1989 Marietta Crowder, MD

1990 Robert Galvan, MS, RS1991 Wm. F. Jackson, REHS*1992 Charlie Norris*1993 T. L. Edmonson, Jr.*1994 David M. Cochran, PE1995 JoAnn Brewer, MPH, RN*1996 Dan T. Dennison, RS, MT, MBA1997 Mary McSwain, RN, BSN1998 Robert L. Drummond1999 Nina M. Sisley, MD, MPH2000 Nancy Adair2001 Dale Dingley, MPH2002 Stella Flores2003 Tom Hatfi eld, MPA2004 Janet Greenwood, RS2005 Charla Edwards, MPH, RN2006 Janice Hartman, RS2007 Jennifer Smith, MSHP2008 Catherine D. Cooksley, DrPH2009 Hardy Loe, M.D.2010 John R. Herbold, DVM, PhD2012 Bobby D. Schmidt, M.Ed2013 Sandra H. Strickland, DrPH, RN*deceased

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Ron Anderson, MDMinnie Bailey, PhDNed V. Brookes, PEOran S. Buckner, Jr., PE, RSBurl Cockrell, RS

Exa Fay HootenRobert MacLean, MDSam MarinoAnnie Lue MitchellLaurance N. Nickey, MD

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Volume 66 Issue 1

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