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Determining food and nutrition literacy of community health workers in the Western Cape, South AfricaKetelo, Asiphe January 2020 (has links)
Master of Public Health - MPH / Obesity is one of the critical problems that threatens not only health, but the
economy at a global level. Among the factors associated with obesity is less than optimum
level of nutrition literacy. Nutrition literacy is more than just the food knowledge, it is a
combination of other essential factors that help individuals to maintain healthy a body size.
These factors include the selection and consumption of nutritious food; acquiring knowledge
and skills in the areas of meal planning and preparation; as well as using and knowing how to
read food labels correctly.
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Nutrition Literacy And Demographic Variables As Predictors Of Adolescent Weight Status In A Florida CountyD'Amato-Kubiet, Leslee 01 January 2013 (has links)
In recent years, childhood obesity has increased to epidemic proportions across the United States (U.S.) in parallel with adult obesity, which often reflects poor dietary choices and bad nutritional habits. Nutrition literacy, which encompasses the constructs of nutrition knowledge and skills, is considered a basic tool for good dietary habits and health promotion undertakings; however, its more definitive relationship to adolescent children’s weight status is unknown. Most childrens’ weight status studies have focused solely on behavioral aspects of adolescent food intake, taking into consideration parental influence, peer pressure, and societal expectations. Studies evaluating the measurement of nutrition literacy with regard to adolescent weight status are non-existent. The primary purpose of this study was to examine the effects of parent and adolescent nutrition literacy expressed as nutrition knowledge and skills, with total household income and parent level of education, as predictors of weight status in adolescents that live in a Florida community. The secondary purpose of this study was to examine the implications for nutrition literacy levels within parent/adolescent dyads to identify public health initiatives aimed at adult and adolescent populations. Parent/adolescent dyads were screened against inclusion criteria and 110 dyads were chosen to participate. Following informed consent from the parent and assent from the adolescent, demographic data were collected and the parent/adolescent participants were asked to complete two study instruments: the Nutrition Literacy Survey (NLS) testing nutrition knowledge (Diamond, 2007) and the Newest Vital Sign (NVS) assessing nutrition skills (Weiss, Mays, Martz, Castro, DeWalt, Pignone, Mockbee, Hale, et al., 2005). The written instruments were administered to both parents and the adolescent child simultaneously, directly following the collection of adolescent height and weight. iv First, paired t-tests were used to compare means for the NLS and NVS survey in parentadolescent dyads. Next, bivariate correlation scores were computed between the two variables of parent/adolescent NLS and NVS scores. Higher total correct scores indicated higher levels of nutrition knowledge, whereas lower total correct scores indicated lower nutrition knowledge. Next, a correlation analysis using the Pearson r correlation coefficient was computed to determine if a relationship existed between nutrition knowledge and nutrition skills in parentadolescent dyads. Lastly, regression models for examining adolescent BMI were compared with the independent variables of the study. The first model used standard multiple regression analysis to determine the correlation between parent/adolescent level of nutrition knowledge and parent/adolescent level of nutrition skills to children’s weight status (BMI). The second model used logistic regression analysis to determine if a correlation between parent/adolescent level of nutrition knowledge, parent/adolescent level of nutrition skills, and demographic characteristics, to children’s BMI could be predicted. The third model used the same procedure for logistic regression with all IV data as categorical data rather than actual values. Gender was included in the final model, since it was of relevance to BMI for adolescent populations. The study results indicate that adolescent male participants had higher BMI (27 + 3.48) than females (24 + 2.90), t(108) = 4.83, (p = < .001). The results suggest that percentage underweight/normal weight for males (32.8%) and females (75.5%) and percentage overweight/obese for males (67.2%) and females (24.5%) differed comparatively between the two groups, with a larger percentage of adolescent males having greater BMI than female adolescents. The mean Nutrition Literacy Scale score (M=19) for parent (adult) study participants indicated low overall levels of general nutrition knowledge whereas the mean Nutrition Literacy v Scale score (M=21.7) for adolescent study participants demonstrated slightly greater aptitude for general nutrition knowledge than parental scores. The mean Newest Vital Sign score (M=4.1) for parents suggests adequate levels of nutrition skills. Likewise, the mean Newest Vital Sign score (M= 4.1) for adolescents suggests adequate levels of nutrition skills, similar to scores attained in the adult population. Spearman rho correlations yielded positive correlations between parents’ nutrition knowledge and adolescents’ nutrition knowledge, (rs = .224, p = .019), and parents’ nutrition knowledge and skills (rs = .596, p < .001). Positive correlations were also noted between adolescents’ nutrition knowledge and parents’ nutrition skills (rs = .257, p = .007) and adolescents’ nutrition knowledge and nutrition skills (rs = .260. p = .006). For the first model, a multiple regression was calculated to predict BMI from parent/adolescent nutrition knowledge and parent/adolescent nutrition skills. These variables did not statistically predict adolescent BMI, F(4,109) = .348, p < .845, R2 = .013. All four variables did not significantly add to the prediction, p < .05. In the second model, a logistic regression was computed to predict adolescent underweight/normal weight and overweight/obese from parent/adolescent nutrition knowledge and parent/adolescent nutrition skills, household income, and parent education level. These variables did not statistically predict adolescent weight status, (χ2 (6) =3.31, p = .769; -2 Log Likelihood 149.036; R2 .03; Hosmer and Lemeshow Goodness-of-Fit χ2 (8) = 12.36, p = .136). In the third model, a logistic regression was calculated to predict adolescent underweight/normal weight and overweight/obese from parent/adolescent nutrition knowledge and parent/adolescent nutrition skills, household income, and parent education level, and adolescent gender. These variables did not statistically predict adolescent weight status, (χ2 (11) vi = 14.506, p = .206; -2 Log Likelihood 137.841; R2 .124; Hosmer and Lemeshow Goodness-ofFit χ2 (8) = 10.864, p = .210. Analysis of regression coefficients indicates none of the variables demonstrated significance. The results of the study suggest that parents and adolescents may have similar amounts of nutrition literacy when examining the constructs of nutrition knowledge and skills; however, BMI is not solely dependent on these skill sets. Gender may play an important role in the prediction of BMI in adolescents. Examination of the factors that influence parents and children’s weight status are important elements in shaping families adoption of sound dietary habits and improving health outcomes
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Validity of a Food Literacy Assessment Tool in Food Pantry ClientsHitchcock, Kathryn 02 November 2018 (has links)
No description available.
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The state of social media usage to fight malnutrition among children under the age of five years in TanzaniaMbilinyi, Debora January 2023 (has links)
This study has evaluated how Tanzania Food and Nutrition Centre (TFNC), a government institution overseeing nutrition, uses social media to enhance the nutrition literacy of caregivers and parents of children under the age of five years. The study contributes to knowledge on how Tanzania’s resource-constrained health sector’s nutrition communication can benefit from social media by answering the following research questions: Which social media platforms and features does TFNC use to share nutrition knowledge pertaining to children under the age of five years? What kinds of nutrition knowledge pertaining to children under the age of five years does TFNC share on social media? How is nutrition knowledge pertaining to children under the age of five years posted on TFNC social media pages packaged? And, how frequently is nutrition knowledge pertaining to children under the age of five years repeated on TFNC social media pages? These questions have been answered from a social-behavioral change communication perspective that has combined the Media Ecology Theory and the Theory of Planned Behavior. This quantitative study has gathered data on TFNC’s social media activities (posts containing nutrition knowledge pertaining to children under the age of five years) between May 2020 to April 2023. The posts were manually extracted from the center’s pages into Microsoft Excel for coding before exportation to SPSS version 20 for analysis. The study has found that TFNC actively uses Facebook, Instagram, Twitter, and YouTube to share nutrition knowledge on its pages and video format is the most used. The shared educative nutrition knowledge during the observed period, the use of social media features in sharing the knowledge, and the frequency of repeating nutrition messages are limited. Overall, the center’s nutrition social media-based knowledge-sharing needs improving to optimally contribute to nutrition literacy pertaining to children under the age of five years.
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