VTechWorks staff will be away for the Thanksgiving holiday beginning at noon on Wednesday, November 22, through Friday, November 24, and will not be replying to requests during this time. Thank you for your patience, and happy holidays!
Exploring Cross-Sectional Relationships between Health Literacy, Dietary Intake, Physical Activity, and Anthropometric/Biological Variables among Residents in Southwest Virginia
Wilburn, Grace Alexandra
MetadataShow full item record
BACKGROUND: Low health literacy and numeracy are significant problems facing the United States. Recent research focuses heavily on the role health literacy and numeracy play in perception of disease risk, health care costs, all-cause mortality, and access to care; however, there has been relativity little emphasis on the relationships between health literacy or numeracy with health promotion behaviors, such as nutrition or physical activity. As our nation continues to face challenges with the high prevalence of obesity and other chronic diseases, it is increasingly important to understand the role that health literacy and numeracy play in nutrition and physical activity behaviors, as well as in the prevalence and control of chronic disease. PRIMARY AIMS: The proposed research is embedded within a larger randomized-control trial, Talking Health, which is a 2-arm behavioral trial targeting residents in eight counties in southwest Virginia with sugar-sweetened beverage (SSB) consumption as the primary outcome. The primary aims of this cross-sectional study, using baseline Talking Health data, are to 1) examine correlations among health literacy and numeracy measures, namely the Newest Vital Sign (NVS), separated by reading (NVS Reading) and math (NVS Math) scores, the Rapid Estimate of Adult Literacy in Medicine (REALM), and the Subjective Numeracy Scale (SNS); 2) explore the relationships between demographic factors and the NVS, REALM, and SNS scores; 3) determine the relationships between the NVS, REALM, and SNS and dietary quality [i.e. Health Eating Index (HEI) scores], physical activity behaviors, and anthropometric and biological variables (body mass index, blood pressure, fasting blood lipids, and fasting blood glucose); and 4) determine if NVS, REALM, and SNS scores predict metabolic syndrome (MetS), while controlling for relevant demographic factors. METHODS: Eligibility requirements for the study include being 18 years of age or older, having reliable access to a telephone, drinking �[BULLET]�200 kilocalories of SSB per day, and being a resident of Southwest Virginia. Using previously validated instruments and standardized data collection protocol, a variety of baseline variables was collected on 264 participants. Health literacy was measured using the NVS and REALM and health numeracy was measured using the SNS. Dietary intake was measured via three 24-hour dietary recalls and HEI scores were calculated. Physical activity behaviors were assessed using the Godin Leisure Time Exercise Questionnaire. Weight was measured using a calibrated digital Tanita scale (Model: 310GS), height was measured using a portable research-grade stadiometer, blood pressure measurements were made with an OMRON automated oscillometric device (Model: HEM-907XL), and fasting blood samples were obtained via a finger stick and the CardioChek PA system was used to assess blood glucose, cholesterol, and triglycerides. MetS scores were determined based on an adaptation of the National Cholesterol Education Program guidelines. Statistical analysis included descriptive statistics, simple correlations (Pearson bivariate), one-way ANOVAs, and regression models. RESULTS: Of 264 enrolled participants (mean age 41.1 + 13.5 years; 92.0% Caucasian; 81.8% female; 30.6% > high school education; 42% > $15,000 annual income), 33.7% were classified as having a high probability of low health literacy or possibility of low health literacy as measured by the NVS, 19.7% had less than a high school reading level as measured by the REALM, and 45.4% had low health numeracy as measured by the SNS. Additionally, 78.8% were overweight or obese and 29.0% meet the criteria for metabolic syndrome. Nine of the ten correlations between the NVS Total, NVS Reading, NVS Math, REALM, and SNS were statistically significant (p < .01, two-tailed). NVS scores were found to be significantly different by age (F = 2.36, p = .05), race (F = 4.49, p = .03), education level (F = 20.97, p < .001), and income (F = 13.88, p < .001); while REALM scores were only significantly different by race (F = 3.74, p = .05), education level (F = 21.06, p < .001), and income (F = 6.80, p < .001). SNS scores were significantly different by gender (F = 12.40, p = .001), education level (F = 11.01, p < .001), and income (F = 14.45, p < .001). Only systolic blood pressure, diastolic blood pressure, and strength training activity was found to be significantly different by health literacy and/or numeracy level; however, when controlling for hypertension medication use and/or demographic variables, only the relationship between health literacy (i.e, NVS) and strength training activity remained significant (R2 = 0.09, p = .01). Finally, health literacy and numeracy were not found to be predictive of metabolic syndrome while controlling for demographic variables. DISCUSSION: Although numerous demographic factors were related to baseline health literacy and numeracy levels, anthropometric/biological variables, physical activity behaviors, and diet quality did not differ by health literacy and health numeracy level, with the exception of systolic blood pressure and strength training activity. This research helps to fill the gaps in the literature surrounding the prevalence of health literacy, health numeracy, and health promoting behaviors and chronic disease among rural residents in medically underserved counties in southwest Virginia. While few cross-sectional relationships were found, future research from this RCT should examine if health literacy and health numeracy moderates or mediates intervention changes in anthropometric/biological variables, physical activity behaviors, diet quality, and metabolic syndrome scores.
- Masters Theses