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. Author manuscript; available in PMC: 2017 Aug 7.
Published in final edited form as: J Health Commun. 2016;21(Suppl 1):58–68. doi: 10.1080/10810730.2016.1144661

Relationships Between Health Literacy and Genomics-Related Knowledge, Self-Efficacy, Perceived Importance, and Communication in a Medically Underserved Population

Kimberly A Kaphingst a,b, Melvin Blanchard c, Laurel Milam d, Manusheela Pokharel b, Ashley Elrick b, Melody S Goodman d
PMCID: PMC5546792  NIHMSID: NIHMS885853  PMID: 27043759

Abstract

The increasing importance of genomic information in clinical care heightens our need to examine how individuals understand, value, and communicate about this information. Based on a conceptual framework of genomics-related health literacy, we examined whether health literacy was related to knowledge, self-efficacy, and perceived importance of genetics and FHH and communication about FHH in a medically underserved population. The analytic sample was comprised of 624 patients at a primary care clinic at a large urban hospital. About half of participants (47%) had limited health literacy; 55% had no education beyond high school and 58% were Black. In multivariable models, limited health literacy was associated with lower genetic knowledge (β=−0.55; SE=0.10, p<.0001), lower awareness of FHH (OR=0.50; 95% CI=0.28,0.90, p=.020), greater perceived importance of genetic information (OR=1.95; 95% CI=1.27,3.00, p=.0022) but lower perceived importance of FHH information (OR=0.47; 95% CI=0.26,0.86, p=.013), and more frequent communication with a doctor about FHH (OR=2.02; 95% CI=1.27,3.23, p=.0032). The findings highlight the importance of considering domains of genomics-related health literacy (e.g., knowledge, oral literacy) in developing educational strategies for genomic information. Health literacy research is essential to avoid increasing disparities in information and health outcomes as genomic information reaches more patients.

Introduction

Genomic information is playing an increasingly important role in clinical care and public health initiatives. Whole genome and exome sequencing are already being used for clinical purposes (Biesecker & Green, 2014; Guttmacher, McGuire, Ponder, & Stefansson, 2010), and sequencing is likely to become more important to patient care (Pasche & Absher, 2011) as advances in technology will mean greater availability of patients’ individual genomic information (Biesecker & Green, 2014; Mardis, 2008). Genomic information in the form of family health history (FHH) is also critical to improving individuals’ health (Guttmacher, Collins, & Carmona, 2004). Family history is an important contributing risk factor for many common, chronic diseases, reflecting shared genetic, behavioral, and environmental risk (Yoon et al., 2004; Yoon, Scheuner, Jorgensen, & Khoury, 2009). Assessment of FHH has been recognized as an important tool in disease prevention efforts (Valdez, Yoon, Qureshi, Green, & Khoury, 2010). It is therefore critical to examine how individuals understand and value FHH and genetic information and communicate about FHH.

Health literacy may be an important factor affecting communication about genomic information (Hurle et al., 2013; Lea, Kaphingst, Bowen, Lipkus, & Hadley, 2011). Although different definitions of health literacy exist, the Institute of Medicine (IOM) defined health literacy as the degree to which individuals can obtain, process, and understand the basic health information and services needed to make appropriate health decisions (Nielsen-Bohlman, Panzer, Kindig, eds, 2004). The IOM operationalized health literacy as having the following components: conceptual and cultural knowledge; oral literacy (listening and speaking skills); print literacy (reading and writing skills); and numeracy (quantitative skills) (Nielsen-Bohlman et al., 2004). Prior research has shown that individuals with limited health literacy have, on average, less health-related knowledge, increased incidence of chronic disease, lower utilization of preventive health services, and poorer self-reported health (Berkman et al., 2011; Nielsen-Bohlman et al., 2004). Studies have also found that health literacy impacts provider-patient communication (Schillinger, Bindman, Wang, Stewart, & Piette, 2004; Schillinger et al., 2003; Williams, Davis, Parker, & Weiss, 2002). However, less is known about how health literacy impacts knowledge, skills, and communication in the domain of genomics.

Prior studies have found substantial gaps in genetics-related knowledge in the general public (Lea et al., 2011). Qualitative research has shown that although individuals may be familiar with genetics-related terms, they have limited understanding of the underlying concepts (Catz et al., 2005; Lanie et al., 2004; Mesters, Ausems, & De Vries, 2005). Results from larger quantitative studies support this conclusion. In a telephone survey conducted with 1009 adults, Molster, Charles, Samanek, & O’Leary (2009) found that although most respondents were aware of the connection between genes, inheritance and disease risk, significantly fewer understood the biological mechanisms underlying these relationships. Haga et al. (2013) found that 300 adults from the general public had higher knowledge about inheritance and causes of disease compared with biological knowledge about genes, chromosomes, and cells. These prior findings therefore suggest that individuals in the general public may have greater knowledge related to FHH and inheritance than knowledge about genetics concepts or genetic testing, although research conducted among medically underserved populations is still limited.

In studies examining genetic or genomic knowledge, lower educational attainment is consistently associated with lower knowledge (Carlsbeek, Morren, Bensing, & Rijken, 2007; Haga et al., 2013; Henneman, Timmermans, & van der Wal, 2004; Ishiyama et al., 2008; Jallinoja & Aro, 1999; Molster et al., 2009; Rose, Peters, Shea, & Armstrong, 2005). Older age has also been associated with lower knowledge (Ashida et al., 2011; Carlsbeek et al., 2007; Henneman et al., 2004; Ishiyama et al., 2008; Jallinoja & Aro, 1999; Molster et al., 2009; Rose et al., 2005). Because educational attainment and age are significantly associated with health literacy in most studies (Kutner, Greenberg, Jin, Paulsen, & White, 2006; Nielsen-Bohlman et al., 2004; Paasche-Orlow, Parker, Gazmararian, Nielsen-Bohlman, & Rudd, 2005), these findings suggest that health literacy may also be associated with knowledge about genetics and genomics. However, studies are needed to directly examine these associations.

Although the question of how health literacy affects communication of genetic or genomic information has received less attention than levels of genetic knowledge in the public, a few prior studies have examined this issue. In a study conducted with 163 post-treatment breast cancer patients, Lillie et al. (2007) found that after reading written information about a genomic test individuals with lower health literacy had lower recall of the information and lower preference for active participation in decision making about the test. In a subsequent study, Brewer et al. (2009) found that health literacy impacted how women interpreted visual risk information about recurrence. In their work on oral communication, Erby, Roter, Larson, & Cho (2008) developed a genetics-related word recognition measure called the Rapid Estimate of Adult Literacy in Genetics (REAL-G), based on a common, validated measure of general health literacy (Davis et al., 1993). The authors found that individuals with lower REAL-G scores had lower knowledge scores after viewing videotaped genetic counseling sessions, suggesting less learning from verbally presented genetic information (Erby et al., 2008). This team also found that more difficult oral language during a genetic counseling session was associated with less satisfaction (Roter, Erby, Larson, & Ellington, 2007). These prior studies have therefore indicated that individuals with limited health literacy may understand less from written and oral communication about genomic information and may engage less in discussions with health care providers about the information. However, more research is needed to better understand how health literacy impacts communication about FHH, as well as individuals’ confidence in their ability to communicate about genomics topics (i.e., their self-efficacy). Health literacy has been shown to affect self-efficacy (Bandura, 1986) in other domains of behavior (Osborn, Cavanaugh, Wallston, & Rothman, 2010; von Wagner, Semmler, Good, & Wardle, 2009; Wolf et al., 2007), but the effect of health literacy on communication self-efficacy needs further study. In addition, the existing research is limited because many of the studies in this area have included highly educated or predominantly white populations.

We therefore conducted a study in a medically underserved population to examine the association between health literacy and individuals’ knowledge about genetics and FHH, perceived importance of genetics and FHH, self-efficacy to engage in communication about genetics and FHH, and communication about FHH. We examined perceived importance since this might encourage individuals to elaborate on a topic and communicate about it (Petty, Barden, & Wheeler, 2002). Based on the prior literature and our conceptualization of genomics-related health literacy (Hurle et al., 2013; Lea et al., 2011), we hypothesized that: (1) individuals with limited health literacy would have lower knowledge about genetics and FHH than those with adequate health literacy; (2) individuals with limited health literacy would have lower self-efficacy related to genetics and FHH than those with adequate health literacy; (3) individuals with limited health literacy would have less communication about health and FHH than those with adequate health literacy; and (4) the association between health literacy and communication about FHH would be mediated by knowledge, self-efficacy, and perceived importance.

Methods

Setting

We conducted this study in the primary care clinic of a large urban hospital, the Center for Outpatient Health (COH) at Barnes-Jewish Hospital in St. Louis, MO, which serves as the site for ambulatory care training for a large internal medicine residency with about 150 residents. Resident trainees provide primary care to patients and have a continuous relationship with them over their three years of training. The COH serves a large and diverse patient population. In one year the clinic saw 16,907 unique patients, 64% of whom were Black and 30% were White. The majority of patients seen are female (67%), between 35–64 years of age (59%) and live in St. Louis City (46%) or the surrounding county (31%).

Participants

Participants were recruited between July 2013 and April 2014. Inclusion criteria were that participants be at least 18 years of age, a patient at the COH, and speak English. Visitors in the waiting rooms were approached by trained data collectors and asked to complete a survey in English. Surveys were administered on different days of the week and at different times of day throughout the recruitment period; data collectors approached all visitors in the waiting room during their shift. Participants were asked to complete a self-administered written questionnaire followed by a set of verbally administered measures. The latter component included the assessment of health literacy, as described below in the Measures section. Any participant could request that the written questionnaire was verbally administered. All participants completed a verbal consent process and then signed a written consent form before completing the survey. This study was approved by the Human Research Protection Office at the Washington University School of Medicine.

Approximately 26% (n=1,111) of those approached were ineligible to participate in the study because they were not patients, did not speak English, or had previously taken the survey. Among eligible participants, 44% (n=1380) agreed to participate and completed the consent process. Of these 1380 patients, 975 (71%) completed the written questionnaire without substantial missing data (i.e., completed at least 75% of items). Although 602 completed all verbally administered measures, 624 completed the health literacy measure and were included in the analytic sample (see Figure 1). Participants completed the questionnaires and verbally-administered measures while waiting for their appointment. The primary reason for incomplete surveys was inadequate time before the clinic was ready to begin the patient evaluation. There were no significant differences in gender between individuals with complete surveys and those with incomplete surveys; a higher proportion of those not completing the survey were African Americans (75%) compared with those who completed the survey (63%; p=0.003). Survey respondents were similar to the underlying COH patient population with respect to gender, age, race, and location of residence.

Figure 1.

Figure 1

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Recruitment of study participants.

Measures

Health literacy

The primary predictor, health literacy, was assessed using the Rapid Estimate of Adult Literacy in Medicine – Revised (REALM-R), a validated word recognition measure in which the participant is asked to pronounce eight health-related words (Bass, Wilson, & Griffith, 2003; Davis et al., 1993). The REALM-R was verbally administered following standard procedures. We summed the number of words pronounced correctly. For analysis, patients who pronounced 7–8 words correctly were scored as having adequate health literacy and patients who pronounced 0–6 words correctly were scored as having limited health literacy (Agency for Healthcare Research and Quality, 2013).

Outcome measures

The outcome measures were assessed on the written questionnaire. We assessed genetic knowledge with an adapted version of the Genetic Knowledge Index (Furr & Kelly, 1999), which we have used in prior studies (McBride et al., 2009; McBride et al., 2008). Participants are asked five true/false questions and the number answered correctly is summed. We modeled genetic knowledge as a continuous score in analysis. We assessed knowledge of FHH as participants’ prior awareness of FHH: “Before today, had you ever heard of a family health history?” (Kaphingst, Lachance, Gepp, D’Anna, & Rios-Ellis, 2011). We categorized responses as “yes” vs. “no/don’t know” for analysis.

We assessed genetic self-efficacy (i.e., individuals’ confidence in their ability to use genetic information) using a measure developed by Parrott, Silk, Krieger, Harris, & Condit (2004). Participants indicated the extent to which they agreed with each of the following statements on a five-point Likert-type scale from strongly disagree to strongly agree (i.e., “I can explain genetic issues to people”). Scores on these items were averaged and modeled as a continuous variable in analysis (Cronbach’s alpha = 0.86). FHH self efficacy (i.e., participants’ confidence in their ability to communicate about FHH with their family) was assessed using one item: “How sure are you that you could discuss family health history with members of your family?” (Kaphingst et al., 2011). We compared those who answered “very sure” to those who answered “somewhat” or “not at all sure” in analysis.

We used one item to assess the perceived importance of genetic information: “How important is it to you to learn more about how your genes, that is the characteristics that are passed from one generation to the next, affect your chance of getting certain health conditions?” Participants responded to this item on a five-point scale from “not at all important” to “very important.” Scores were dichotomized as very important vs. other categories for analysis. We measured perceived importance of FHH with the item “It is important for my own health to know if diseases like cancer, diabetes, stroke, or heart disease run in my family,” which had a five-point response scale from “strongly disagree” to “strongly agree” (Yoon et al., 2004). We dichotomized participants’ responses as strongly/somewhat agree vs. neither agree nor disagree/somewhat disagree/strongly disagree for analysis.

We examined three different communication behaviors. Communication with family about FHH and communication with a doctor about FHH were assessed with two separate items: “I talk with family members about our family health history” and “I talk with a doctor about my family health history,” respectively (Kaphingst, Goodman, et al., 2012). Both items were answered on a scale from “not at all often” to “very often” and were dichotomized as “very” vs. “somewhat/not very/not at all” often in analysis. We assessed communication about health with friends or family with the item: “How often do you talk to friends or family members about health,” which had the same response scale and was dichotomized in the same way (National Cancer Institute, 2015).

Covariates

We collected data on age, gender, race/ethnicity, educational attainment, marital status, self-reported health, and self-reported family history and personal history of heart disease, diabetes, and cancer. We also examined three psychosocial covariates. We assessed social influences with the item “The people who mean the most to you think you should learn more about ways you can keep yourself healthy,” which had a seven-point response scale from “strongly disagree” to “strongly agree” (Hay et al., 2012). We assessed perceived control using three items (i.e., “There’s a lot I can do to prevent heart disease”), which had five-point response scales from “strongly disagree” to “strongly agree” (Wang et al., 2009). We also assessed behavioral and genetic causal beliefs related to heart disease, diabetes, and cancer using six items (i.e., “How much do you think health habits such as diet, exercise, and smoking determine whether or not a person will get heart disease”), which had a five-point response scale from “not at all” to “completely” (McBride et al., 2009; McBride et al., 2008).

Data Analysis

Data were analyzed using SAS/STAT® Software Version 9.4 for Windows (Cary, NC); statistical significance was assessed as p<0.05. In this analysis, the sample was limited to those who completed the health literacy measure (n=624). We examined descriptive statistics for all variables. We examined the bivariate association between REALM-R score and each outcome using chi-squared tests for categorical outcomes and ANOVA or t-tests for continuous outcomes. We then created multivariable logistic or linear regression models to examine the association between health literacy and outcomes that had a bivariate association with p<.10, controlling for potential confounders (Hildalgo & Goodman, 2013). All multivariable models included age, gender, race, and marital status. Age was modeled continuously. Race/ethnicity was categorized as non-Hispanic White; non-Hispanic Black; or other, and marital status was categorized as married or partnered; divorced, separated, or widowed; or never married. We tested possible covariates for entry into the model and retained those with a p<.10. We examined mediation using the standard three-step approach for testing mediation in regression models described by Baron & Kenny (1986).

Results

About half of participants had limited health literacy (47%, see Table 1). Less than half had completed any college (45%), 38% had a high school degree or GED and 17% had not completed high school. More than half (58%) self-identified as Black. The mean age was 51 years. Two-thirds (67%) were female and about 24% were married or partnered. A majority described themselves as being in “fair” or “poor” health (62%); 65% had been diagnosed with hypertension and 41% with diabetes. The majority reported having a family history of diabetes (76%), cancer (66%), and heart disease (65%).

Table 1.

Characteristics of study participants.

Characteristic Mean Standard Deviation (SD)
Age (n=588) 50.9 11.6
N %
Limited health literacy (n=624) 290 46.5
Female (n=603) 405 67.2
Race
 White 198 31.7
 Black 363 58.2
 Other 63 10.1
Marital status (n=598)
 Married or partnered 145 24.3
 Separated, widowed, or divorced 248 41.5
 Never married 205 34.3
Educational attainment (n=596)
 Less than high school 97 16.6
 High school degree or GED 224 38.2
 Some college or higher 265 45.2
Self-reported health (n=605)
 Poor 98 16.2
 Fair 274 45.3
 Good 171 28.3
 Very good 48 7.9
 Excellent 14 2.3
Personal history of
 Hypertension (n=592) 384 64.9
 Diabetes (n=585) 241 41.1
 Cancer (n=563) 83 14.7
 Heart disease (n=586) 133 22.7
Family history of
 Diabetes (n=583) 443 76.0
 Cancer (n=540) 356 66.0
 Heart disease (n=544) 351 64.5
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On average, participants answered 3 of the 5 genetic knowledge questions correctly (M=3.5, SD=1.1, see Table 2). Most were aware of FHH (87%). Participants had a moderate degree of genetic self-efficacy on average (M=3.2, SD=1.1); the majority were very sure that they could talk with their family members about FHH (75%). Over half (54%) rated genetic information as very important, and 75% rated FHH information as very important. About half reported talking very frequently about health with friends and family (50%), although a smaller proportion reported talking very frequently about FHH with their family (27%) or their doctor (25%).

Table 2.

Frequencies for genomics-related knowledge, self-efficacy, importance, and communication behaviors.

Characteristic Mean Standard Deviation (SD)
Genetic knowledge (n=589) 3.5 1.1
Genetic self-efficacy (n=596) 3.2 1.1
N %
Awareness of FHH (n=611)
 Yes 529 86.6
 No 67 11.0
 Not Sure 15 2.5
FHH self-efficacy (n=607)
 Very sure 456 75.1
 Somewhat sure 120 19.8
 Not at all sure 31 5.1
Importance of genetic information (n=600)
 Very important 321 53.5
 Pretty important 120 20.0
 Somewhat important 104 17.3
 A little bit important 32 5.3
 Not at all important 23 3.8
Importance of FHH (n=613)
 Strongly disagree 52 8.5
 Somewhat disagree 16 2.6
 Neither agree nor disagree 23 3.8
 Somewhat agree 65 10.6
 Strongly agree 457 74.6
Frequency of communication about health with friends or family (n=617)
 Very often 306 49.6
 Somewhat often 191 31.0
 Not very often 98 15.9
 Not at all 22 3.6
Frequency of communication about FHH with family (n=616)
 Very often 163 26.5
 Somewhat often 264 42.9
 Not very often 142 23.1
 Not at all 47 7.6
Frequency of communication about FHH with doctor (n=612)
 Very often 150 24.5
 Somewhat often 213 34.8
 Not very often 183 29.9
 Not at all 66 10.8
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FHH= family health history

In bivariate analysis, we found a number of significant relationships between health literacy and hypothesized outcome variables. Individuals with limited health literacy had significantly lower genetic knowledge (t=9.3, df=482.5, p<.0001) and awareness of FHH (χ2=21.7, p<.0001) than those with adequate health literacy (see Table 3). Participants with limited health literacy were more likely to perceive genetic information as very important (χ2=9.7, p=.0018) but less likely to perceive FHH as very important (χ2=9.4, p=.0022) than those with adequate health literacy. For communication, individuals with limited health literacy were significantly more likely to report talking about FHH very often with both their families (χ2=5.3, p=.021) and doctors (χ2=14.1, p=.0002). There was a trend toward those with limited health literacy having lower self-efficacy about FHH than those with adequate health literacy (χ2=3.6, p=.057).

Table 3.

Bivariate associations between health literacy and genomics-related knowledge, self-efficacy, importance, and communication behaviors.

Characteristic Test Statistic df p-value
Genetic knowledge (n=589) 9.3 482.5 <0.0001
Awareness of FHH (n=611) 21.7 1 <0.0001
Genetic self-efficacy (n=596) −1.1 594 0.2867
FHH self-efficacy (n=607) 3.6 1 0.0571
Importance of genetic information (n=600) 9.7 1 0.0018
Importance of FHH (n=613) 9.4 1 0.0022
Communication about health with friends or family (n=617) 2.0 1 0.1623
Communication about FHH with family (n=616) 5.3 1 0.0211
Communication about FHH with doctor (n=612) 14.1 1 0.0002
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df= degrees of freedom

In multivariable analysis, we found that health literacy was significantly associated with both knowledge variables (see Table 4). Participants with limited health literacy had significantly lower genetic knowledge than those with adequate health literacy (β=−0.55; SE=0.10, p<.0001). In this model, older participants had significantly lower genetic knowledge than younger participants (β= −0.01; SE=0.0042, p=.0050), and Black participants had lower genetic knowledge than White participants, on average (β= −0.30; SE=0.10, p=.0044). Individuals with limited health literacy were less likely to be aware of FHH than those with adequate health literacy (OR=0.50; 95% CI=0.28, 0.90, p=.02). In this model, men were less likely to be aware of FHH than women (OR=0.32; 95% CI=0.19, 0.55, p<.0001).

Table 4.

Associations between health literacy and knowledge about genetics and family health history in multivariable models.

Characteristic Genetic knowledge (n=525) Awareness of family health history (n=541)
β SE p-value OR 95% CI p-value
Limited health literacy −0.55 0.10 <.0001 0.50 (0.28, 0.90) 0.0203
Age −0.01 0.004 0.0050 0.99 (0.97, 1.02) 0.6336
Gender
 Female ref ref ref ref ref ref
 Male −0.08 0.10 0.4404 0.32 (0.19, 0.55) <.0001
Race
 White ref ref ref ref ref ref
 Black −0.30 0.10 0.0044 0.66 (0.34, 1.29) 0.2251
 Other −0.09 0.18 0.6354 0.57 (0.20, 1.66) 0.3027
Marital status
 Married/partnered ref ref ref ref ref ref
 Separated/widowed/divorced −0.10 0.12 0.4124 0.58 (0.28, 1.21) 0.1463
 Never married −0.13 0.12 0.2858 0.63 (0.31, 1.27) 0.1965
Education
 Less than high school ref ref ref ref ref ref
 High school degree or GED 0.03 0.13 0.7931 1.56 (0.83, 2.95) 0.1687
 At least some college 0.29 0.13 0.0307 3.33 (1.63, 6.82) 0.0010
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Health literacy was also significantly associated with perceived importance of both genetic and FHH information in multivariable models, but these associations had different directions (see Table 5). Individuals with limited health literacy were more likely to think that learning genetic information was very important compared to those with adequate health literacy (OR=1.95; 95% CI=1.27, 3.00, p=.0022). In this model, men were less likely to think learning genetic information was very important compared with women (OR=0.59; 95% CI=0.39, 0.89, p=.013), and compared to White participants, both Black participants (OR=1.74; 95% CI=1.14, 2.65, p=.010) and those of another race/ethnicity (OR=2.48; 95% CI=1.14, 5.38, p=.022) were more likely to rate genetic information as very important. In contrast, individuals with limited health literacy were less likely to think that FHH information was very important compared to those with adequate health literacy (OR=0.47; 95% CI=0.26, 0.86, p=.013). In this model, individuals who reported having a family history of cancer were more likely to think that FHH information was very important compared to those without this family history (OR=1.75; 95% CI=1.01, 3.04, p=.045).

Table 5.

Associations between health literacy and perceived importance of and communication about genetics and family health history in multivariable models.

Characteristic Importance of genetic information (n=490) Importance of family health history (n=474) Frequent communication with doctor about FHH (n=537)
OR 95% CI p-value OR 95% CI p-value OR 95% CI p-value
Limited health literacy 1.95 (1.27, 3.00) 0.0022 0.47 (0.26, 0.86) 0.0134 2.02 (1.27, 3.23) 0.0032
Age 1.00 (0.98, 1.02) 0.9500 0.98 (0.96, 1.01) 0.1720 1.00 (0.98, 1.02) 0.6939
Gender
 Female ref ref ref ref ref ref ref ref ref
 Male 0.59 (0.39, 0.89) 0.0127 1.20 (0.67, 2.16) 0.5362 0.48 (0.29, 0.78) 0.0030
Race
 White ref ref ref ref ref ref ref ref ref
 Black 1.74 (1.14, 2.65) 0.0104 1.75 (0.94, 3.25) 0.0774 1.47 (0.88, 2.46) 0.1384
 Other 2.48 (1.14, 5.38) 0.0217 0.76 (0.28, 2.10) 0.5995 1.32 (0.52, 3.37) 0.5615
Marital status
 Married/partnered ref ref ref ref ref ref ref ref ref
 Separated/widowed/divorced 0.93 (0.58, 1.50) 0.7677 1.10 (0.55, 2.21) 0.7806 1.02 (0.59, 1.77) 0.9501
 Never married 0.83 (0.50, 1.36) 0.4565 0.65 (0.32, 1.31) 0.2272 0.96 (0.54, 1.71) 0.8936
Education
 Less than high school ref ref ref ref ref ref ref ref ref
 High school degree or GED 0.96 (0.55, 1.68) 0.8858 0.79 (0.37, 1.67) 0.5336 1.69 (0.89, 3.23) 0.1078
 At least some college 1.32 (0.76, 2.31) 0.3292 0.93 (0.44, 1.98) 0.8470 1.69 (0.89, 3.23) 0.1100
Behavioral causal beliefs
 Diabetes 1.25 (0.80, 1.94) 0.3291 -- -- -- -- -- --
 Heart disease 1.47 (0.95, 2.29) 0.0878 -- -- -- -- -- --
Family history of Cancer -- -- -- 1.75 (1.01, 3.04) 0.0451 -- -- --
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FHH= family health history

Of the communication outcomes, frequent communication with a doctor about FHH was significantly associated with health literacy in a multivariable model. Individuals with limited health literacy were more likely to report discussing FHH with their doctor very often compared to those with adequate health literacy (OR=2.02; 95% CI=1.27, 3.23, p=.0032). In this model, men were less likely to report frequently discussing FHH with a doctor compared with women (OR=0.48; 95% CI=0.29, 0.78, p=.0030).

We did not find significant associations between health literacy and self-efficacy related to genetics or FHH, communication about health, or communication with family about FHH in multivariable models. Because self-efficacy was not associated with health literacy, we did not test whether self-efficacy was a mediator between health literacy and communication with a doctor about FHH. We tested whether genetic knowledge or perceived importance of genetic and FHH information mediated this association, but did not find evidence of mediation, either because the variable was not associated with the outcome (perceived importance of FHH) or adding the variable did not change the effect of health literacy in a multivariable model (genetic knowledge, perceived importance of genetic information).

Discussion

In this study, we examined the associations between health literacy and individuals’ knowledge about genetics and FHH, self-efficacy to communicate about genetics and FHH, perceived importance of genetics and FHH, and communication about health and FHH in a medically underserved population. We found support for our first hypothesis, that individuals with limited health literacy would have lower knowledge about genetics and FHH. These results, in addition to the consistent findings described in the Introduction that individuals with lower educational attainment have lower genetic knowledge, suggest that there is a strong need to examine why differences exist in knowledge about genomics by both health literacy and education. Prior research has also found disparities in awareness of FHH across subgroups (Yoon et al., 2004), but we do not yet understand why these differences exist. Other researchers have suggested that differences in knowledge across population subgroups might be due to differences in exposure to genetic information (Hughes et al., 1997), differences in information sources (Catz et al., 2005; Parrott et al., 2004), or different levels of formal education about genetics (Furr & Kelly, 1999), but empirical research is limited.

In addition, the finding that individuals with limited health literacy have lower genetic knowledge suggests that it is critical to consider health literacy in developing approaches to educating individuals about genomics. Currently, the way in which this information is presented is likely to be too difficult for many adults (Lachance, Erby, Ford, Allen, & Kaphingst, 2010; Wang, Gallo, Fleisher, & Miller, 2011). Some prior studies have examined various educational approaches for genetic and genomic information, for example, education during genetic counseling (Edwards et al., 2008; Kelly et al., 2004; Lerman et al., 1997), computer-based educational approaches (Green et al., 2004; Meilleur & Littleton-Kearney, 2009), and culturally-tailored educational approaches led by lay health advisors (Kaphingst et al., 2011). However, these studies have not investigated whether the effectiveness of different educational approaches varies by health literacy. A number of researchers have suggested genomics educational approaches based on the health literacy literature (Kaphingst & McBride, 2010; Lea et al., 2011; Syurina, Brankovic, Probst-Hensch, & Brand, 2011), but research is limited. Future studies should incorporate theoretical and conceptual work that has been conducted to identify relevant components of genomic knowledge that inform health decision making (Decruyenaere, Evers-Kiebooms, Welkenhusen, Denayer, & Claes, 2000; Smerecnik, Mesters, de Vries, & de Vries, 2008). In particular, the conceptual distinction between awareness knowledge, how-to knowledge, and principles knowledge related to genetics developed by Smerecnik et al. (2008) could allow us to identify and focus educational efforts on the most salient aspects of genomics for improving health. Such studies could also examine what types of genomic knowledge are relevant for an individual at different times in the lifespan (Condit, 2010; Syurina et al., 2011).

Our second hypothesis was not supported; we found no significant association between health literacy and self-efficacy related to genetics and FHH. This could be for a number of reasons. We may need to measure different aspects of communication self-efficacy related to genetics and FHH. It is also possible that health literacy is related to actual communication behaviors as suggested by prior literature (Schillinger et al., 2004), but not to individuals’ confidence in their ability to perform these communication behaviors. A recent study found that direct-to-consumer genetic testing lowered genetic self-efficacy, and the authors suggest that this might reflect an appropriate reevaluation by consumers in response to receiving complex genetic information (Carere, Kraft, Kaphingst, Roberts, & Green, 2015). The relationship between health literacy and genomics self-efficacy may be challenging to investigate because of the unfamiliarity of this complex topic for many individuals.

For our third hypothesis, we found an association between health literacy and communication about FHH, although not in the hypothesized direction since individuals with limited health literacy were more likely to report frequent communication with a doctor about FHH. We hypothesize that this unexpected result may be due in part to more frequent health care provider visits among those with limited health literacy, since there is some evidence that patients with limited health literacy have greater health care utilization (Berkman et al., 2011). For our fourth hypothesis, the variables that we proposed (i.e., knowledge, self-efficacy, perceived importance) did not act as mediators in the relationship between health literacy and communication behaviors. A priority for future research will be to examine the pathways underlying the relationship between health literacy and communication about genomic information (Williams et al., 2002).

Interestingly, health literacy was not associated with communication about FHH with family members or communication about health with friends and family. While we examined the frequency of communication because researchers have emphasized the importance of ongoing conversations about FHH to generate and maintain an accurate record (Acheson, Weisner, Zyzanski, Goodwin, & Stange, 2000; Medalie, Zyzanski, Langa, & Stange, 1998), it may be that health literacy is related to the quality of provider-patient communication rather than the frequency of this communication (Schillinger et al., 2004; Schillinger et al., 2003; Williams et al., 2002). Observational and longitudinal studies that investigate provider and patient communication behaviors by level of health literacy could help to disentangle this issue and examine how quality and quantity of communication affect downstream behaviors. It is also important to note that we did not measure frequency of communication about genetics with a doctor or with family members, because genetic testing is not yet common among medically underserved patients. As genomic information diffuses to an increasingly greater proportion of the population (McBride et al., 2010), this will be an important issue to examine.

Our data highlighted that patients with limited health literacy did not place equal value on genetic and FHH information. We found that these patients were more likely to view genetic information as very important, but less likely to view FHH information as very important, compared to those with adequate health literacy. This finding suggests that messages about the importance and usefulness of FHH may not be reaching individuals with limited health literacy, or that they may not understand these messages, and that we need to develop new ways of communicating this information to reach a broader population (Kaphingst et al., 2011). Our prior work has indicated that individuals with limited health literacy may be more interested in receiving an assessment of genomic risk based on genetic testing than those with higher health literacy (Kaphingst et al., 2015), and other researchers have found that genetics-related literacy may impact how patients evaluate the utility of genetic testing (Hooker et al., 2014). Assessing knowledge of the benefits of genetic technologies separately from knowledge of the limitations may be important to understand the association between health literacy and knowledge (Kaphingst, Facio, et al., 2012).

The findings from this study should be interpreted in light of its limitations. Because we conducted the study in a busy primary care clinic, we were not always able to complete the verbally-administered health literacy measure with those who agreed to participate, reducing our analytic sample size. In order to reduce patient burden we were only able to ask a limited number of questions for each construct, and some constructs were assessed only with a single item. The REALM-R only assesses a part of the construct of health literacy, and future studies are needed to examine how other domains (e.g., oral literacy, numeracy) affect these outcomes. We did not make statistical adjustment for multiple comparisons. We were not able to assess other variables that might impact provider-patient communication behaviors, such as the quality of the provider-patient relationship. We were not able to examine related questions such as who initiated communication about FHH and whether participants felt that the frequency of communication about FHH met their needs. The findings may not generalize to other patient populations, particularly patients from other racial and ethnic groups or younger patients. Since we have previously found that age is related to genetic knowledge and beliefs (Ashida et al., 2011), the research questions on which this study focused are important to investigate in other patient populations. Because many patients in this sample had already developed chronic conditions, they may have different communication behaviors about genomic information than a younger, healthy population. However, it is still important to examine communication behaviors among older adults, as they are an important source of information about inherited risks within the family (Ashida et al., 2011).

Despite these limitations, this study added to the existing literature in a number of important ways. We investigated whether health literacy was related to a number of outcomes (i.e., knowledge, self-efficacy, perceived importance, communication) suggested by our conceptualization of genomics-related health literacy (Hurle et al., 2013; Lea et al., 2011) among a medically underserved patient population, an important group often overlooked in genetics-related research. We found support for some aspects of our framework. Health literacy was related to knowledge about genomic information and the reported frequency of communication with providers about FHH. Although further research is needed to investigate these effects and other types of provider-patient communication about genomics, the findings do suggest that the domains of knowledge and oral literacy are important aspects of genomics-related health literacy. We also found that individuals with limited health literacy placed greater value on genetic information than FHH information, despite the current greater usefulness of the latter for most individuals (Kaphingst et al., 2015; Valdez et al., 2010). This result highlights the need to investigate the underlying mechanisms further and develop messages regarding the importance of FHH for individuals with limited health literacy. As genomic information plays an increasingly important role in medicine and public health, health literacy research is critically necessary in order to avoid increasing existing health inequalities in information, services, and health outcomes (De Viron, Suggs, Brand, & Van Oyen, 2013; Hurle et al., 2013).

Acknowledgments

This study and the work of the project team was supported by the Barnes-Jewish Hospital Foundation, Siteman Cancer Center (National Cancer Institute, National Institutes of Health grant P30 CA91842), Washington University School of Medicine (WUSM), and the WUSM Faculty Diversity Scholars Program. KAK was supported by funding from the Huntsman Cancer Institute and University of Utah. The funding agreement ensured the authors’ independence in designing the study, interpreting the data, writing, and publishing the report. We would like to thank the study participants, data collection and data entry team, Center for Outpatient Health Primary Care Clinic staff, administrators, and residents for their contributions to our work.

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