1. Addressing Health Literacy and Health Communication in Diabetes and Obesity
Russell L. Rothman MD MPP
Associate Professor, Internal Medicine & Pediatrics
Director, Center for Health Services Research
Chief, Internal Medicine/Pediatrics Section
Co-Director, Community Engaged Research, VICTR
Associate Director, Center for Diabetes Translational Research
Vanderbilt University Medical Center
Thank you. It is a pleasure to be here with you this morning.
I am going to give a brief overview of our Center for Health Services Research and then focus on research that we have been doing that examine the role of health literacy and health communication in patient care.

2. Disclosed no conflict of interest.
Presenter Disclosure
Disclosed no conflict of interest.

3. Why inadequate diabetes care?
Community
Cultural beliefs
Access to Care
Access to Diet
Access to Exercise
Environmental Factors
System
Insurance/Financing
Focus on Acute Care
Lack of EMR
Bureaucracy
Quality
Patient
Physiology/genetics
SES factors
Knowledge/Attitudes/Beliefs
Behaviors/ Adherence
Health Literacy
Provider
Knowledge
Attitudes/Beliefs
Behaviors
Incentives
Health Communication Skills

4. Increasing Concern about Literacy and Numeracy Skills
Ok, I would now like to transition to discussing my own research related to Health Literacy and health Communication.
Some of you may be aware that literacy issues are of increasing concern in this country.

5. Literacy is a Complex Skill
Cultural and
Conceptual
Knowledge
Speaking
Reading
Numeracy
Listening
Writing
Print Literacy
Oral Literacy
Literacy actually consists of numerous components including listening and speaking skills – which are one’s oral literacy, writing andreading skills – or print literacy, and numeracy – or ones math skills.
IOM, Health Literacy, 2004

6. Poor Health Literacy is Common
Health literacy: “the capacity to obtain, process, and understand basic health information and services needed to make appropriate health decisions.”
Over 90 million Adult Americans have poor literacy skills and over 110 million have poor quantitative skills
Difficulty navigating health system, understanding materials and recommendations, performing self-care, etc.
And Health Litearcy is defined as the “the capacity to obtain, process, and understand basic health information and services needed to make appropriate health decisions”
In 1992 and in 2003 the US Dept of Education did a national study which found that over 90 million americans have difficulties with literacy and over 110 million have poor quantitative or numeracy skills. The avg american only reads at the 8th-9thgrade level, and their math skills are typically worse.
As you can imagine, having poor literacy and numeracy skills is particualrly challenging when trying to navigate our health care system – which is getting more and more complex and which is asking patients to do more and more to take care of themselves.

7. Numeracy is an Important Component
“The ability to understand and use numbers and math skills in daily life”
Calculations, deduction/logic, interpretation of graphs/labels, time, probability, etc.
Highly correlated with literacy, but not perfect
Numeracy skills are particularly important in health care where we ask patients to understand risk and probability, read food labels, understand medicaiton dosing and other issues. And our research group did some of the seminal research on the role of numeracy in health. We defined numeracy as “the ability to understand and use numbers and math skills in daily life”
While most people think of numeracy as being about calcualtions, it also includes a host of other skills including deduction/logic, interpretation of graphs/labels, time, probability, etc.
And while patient literacy is highly correlated with numeracy it is not perfect. There are a lot of people with adequate literacy skills, but poor numeracy skills. Like Calvin in this old Calvin and Hobbs cartoon – they had a hard time with math back in elementary school – and now they are very intimidated when they see numbers. They break out in a sweat, they get anxious – and here we are in health care talking with people and asking them to do a lot of math!
Calvin and Hobbs, Bill Watterson, Universal Press Syndicate, Released on: Friday, Oct 10th 1986.
Rothman et al, J Health Comm, 2009

8. Why is literacy important in health care and research?
Patients with low literacy have:
Trouble reading prescriptions, following medical instructions
Trouble understanding educational materials
Trouble interpreting and applying numbers to health situations
Trouble consenting to research or procedures
Difficulty answering survey items or other measures
Difficulty following research protocols

9. Why is numeracy important in health care?
Patients with low numeracy may have trouble:
Understanding dosages of medications
Understanding the timing of when to take medications or have them refilled
Interpreting nutritional information
Understanding volume status
Interpreting blood sugars, adjusting insulin
Understanding risks and probability

10. What it is like for patients…

11. Many Outcomes Associated with Literacy
Behaviors
Breastfeeding
Behavioral problems
Adherence to medication
Smoking, Substance abuse
Knowledge
Food label and portion size understanding
Birth control knowledge
Emergency department instructions
Asthma knowledge
Hypertension knowledge
Health Outcomes/Services
General health status
Hospitalization
Mortality
Emergency department use
Depression
Diabetes control
HIV control
Prostate Cancer Stage
BMI
Mammography
Pap smear, STD Screening
Immunizations
Cost
Over the past decade there have been a series of predominantly cross sectional studies, including many by our group that have now shown that literacy is significantly associated with health behaviors, health knowledge, and even health outcomes. For example, studies have shown that poor health literacy is associated with increased risk for hospitalization and even mortality. Most of these studies have shown that literacy is important even after adjusting for covariates such as education level, SES, age, income, and other factors.
DeWalt, JGIM 2004
McCormack, Annals of Internal Medicine 2011

12. Literacy/Numeracy & Diabetes
Literacy skills needed:
Knowledge of disease prevention and disease
Understanding of educational materials
Performance of self-management tasks
Interaction with medical system
Numeracy skills needed:
Understanding of risk and probability
Understanding weight status
Understanding medications
Understanding nutrition information
Understanding exercise
Interpreting glucose and other measures
Studies have shown that diabetes patients with low literacy can have worse knowledge of their diabetes, worse blood sugar control, and higher diabetes related complications.
Numeracy may be particularly important for patients with diabetes. Patients with diabetes need to use numbers on a daily basis for such tasks as:
Glucose monitoring
Carbohydrate counting
Adjusting insulin based on blood sugar
Adjusting insulin based on carbohydrates
Insulin pump adjustment

13. Literacy and Diabetes Outcomes
Schillinger, JAMA, 2002

14. Numeracy and Food Labels
One of the next studies we did, was a study to examine how patients understand food labels. As you can see food labels are actually very dense – with a lot of complicated information. Understanding of food labels can be particularly important for followlojgn a good diet- especially for patients with diabetes

15. Study Design Design: Cross sectional survey
Setting: Primary care clinic
Instruments:
Demographics
Food Label Usage and Attitudes
Assessed literacy with REALM
Assessed numeracy with WRAT3
26 item food label survey
Rothman et al, AM J Prev Med, November 2006

16. Demographics Variable (n=200) Avg (SD) or Percent Age 43 (15) Female
72%
African American
25%
Family Income < $20,000
Private Insurance
75%
HS education or less
33%
Chronic Illness requiring dietary restriction
41%
BMI (n=151)
30 (7)
Reads Food Labels
89%

17. Literacy, Numeracy, Food Labels
Variable (n=200)
Percent
Literacy (REALM) <= 8th Grade
23%
Numeracy (WRAT) <= 8th Grade
63%
Food Label Score (Range 30% - 100%)
69% (19%)
Internal Reliability (KR 20)
0.87

18. Calculating Fiber Intake
How many grams of dietary fiber are in 5 candies?
Correct Response: 1 gram
Percent Correct 66 %

19. Nutrition Score by Characteristics
Variable (n=200)
Mean Nutrition Score (SD)
p value
Age
< 65
≥ 65 yrs
70 (21)
59 (19)
0.04
Gender
Female
Male
67 (21)
74 (20)
Race
White
Black
Other
74 (19)
57 (18)
77 (18)
<0.0001
Private Insurance
Yes No
73 (20)
Chronic Illness*
65 (20)
72 (20)
BMI
< 30
≥ 30
73 (21)
66 (20)

20. Nutrition Score Correlations
Higher performance on the food label survey was significantly correlated with:
Higher education (r=0.44)
Higher income (r=0.56)
Higher literacy (r=0.52)
Higher numeracy (r=0.67)

21. Conclusions Patient comprehension of food labels was fair.
Comprehension was worse when patient needed to apply serving sizes, or perform multi-step math.
Comprehension was worse for patients who were obese or had chronic illness
Comprehension was highly correlated with math and literacy skills

22. Literacy, Numeracy, Food Labels
This study generated a lot of press – including a story on CNN, the NY Times, the Tennessea, and over 200 other newspapers, televion, and other media outlets. Our hope is that this study will encourage providers to be more careful in what they recommend to their patients, and this study has also opened a dialogue for us with the FDA about the design of current food lavels and how to make them easier for people to understand.

23. Portion Size Study Enrolled 164 pts
20 Years Ago
Today
Enrolled 164 pts
Asked to serve “single serving” of 4 items, and then told to serve actual amount (in oz or grams)
2/3 had inaccurate estimation of portion sizes
Poor estimation linked with literacy and numeracy
500 calories
1,025 calories
333 calories
590 calories
85 Calories
250 Calories
Huizinga et al, Am J of Prev Med, 2009

24. Numeracy and Diabetes

25. Diabetes and Numeracy Study
Design: Cross sectional survey
Setting: Endocrine and Primary Care Clinics
Instruments:
Demographics
A1C and Meter Downloads
Assessed literacy with REALM
Assessed math skills with WRAT3
Diabetes Knowledge (DKT), Self Care (SSCA)
Assess diabetes numeracy with DNT
Cavanaugh et al, Annals of Internal Medicine, 2009

26. Demographics Variable (n=398) Number (%) or Mean (SD) Age, yrs (SD)
54.2 (12.9)
Female, No. (%)
202 (51)
Race, No. (%)
White
Black
Other
249 (63)
134 (34)
14 ( 3)
Education, No. (%)
≤ High School or GED
Some college
College or more
168 (43)
115 (29)
109 (28)
Literacy Status (REALM), No (%)
≤ -8th grade
≥ High School
124 (31)
273 (69)
Numeracy Skills (WRAT), No (%)
≤ 8th grade
276 (69)
122 (31)
Type 2 Diabetes (%)
341 (86)
On Insulin (%)
241 (61)
A1C (SD)
7.6 (1.7)

27. Overall DNT Results Mean score 61% (SD 25%) Range 5%-100%
Internal Reliability: 0.95
Trouble Spots
Interpreting serving sizes
Fractions or decimals
Applying multi-step regimens (ex. sliding scale and carb-ratios)
Applying titration instructions

28. Serving Size
If you ate the entire bag of chips, how many total grams of carbohydrate would you eat?
Correct Response: 63 gms
Correct: 44%

29. Monitoring
Your target blood sugar is between 60 and 120. Please circle the values below that are in the target range (circle all that apply): 55
145
118
Correct Response: Circle 118 only
Percent Correct: 74%
Here are a few sample questions:
In this question, we told patients:
Your target blood sugar is between 60 and 120. Please circle the values below that are in the target range (circle all that apply):
So – patients should only cirlcle 118. However, only 74% of patients answered this correclt.y So 25% of patients could not perofmr a skill that we consider fundamental to daily diabetes care- to understand their glucose meter.

30. Insulin Correction Scale (I)
You are told to follow the sliding scale shown here. The sliding scale indicates the amount of insulin you take based upon your blood sugar levels:
How you frame something to a patient can make a big difference. So for example, if you show patients a table and ask them to calculate how much insuliun to take for a certain BG – most patients can do this just fine,
Percent Correct: 85%

31. Insulin Correction Scale (II)
After seeing the Doctor, you are given the following
instruction to lower a high blood sugar level before a
meal:
“ Starting with a blood sugar of 120, take 1 unit of Humalog insulin for each 50 points of blood sugar.”
How much insulin should you take for a blood sugar of 375?
43. ANSWER _________ units
Percent Correct: 37% (accept 5-6units)
If on the other hand, you were to give people instructions- such as these:
Starting with a blood sugar of 120, take 1 unit of Humalog insulin for each 50 points of blood sugar.”
This is a much more challenging thing for a patient to do – and patients really struggled with this.
But these instructions were actually being used in some of our clinics before we did this study.

32. DNT and other measures
Higher DNT scores are sig. correlated with higher:
education (r=0.51)
literacy (r=0.50)
math skills (r=0.64)
diabetes knowledge (r=0.78)
Frequency of glucose monitoring (r=0.21)
and lower:
A1C (r= -0.08, p =0.11)
In multivariate analysis, each 10 point increase in DNT score was correlated with a 0.1 point decrease in A1C (p<0.05).

33. Conclusions Performance on DNT was fair/poor
Disconnect between what is taught and what patients can do.
Performance on DNT was correlated with literacy and math skills.
Performance on DNT was also correlated with A1C, when adjusted for other covariates.

34. Communicating: What can you do?
Use low literacy and picture based materials
Individualize education
Teach concepts in a simplified manner
Use teach back technique
Address cultural issues
Shared goal setting

35. Sample Low Literacy Materials

36. Teaching Concepts
Limit advice to key concepts. Focus on behaviors and actions
Focus on one concept at a time; partition information
Use concrete terms and examples
Make info culturally relevant and personal
Avoid Jargon!
Practice patient centered communication and shared goal setting

37. Teachback technique
Clinician Explains New Concept
Patient Recalls and Comprehends
Clinician Clarifies and Tailors Explanation
Clinician Reassesses Patient Recall and Comprehension
Clinician Assesses Patient recall and Comprehension
New Concept: Health Information, Advice, or Change in Management
Adherence
Schillinger, Arch Int Med, 2003

38. Cultural Challenges Language Family Structure Health Beliefs
Use Language Appropriate Handouts
Use a translator!
Family Structure
Multiple caregivers
Health Beliefs
Dissonance from the “biomedical model”
Campinha-Bacote, 2003 38

39. Shared Goal Setting Let patient or family initiate
Practice “reflective” listening”
Provide affirmation of positive behaviors
Show empathy for challenges
Choose goal that is realistic and attainable
Can offer a few choices and settle on goals together
Roll with resistance (don’t challenge patients who resist change; instead ask them to come up with solutions)
Assess their confidence in achieving the goal
Be concrete
Set a time for accomplishing goal
Let them know it is up to them to make change!
Promote a “you can do it” approach!

40. Literacy Interventions
Our group has also been on the forefront of performing randomized trials to evaluate the role of addressing literacy and health communication to improve patient outcomes.

41. Initial Diabetes Intervention
6 Month
Follow-Up
1 Year Follow-Up
Baseline
105
Control 99
Control 95
Control
217
Patients
with T2DM
Initial
Pharmacist
Session R
112
Interv.
105
Interv. 98
Interv.
THE RESULTS…
From February 2001 to April 2002, 217 patients were randomized. Of these 105 patients were controls and 112 patients received the intensive intervention. At 6 months, we have complete f/u data for almost 95% of eligible patients, and at 12 months we have complete follow up for close to 90%

42. Intervention Diabetes Education Evidence-based medication algorithms
Database to track and manage patient outcomes
Diabetes Care Coordinator
Addressed literacy by using:
Individualized verbal education
Low literacy material
Teaching concepts in a simplified manner
“Teach back” techniques to confirm learning
In the intervention group, Clinical pharmacists, who were also certified diabetes educators, provided diabetes education, applied Evidence based medication Algorithms and used a Data base to track and manage patient outcomes. In addition, the pharmacists addressed literacy by using: individualized verbal education, using low literacy materials, teaching concepts in a simplified manner, and having patients “teach back” information to confirm learning.

43. Significant Clinical Improvements at 12 months
Variable
Control
(n=95)
Intervention
(n=98)
Difference
A1C (%)
-1.2%
-2.1%
0.9% (0.8,1.0)
SBP (mmHg)
+2.3
-6.9
9.2 (2.3,16.1)
DBP (mmHg)
+1.2
-3.6
4.8 (1.1,8.6)
ASA (mmHg)
+6%
+47%
41% (25-55)
T. Chol. (mg/dL)
-12
-27
15 (-4, 35)
At 12 months follow up we saw significant clinical improvements between the Control and Intervention Groups.
As seen in this table,
We saw close to a 1% improvement in A1C, over 9 points improvement in SBP,almost 5 points in DBP, and over 40% points increase in aspirin use.
We saw a modest reduction in cholesterol, and this did not reach statistical significance.
{delete control and intervention columns?}
Rothman AM J Med, 2005

44. Literacy was an Important Factor
We were the first to demonstrate the importance of addressing literacy in a randomized Trial. In this study we examined the role of literacy as part of a comprehenive intervention for patients with type 2 diabetes. For the study we randomized patients to get usual care, or to get a comprehensive intervention that included addressing the problem of low literacy by proviidng low literacy oriented education materials, indiviudalized educaiton, and using communication skills that are helpful for patients with poor litearcy skills.
we found that patients who received our comprehensive intervention (shown in red) had signficant improvement in their blood sugar compared to the control patients. However, when we stratified by patient literacy status, we found that patients with higher literacy only did slightly better, but patient with low literacy actually did a lot better. So this study suggested that addressing literacy could really improve care for patients with lower literacy. However, because this was a very comprehensive intervention – where we were doing many different things to the patients we were unable to ascertain how much of the improvement was specifically related to our literacy oriented interventions. So, after this study we embarked on several additional studies to better examine the role of literacy, and particularly numeracy in our patients ability to care for their diabetes….
High Literacy Patients
Low Literacy Patients

45. Diabetes and Numeracy RCT
We developed a new educational toolkit that addressed literacy and numeracy issues.

46. DLNET Toolkit Simplified medication instructions
Text at 5th grade reading level
Color coding
Pictures for key concepts
Step-by-step instructions
Simplified medication instructions
Practice skills worksheets
The toolkit included many approaches known to improve patient understanding for both patients with normal and low literacy or numeracy skills. We then perform performed 2 randomized trials where we trained health care providers in improved health communication skills and gave them our toolkit to help manage patients with diabetes. 46
Wolff K et al. The Diab Educ 2009 46

47. Study Demonstrates Value of Addressing Health Literacy
*P = 0.03
This study, pubished in Diabetes Care, showed that while the study was active in the first 3 months we were able to significantly improve glycemic control at the 2 intervention groups compared to control groups that recevied comprehensive diabetes disease management.
We have since shared our Toolkit with providers all over the country and even the world.
*Adjusting for age, gender, race, type of diabetes, income level, site of intervention and baseline DNT score and Hba1c levels 47
Cavanaugh KL et al. Diabetes Care 2009 47

48. Diabetes Nutrition Education Study (DINES)
We followed this up with another study where we specifically examined the role of Certified Diabetes Education, and of different approaches to Nutrition Education. Patients were randomized to a control group receiving standard education vs a group that received CDE with a focus on a simplified plate method for nutrition education, or a group that received CDE with a focus on the more numeracy intensive carb counting approach to nutrition.

49. Carb Counting vs Plate Method49

50. Results Demonstrate Value of Simpler Diabetes Education
At the end of the study, we demonstrated that patients with both low and high numeracy skills who got CDE had more improvement in A1C than those in the Control Condition. And among those in the plate method group, both low and high numeracy patients did better. But in the Carb counting group only the high numeracy patients did significantly better. So this study demonstrated that it might be beneficial to provide a simpler approach to most patients, or at least to avoid carb counting with those who have lower numeracy skills.

51. New Standards for Diabetes Education
Diabetes Care, 2012, in press

52. PRIDE Study PaRtnering to Improve Diabetes Education
Goal to address health communication issues to improve diabetes care in middle TN
Collaboration between TN Dept. of Health, Vanderbilt, and Meharry
5 year NIDDK R18 study
Cluster RCT with 10 Clinics and
400 diabetes patients
Develop a sustainable model
for improved diabetes care
Currently we are further studying the role of addressing literacy and numeracy and other health communication issues in a 5 year cluster randomized trial here in middle TN. This study is a partnership with the TN Dept of Health and we are working in 10 State health department clinics in Middle TN. We have trained over 150 health care providers including MD, NP, RN, RD as part of this study…

53. Pride Materials
And we have developed a robust array of toolkit materials in English and Spanish for providers to use with their diabetes patients to help manage diabetes and set realistic goals.

54. HIT approaches for Diabetes
Web-based and mobile phone intervention to promote problem solving skills and self-care in adolescents with diabetes
Use of electronic patient portal to address medication adherence
Our group has also been engaged with several informatics based interventions – particularly with the use of web-based, mobile-based, and text messaging intervetntions for our adolescents with diabetes, and the use of our electronic patient portal.

55. Childhood Obesity 1 in 4 preschoolers in the US are overweight/obese
Overweight in infancy associated with increased risk for overweight in adulthood
Weight gain in first few months of life associated with increased CV risks in adulthood
“Obesogenic” behaviors start early in infancy and are very common!

56. Pediatric Obesity Prevention
Over 26% of all preschoolers are overweight or obese
Study involves Vanderbilt, UNC, NYU, UMiami and 865 English and Spanish speaking families addressing health literacy and numeracy to prevent early childhood obesity
Trained pediatric residents in health communication skills
Provide toolkit of materials to use with families (Greenlight)
We are also leading a national study that is addressing literacy and health communication in early childhood obesity prevention. We have enrolled 870 English and Spanish speaking families starting at 2 months of age, and are trying to prevent Obesity Devlopment by age 2, because nationaly over 20% of pre-schoolers are overweight, and in our pediatric resident clinics about 50% of our 2 year olds are overweight. For this study we have trained over 200 pediatric residents in improved communication skills.

57. Greenlight Toolkit Materials
1-2 Booklets per Well Child Visit
1 CORE booklet focused on key behaviors
1-3 SUPPLEMENTAL booklets (Provider Chooses)
Booklets are 2-6 pages and end with goal setting
Designed to be used interactively during the visit
Available in English and Spanish

59. Baseline Demographics
Child Characteristics
Mean (SD) or n (%)
Child Age, weeks
9.3 (1.8)
Child Gender, Male
429 (49)
Child weight at 2 months (kg)
5.36 (0.78)
Parent Characteristics
Parent Age, years
27.7 (6.1)
Relationship to Child, Mother
 839 (95. 6)
Parent Non-US Born
428 (49.0)
Parent Race/Ethnicity
Hispanic
White, non-Hispanic
Black, non-Hispanic
Other, non-Hispanic
436 (50) 
154 (18.0)
239 (27.0)
46 (5.0)
Parent Language, Spanish
303 (35.0)
Parent Education, Less than HS Graduate
227 (26.1)
Income (annual)
<$10,000
$10,000-$19,999
$20,000-$39,999
>$40,000
268 (31)
229 (27.0)
204 (24.0)
137 (15.9)
WIC
729 (85%)
Medicaid
740 (85%)
# of Adults in home, >1
782 (90.0)
# of Children in home, >1
524 (60.2)

60. Obesogenic Behaviors are Common
 Behaviors at 2 month visit
Total (n=863)
Type of Feeding
Formula only
Mostly formula, and some breast milk
Equal formula and breastmilk
Mostly breast milk, and some formula
Breast milk only
385 (44.6)
127 (14.7)
 11 (1.3)
 175 (20.3)
 165 (19.1)
Sweet drinks
 26 (3.0)
Early introduction of solids
98 (11.6)

61. Behaviors at 2 months Infant feeding style and practices
In last 2 weeks, how often put to sleep while drinking a bottle
At most sleep times
Sometimes, at least once a day
Sometimes, but not every day
Never
 108 (12.5)
119 (13.8)
143 (16.6)
491 (57.0)
I try to get my child to finish her breast milk or formula
Always
Most of the time
Half of the time
Seldom or infrequently
 324 (37.6)
149 (17.3)
75 (8.7)
103 (11.9)
211 (24.5)
When my baby cries, I immediately feed him/her
 175 (20.3)
184 (21.4)
176 (20.4)
207 (24.0)
When my child has a bottle, I prop it up
 31 (3.7)
24 (2.9)
37 (4.4)
102 (12.2)
643 (76.8)

62. Behaviors at 2 months Physical Activity-related Practices
Tummy time, minutes, d (Median, Inter-quartile range)
12.5 [ ]
Tummy time
30 minutes or more
<30 minutes
288 (33.5)
571 (66.5)
Television Exposure, minutes [interquartile range]
346 [60-480]
Television watching, minutes [interquartile range]
25 [ ]
Television watching
Any
None
429 (49.8)
432 (50.2)
I watch TV while feeding my baby
Always
Most of the time
Half of the time
Seldom or infrequently
Never
 72 (8.4)
101 (11.7)
223 (25.9)
252 (29.2)
214 (24.8)

63. Racial/Ethnic Differences
Hispanic
Black, non-Hispanic
Other, non-Hispanic
Outcome, N
Overall p-value for Race/Ethnicity
AOR, [95% CI]
p-value
More formula than BM, 820
0.029
0.70 [0.43, 1.17]
0.174
1.31 [0.82, 2.10]
0.261
0.65 [0.33, 1.26]
0.199
Bottle to bed, 819
0.003
1.05 [0.61, 1.78]
0.867
1.97 [1.25, 3.12]
0.004
2.26 [1.12, 4.57]
0.023
Finish BM/formula, 820
0.012
1.93 [1.20, 3.11]
0.007
1.62 [1.09, 2.41]
0.018
0.88 [0.46, 1.68]
0.698
Immediately feed, 819
1.24 [0.78, 1.96]
0.362
1.05 [0.70, 1.57]
0.821
3.08 [1.65, 5.74]
<0.001
Bottle propping, 797
0.002
2.47 [1.25, 4.88]
0.009
3.05 [1.71, 5.43]
2.26 [0.92, 5.58]
0.076
TV while feeding, 820
0.014
1.04 [0.66, 1.63]
0.872
1.29 [0.87, 1.92]
0.213
0.46 [0.24, 0.86]
0.015
Active TV Watching, 819
0.006
0.88 [ ]
0.595
1.58 [ ]
0.034
0.57 [0.28, 1.19]
0.133
Tummy Time, 817
0.083
0.62 [0.40, 0.97]
0.037
0.86 [0.58, 1.28]
0.447
0.53 [0.28, 1.003]
0.051
Perrin et al, Pediatrics, 2014

64. Literacy and Behaviors
AOR* (Low Lit vs Adeq. Literacy)
95% CI
p-value
Feeding Practices: Diet content-related
Type of feeding: More formula than BM
805
2.0
0.01
Feeding Practices: Feeding style-related
Gets child to finish BM or formula
1.3
0.3
Immediately feeds when baby cries
804
1.8
Props the bottle
782
0.049
Watches TV while feeding baby
0.8
0.5
Does not let child decide how much to eat
1.1
Physical activity-related behaviors
Television watching
Television watching: Any
0.03
Tummy time: None
802
2.2
0.008
*Controlling for child gender, child out of home care, WIC status; parent age, race/ethnicity, language; number of adults in the home, number of children in the home, income; recruitment site
Yin et al, J Pediatrics, 2014

65. Conclusions Low literacy and numeracy common
Even patients with good literacy and numeracy can struggle to navigate our complex system and perform self-care!
Patients with lower literacy/numeracy have worse knowledge, behavior, and outcomes
Interventions that use low literacy materials and improved communication skills can improve outcomes!

66. Acknowledgements UNC Vanderbilt/ Meharry Eliana Perrin MD MPH
Joanne Propst-Finkle JD
Alice Ammerman PhD RD
Michael Pignone MD MPH
Darren DeWalt MD MPH
Morris Weinberger PhD
John Buse MD PhD CDE
Robb Malone PharmD CDE
Betsy Bryant PharmD CDE
Victoria Hawke RD
Britton Crigler BS, James Joyner BA
Miami/Stanford
Lee Sanders MD MPH
Vivian Franco MPH
Lee Sanders, MD, MPH
Anna Maria Patino Fernandez, PhD
Daniela Quesada, MPH
Sheah Rarback, RD
Sarah Messiah, PhD
Lourdes Forster, MD
Vanderbilt/ Meharry
Tom Elasy MD MPH, Robert Dittus MD MPH
Kerri Cavanaugh MD MPH, Mimi Huizinga MD MPH
Dianne Davis RD CDE, Becky Gregory RD CDE
Ken Wallston PhD. Phil Ciampa MD
Ayumi Shintani PhD, Tebeb Gebretsadik MPH
Disha Kumar BS, Jessica Sparks BA, Ryan Housam BA, Hilary Weiss BS, Kirbee Bearden
Shari Barkin MD MHs
Kathleen Wolf MSN, FNP-BC, ADM-BC
Sunil Kripalani MD
Heidi Silver RD PhD
Richard White MD (Meharry)
NYU
Shonna Yin MD MSc
Linda van Schaick PhD
MaryJo Messito MD
Elaine Galland RD
Benard Dreyer, MD
Alan Mendelsohn, MD
Previous Funding Support: RWJ Clinic Scholars Program, UNC Department of Medicine, Vanderbilt Diabetes Center, Vanderbilt DRTC, Vanderbilt Center for Health Services Research, Pfizer Clear Health Communication Initiative, ADA (Novo Nordisk), K23/R03, AADE
Current Funding Support: NIDDK (R18), NICHD (R01), NCATS (VICTR), NIDDK (P30), PCORI

67. Questions