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INTRODUCTION OBJECTIVES DATA & METHODS RESULTS CONCLUSIONS Examining Health Literacy Disparities in the United States: A Third Look at the National Assessment of Adult Literacy (NAAL) Our research is a third look at the health literacy of American adults. In a series of reports from the 2003 National Assessment of Adult Literacy (NAAL), Kutner and colleagues (2006; 2006) provide a first look at literacy and health literacy of America’s adult population. In brief, the results implicitly point to the differential relationship between socioeconomic status (SES) and health literacy level. However, Kutner and colleagues (2006; 2006) explicitly caution that the results do not capture complex associations or interactions. R.V. Rikard Maxine S. Thompson Andrew Pleasant Julie McKinney Department of Sociology & Anthropology North Carolina State University Raleigh, North Carolina Canyon Ranch Institute Tucson, Arizona McKinney & Associates Health Literacy Consulting Cambridge, Massachusetts On your mobile device? Scan the code to download and read our research. The data come from the 2003 National Assessment of Adult Literacy (NAAL) managed by the National Center for Education Statistics (NCES) under restricted access. The NAAL is the only nationally representative data set that contains a latent measure of health literacy (Baldi et al., 2009; Jin, Greenberg, & Baer, 2007). In our analyses, the complete household sample is limited to an analytical sample of adults 18 years of age or older and individuals with complete data on the independent variables. Thus, the sample is reduced to 15,309 respondents. Given the multi-stratified cluster sampling design, all analyses are conducted in STATA 12 to include sample weights. NAAL ANALYTIC SAMPLE 1. Examine social differences in health literacy to understand disparities in health outcomes. 2. Move beyond descriptive analyses and employ data from the general population to examine health literacy disparities. 3. Expand measures of SES to include measures of relational social class and social resources to provide more insight about the importance of SES resources than income, educational attainment, and/ or occupational status (Muntaner et al., 2010). A series of weighted Ordinary Least Squares (OLS) regression models predicting health literacy level reveal: As an individual’s occupational prestige increases there is approximately half a point increase in health literacy scores; Health literacy levels among women are higher compared to men; • Health literacy levels are significantly lower for respondents who never marry compared to married respondents or those living as married; Compared to English-speaking respondents, health literacy scores are significantly lower for those who grew up speaking another language; Compared to respondents who voted in the 2000 election, lower health literacy scores are observed for individuals who are either non-citizens or non-voters; Health literacy scores increase as time spent volunteering increases. 1. The findings in the present research are generalizable to the adult population in the United States. 2. The analyses call attention to the limitations of the current definition of health literacy. 3. Relational social class and social resources shape disparities in health literacy. Pleasant’s (2008) second look clarifies the presentation of NAAL results by emphasizing the context of findings from the initial NAAL report. HEALTH LITERACY AS A LATENT TRAIT? Item Response Theory (IRT) focuses on the level of difficulty for a given question or item and an individual’s performance (i.e., answering the question correctly) in relation to the item. The Graded Response Model (GRM) is considered a more general IRT model for dichotomous response options. The NCES provides the a or discrimination parameter and b or difficulty parameters for all items in the NAAL. The a parameters, b parameters, and recoded item responses are entered into Meade’s (2010) VisualDF program to compute theta values for the 28 items.

2013 Health Literacy Annual Research Conference Poster Presentation

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Page 1: 2013 Health Literacy Annual Research Conference Poster Presentation

IntroductIon

objectIves

data & Methods results

conclusIons

Examining Health Literacy Disparities in the United States: A Third Look at the National Assessment of Adult Literacy (NAAL)

Our research is a third look at the health literacy of American adults.

In a series of reports from the 2003 National Assessment of Adult Literacy (NAAL), Kutner and colleagues (2006; 2006) provide a first look at literacy and health literacy of America’s adult population.

In brief, the results implicitly point to the differential relationship between socioeconomic status (SES) and health literacy level.

However, Kutner and colleagues (2006; 2006) explicitly caution that the results do not capture complex associations or interactions.

R.V. Rikard Maxine S. Thompson Andrew Pleasant Julie McKinneyDepartment of Sociology & Anthropology

North Carolina State UniversityRaleigh, North Carolina

Canyon Ranch InstituteTucson, Arizona

McKinney & Associates Health Literacy ConsultingCambridge, Massachusetts

On your mobile device? Scan the code to download and read our research.

The data come from the 2003 National Assessment of Adult Literacy (NAAL) managed by the National Center for Education Statistics (NCES) under restricted access.

The NAAL is the only nationally representative data set that contains a latent measure of health literacy (Baldi et al., 2009; Jin, Greenberg, & Baer, 2007).

In our analyses, the complete household sample is limited to an analytical sample of adults 18 years of age or older and individuals with complete data on the independent variables. Thus, the sample is reduced to 15,309 respondents.

Given the multi-stratified cluster sampling design, all

analyses are conducted in STATA 12 to include sample weights.

NAAL ANALytic SAmpLe

1. Examine social differences in health literacy to understand disparities in health outcomes.

2. Move beyond descriptive analyses and employ data from the general population to examine health literacy disparities.

3. Expand measures of SES to include measures of relational social class and social resources to provide more insight about the importance of SES resources than income, educational attainment, and/or occupational status (Muntaner et al., 2010).

A series of weighted Ordinary Least Squares (OLS) regression models predicting health literacy level reveal:

• As an individual’s occupational prestige increases there is approximately half a point increase in health literacy scores;

• Health literacy levels among women are higher compared to men;

• Health literacy levels are significantly lower for respondents who never marry compared to married respondents or those living as married;

• Compared to English-speaking respondents, health literacy scores are significantly lower for those who grew up speaking another language;

• Compared to respondents who voted in the 2000 election, lower health literacy scores are observed for individuals who are either non-citizens or non-voters;

• Health literacy scores increase as time spent volunteering increases.

1. The findings in the present research are generalizable to the adult population in the United States.

2. The analyses call attention to the limitations of the current definition of health literacy.

3. Relational social class and social resources shape disparities in health literacy.

Pleasant’s (2008) second look clarifies the presentation of NAAL results by emphasizing the context of findings from the initial NAAL report.

HeALtH LiterAcy AS A LAteNt trAit?Item Response Theory (IRT) focuses on the level of difficulty for a given question or item and an individual’s performance (i.e., answering the question correctly) in relation to the item.

The Graded Response Model (GRM) is considered a more general IRT model for dichotomous response options. The NCES provides the a or discrimination parameter and b or difficulty parameters for all items in the NAAL. The a parameters, b parameters, and recoded item responses are entered into Meade’s (2010) VisualDF program to compute theta values for the 28 items.