OBJECTIVES: Our purpose was to describe relationships between demographic characteristics, body mass index (BMI), and health literacy among Native Hawaiians and other Pacific Islanders (NHPIs). DESIGN AND SAMPLE: In this cross-sectional survey, we interviewed 364 NHPI adults. MEASURES: We used Newest Vital Sign (NVS), a health literacy tool; measured heights and weights; and demographic questions. RESULTS: According to participants' NVS scores, 45.3% had at least a possibility of low health literacy. Lower NVS scores were associated with increased BMI (r = -0.12, p = .027) and increased age (r = -0.26, p < .001). Higher NVS scores were associated with higher incomes (r = 0.21, p = .001) and higher education (r = 0.27, p < .001). Women scored significantly better than men (t = -2.0, p = .05). Participants' NVS scores in Hawaii versus Utah were not significantly different (t = .26, p = .80). CONCLUSIONS: Pathways to health literacy are complex; however, age, income, education, and BMI explained a modest 19.95% of the combined variance in NVS scores. Public health nurses working to improve health literacy could include review of critical information on nutrition facts labels, frequently used calculations, and application of this information when making food choices.
OBJECTIVES: Our purpose was to describe relationships between demographic characteristics, body mass index (BMI), and health literacy among Native Hawaiians and other Pacific Islanders (NHPIs). DESIGN AND SAMPLE: In this cross-sectional survey, we interviewed 364 NHPI adults. MEASURES: We used Newest Vital Sign (NVS), a health literacy tool; measured heights and weights; and demographic questions. RESULTS: According to participants' NVS scores, 45.3% had at least a possibility of low health literacy. Lower NVS scores were associated with increased BMI (r = -0.12, p = .027) and increased age (r = -0.26, p < .001). Higher NVS scores were associated with higher incomes (r = 0.21, p = .001) and higher education (r = 0.27, p < .001). Women scored significantly better than men (t = -2.0, p = .05). Participants' NVS scores in Hawaii versus Utah were not significantly different (t = .26, p = .80). CONCLUSIONS: Pathways to health literacy are complex; however, age, income, education, and BMI explained a modest 19.95% of the combined variance in NVS scores. Public health nurses working to improve health literacy could include review of critical information on nutrition facts labels, frequently used calculations, and application of this information when making food choices.
Authors: Heather D Gibbs; Amy R Kennett; Elizabeth H Kerling; Qing Yu; Byron Gajewski; Lauren T Ptomey; Debra K Sullivan Journal: J Nutr Educ Behav Date: 2016-05-20 Impact factor: 3.045
Authors: Jared W Magnani; Mahasin S Mujahid; Herbert D Aronow; Crystal W Cené; Victoria Vaughan Dickson; Edward Havranek; Lewis B Morgenstern; Michael K Paasche-Orlow; Amy Pollak; Joshua Z Willey Journal: Circulation Date: 2018-06-04 Impact factor: 29.690
Authors: Monica L Wang; Tariana V Little; Christine Frisard; Amy Borg; Stephenie C Lemon; Milagros C Rosal Journal: PLoS One Date: 2018-10-24 Impact factor: 3.240