# Presentation: 393762

## 5 A Day Behavior and Knowledge of Recommendations in Relation to Health Communication in the Health Information National Trends Survey (HINTS)

**Jennifer M. Petrelli, M.P.H.**         ** CRTA Fellow, NCI (Doctoral Student HSPH)**
**Amy L. Yaroch, Ph.D                                             NCI**
**Audie A. Atienza, Ph.D.****	****                                NCI**
**Richard Moser, Ph.D.                                            NCI**
**Louise C. M****âsse, Ph.D.                                         NCI**
**Stephanie A. Smith-Warner, Ph.D.                       HSPH**
**Linda Nebeling, Ph.D., M.P.H., R.D., F.A.D.A.      NCI**
- HINTS Data Users Conference
- January 20-21, 2005
- St. Pete Beach, FL

**Notes:**
This afternoon I will be discussing an analysis of the HINTS looking at 5 A Day Behavior and Knowledge of recommendations in relation to demographic information and health communication.

I am fortunate to have been able to collaborate with a wonderful group from NCI and my research advisor at Harvard, SSW.
They have been extremely supportive and I have truly learned a great deal from these experts!

## National 5 A Day for Better Health Program Recommendations

- The goal of the National 5 A Day for Better Health Program is to increase the consumption of fruits and vegetables in the United States to 5 to 9 servings every day.
*http://www.5aday.gov/index-about.shtml*

**Notes:**
FV related to decreased risk of chronic diseases
Current Recommendation.
The New Dietary Guidelines for Americans released last week increased recommendations to 9-13 servings/day.

 However,  FV consumption is still well below recommended levels of intake

## Fruit and Vegetable (F/V) Intake U.S.

- NHANES, 2000 (Thompson personal communication)
- Median as measured by multiple 24 hour recalls=4.38 servings/day
- BRFSS, 2000 (Serdula et al.2004)
- Mean = 3.37 servings/day

**Notes:**

I am highlighting results from Major National Surveys
NHANES uses multiple 24 hour recalls- a detailed comprehensive assessment
BRFSS telephone survey uses a screener very similar to the one used in HINTS
It uses a F/V screener which is more of an estimate

WE FOUND 3.08 Serving/day s in this analysis

## Study Objectives

- Evaluate knowledge of the F/V recommendation and F/V consumption
- Characterize 4 population subgroups based on demographic and communication factors

**Notes:**
We sought to identify demographic and communications correlates of  F/V intake
We would not expect a precise estimate of F/V intake given the survey questions

## Assessment of F/V Message Awareness and Consumption

- _Knowledge of recommendation_
- How many servings of fruits and vegetables do you think a person should eat each day for good health?
- Dichotomous variable:
**Informed     **=Know recommendation is 5+ servings F/V per day
**Uninformed**=Don’t know recommendation (<5 servings F/V per day)
- _F/V Consumption_
- Derived F/V variable = sum of servings per day of vegetables, potatoes (non-fried), fruit, and fruit juice
- 	Dichotomous variable:
**Complier        **=Ate  5+ servings of F/V per day
**Non-Complier**=Ate < 5+ servings of F/V per day

**Notes:**
There is a  5 item F/V screener questions on the HINTS Survey.

Audie created code that combined the fruit and vegetable questions from the survey into a combined fruit and vegetable servings per day.

We decided to go with the most liberal definition of F/V intake because the intakes are so low in this population. So that means that someone could eat 5 servings of fruits only and they would count as someone who ate the recommended amount.

## Analysis

- SUDAAN
- HINTS statistical weights
- Bivariate Analyses (N = 6369)
- Cross-tabulations
- Multivariate Analyses (N = 5673)
- Multilogistic Regression

**Notes:**
You are all familiar ...
Sudaan allows for analysis of complex survey design
Analyzed all data using HINTS replicate weights and Jacknife variance estimation
Multilog generalizes the modeling capabilities of Logistic to include categorical outcomes with two or more categories. By comparison, logistic provides modeling capabilities for dichotomous outcome variables

11% MISSING in Multivariate

## Outcome & Subgroup Definitions

|  | Ate 5+ F/V a day
 | Ate <5 F/V a day |
| --- | --- | --- |
| Know Recommendation
(5+ servings/day) | Informed Complier
6.8% | Informed 
Non-Complier
17.2 |
| 
Do not know Recommendation
(< 5 servings/day)
 | 
Uninformed Complier
8.3% | 
Uninformed 
Non-Complier
67.7% |

## Descriptive Statistics 

- Informed = 23.7%
- Compliant =15.2%
- Total servings consumed per day
- Mean (SD) =3.08 (1.93)
- Median = 2.66
- Total servings consumed per day
- Among informed:     Mean (SD) =3.87 (2.09)
-                                     Median = 3.42
- Among uninformed: Mean (SD) =2.83 (1.79)
-                                     Median = 2.46

**Notes:**
Our findings are more in-line with the findings of BRFSS (earlier slide)  which is a short F/V screener.
Gloria Stables- Model adjusted mean intake for those aware of the message 5.2 daily servings in 1997
		   “                                            “      not aware of the message 3.6 daily servings
HINTS –Not model adjusted intake Mean =3.08 median 2.66
                                intake among those who know = 3.87 (2.09) median 3.42
                                                             don’t know =2.83 (1.79) median 2.46

HINTS  23.4 % know the recommendation
Gloria 19.2 % know the recommendation 1997
HINTS 15.2% Ate %+ a day    COMPARE TO 24.57 in BRFSS in 2000

## Percent Informed and Compliant by Select Sociodemographic Characteristics

**Notes:**
First we looked at knowledge and intake separately.

HINTS TOTAL POPULATION NOT OUR ANALYTIC POPULATION

Within each education category the % informed increases with increasing education attainment 
The percent compliant also increases with increasing education level

People who never smoked...

## Percent Informed and Compliant by Select Communication Variables

**Notes:**
Magazine reading...with increasing # of magazines read ...more informed, but a decrease in compliance

Derived variable about attention to health information from TV, Radio, Newspaper, Internet. Created by Lila Finney

## Multilogistic Model

- _Predictors_
- Gender
- BMI
- Education
- Race/Ethnicity
- Smoking
- Exercise
- Age
- TV hours/ weekday
- Radio hours/weekday
- Newspaper/week
- Magazines/week
- Information Attention/Seeking (Finney-Rutten)

- _Outcomes_
- Informed Compliers
- Informed Non-Compliers
- Uninformed Compliers
- Uninformed Non-Compliers *
*	**	**	***reference group*

**Notes:**

Multilog generalizes the modeling capabilities of Logistic to include categorical outcomes with two or more categories. By comparison, logistic provides modeling capabilities for dichotomous outcome variables
Created our outcome based on the intersection of Knowledge and intake of fruit and vegetables:
Composite variable with 4 categories

## Key Multilogistic Regression ResultsSociodemographic CharacteristicsInformed Complier vs. Uninformed Non-Compliers

|  | OR |  95% CI |
| --- | --- | --- |
| Female | 1.00 |  |
| Male | 0.20 | 0.15-0.28 |
|  |  |  |
| <= High School | 1.00 |  |
| Some College | 1.68 | 1.23-2.28 |
| College Grad | 2.57 | 1.91-3.47 |
|  |  |  |
| Never Smoker | 1.00 |  |
| Past Smoker | 1.06 | 0.78-1.45 |
| Current Smoker | 0.38 | 0.24-0.59 |
|  |  |  |

**Notes:**
In the interest of time I will present only some key significant or interesting results from our multilogistic regression.
Increase in the odds of being an informed complier controlling for the effects of other variables...remains significant
There are some interesting results for the Informed Non compliers and Uninformed Compliers.
I have also distributed the full tables of our results if you would like to examine them further and I welcome any comments you may have.
Results are very similar to the graphs I showed...
Independent of the effects of the other variables in the model...

## Key Multilogistic Regression Results Communications/Information Seeking Variables Informed Complier vs. Uninformed Non-Compliers

|  | OR |  95% CI |
| --- | --- | --- |
| Television hours/weekday† | 0.92 | 0.84-1.00 |
| Magazines/week†
 | 1.08 | 1.01-1.16 |
| Information Attention/Seeking Score^ | 1.14 | 1.05-1.25 |
| 

†truncated at 16 hours
^range 5-10 |  |  |

**Notes:**
We ran these as continuous variables in the model because we were running into problems with too parameters in our model.

Hours of Television per weekday
Number of Days a magazine was read in the last week
Information Attention/Seeking- our health seeking composite measure

With increase in information attention seeking sore we see an increase in odds that a person is an informed complier

## Conclusions

- Majority of the population
- do not know national F/V consumption recommendations
- do not consume recommended amounts
- Being informed does not necessarily translate to changes in F/V intake
- Differences in key subgroups along demographic and communication lines
- These findings may prove useful in developing programs and/or interventions to increase F/V consumption among specific groups (e.g., men, smokers, less educated)

**Notes:**
Target those who don’t know/don’t eat
Men
Smokers
Those who have <= High school education

## EXTRA SLIDES

## Limitations
Cross-sectional Data 
Short F/V screener
Broad assessment of communications variables
Strengths
Nationally representative survey
Can examine factors that impact both knowledge and consumption
Examine the intersection of knowledge/behavior as related to demographic and communications variables

- Cross-sectional Data
- Short F/V screener
- Broad assessment of communications variables
**Strengths**
- Nationally representative survey
- Can examine factors that impact both knowledge and consumption
- Examine the intersection of knowledge/behavior as related to demographic and communications variables

**Notes:**
Cross-Sectional surveys are useful in describing characteristics of the population and to formulate hypothesis, but the data cannot be used to test hypotheses.

Because of the short length of the F/V screener compared to other National Surveys the results are more of an estimate/approximation
Limited information on F/V, communications
HINTS provides population level data about health information sources and information seeking
How do information channels differ by respondent characteristics?
Can cross behavior and knowledge with communications variables
High cooperation rate in HINTS as compared to other national surveys?

60% cooperation in HINTS....40+ % response?

## Survey Content (Demographics)

- Gender
- Age
- BMI
- <25, 25-29.00, >=30.00
- Education:
- <=high school, some college, college
- Race/Ethnicity
- White, Other (black, Hispanic, Indian, Asian, Hawaiian)
- Smoking
- Never, past, current
- Any Exercise in the Past month
- Yes/No

## Survey Content (Communications)

- Hours of Television per weekday
- Hours of Radio per weekday
- Number of days a newspaper was read in the last week
- Number of days a magazine was read in the last week
- Attention to information about health/medical topics
- TV, Radio, Newspaper, Magazines, Internet
- Utilized combined variable created by Lila Finney (NCI)

## Data Source

- Baseline data collected 2002-2003
- Computer-Assisted Telephone Interview
- Random Digit Dial (RDD)
- National Probability Sample of adult Population age 18+
- Vehicle to research health communication and conduct surveillance
- -Nelson, DE et al. Journal of Health Communication, In Press 2004

## Discuss Missing Data

- HINTS Dataset = 6369 observations
- Our Analytic Dataset = 5673 observations
- Difference=696 or 11%