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Using existing dietary data for evaluating the construct validity of a nutrient profiling model / Susara JohannaLeeLee, Susara Johanna January 2013 (has links)
AIM: Nutrient profiling can be defined as ‘the science of categorising foods according to their nutritional composition’ and can be used as a valuable tool in food labelling legislation. Validation is an absolute essential step in the implementation of a nutrient profiling model (NPM), it is important to verify whether or not the NPM has a good solid scientific basis and if it is at all suitable for South Africa. This mini-dissertation investigated the construct validity of a NPM for South Africa.
OBJECTIVES: 1) To test construct validity for the nutrient profiling model by examining the relationship between the way the NPM categorises foods and the healthiness of diets in South Africa. 2) To assess if the quality of a diet will improve if ‘unhealthy’ foods are replaced by ‘healthy’ foods as defined by the NPM.
STUDY DESIGN: Nested in the South African leg of the international PURE (Prospective Urban and Rural Epidemiology) study at baseline.
METHOD: The PURE (Prospective Urban and Rural Epidemiology) baseline study conducted in the North-West province in 2005, was identified as a suitable dataset of food intake. For the first objective the proportion of respondent’s diets consisting of healthy or unhealthy food, as classified by the NPM, was calculated. The respondents were divided into four groups based on their dietary quality as characterised by the Diet Quality Index (DQI), the lower the DQI-score the better the diet quality. The proportion of healthy or unhealthy foods were compared to the DQI-scores using one-way ANOVA’s, p-values were calculated using the Tukey post-hoc test. For the second objective the diet quality of four different diets consisting of either YES foods (according to NPM), NO foods, a combination of YES and NO were calculated and compared.
RESULTS: The model displayed good construct validity by showing a statistically significant positive relationship between the proportion of ‘healthy’ (p<0.0001) and ‘unhealthy’ (p<0.0001) foods, as classified by the NPM, and participants’ DQI-scores. The second objective was also confirmed and a diet consisting of ‘healthy’ foods or a diet where ‘unhealthy’ foods were substituted by ‘healthy’ foods, had a better DQI than diets consisting only of ‘unhealthy’ foods CONCLUSION: Construct validity was confirmed by proving that the better the diet quality of the respondents the bigger their proportion of foods categorised as ‘healthy’ by the NPM and vice versa. / MSc (Dietetics), North-West University, Potchefstroom Campus, 2014
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Using existing dietary data for evaluating the construct validity of a nutrient profiling model / Susara JohannaLeeLee, Susara Johanna January 2013 (has links)
AIM: Nutrient profiling can be defined as ‘the science of categorising foods according to their nutritional composition’ and can be used as a valuable tool in food labelling legislation. Validation is an absolute essential step in the implementation of a nutrient profiling model (NPM), it is important to verify whether or not the NPM has a good solid scientific basis and if it is at all suitable for South Africa. This mini-dissertation investigated the construct validity of a NPM for South Africa.
OBJECTIVES: 1) To test construct validity for the nutrient profiling model by examining the relationship between the way the NPM categorises foods and the healthiness of diets in South Africa. 2) To assess if the quality of a diet will improve if ‘unhealthy’ foods are replaced by ‘healthy’ foods as defined by the NPM.
STUDY DESIGN: Nested in the South African leg of the international PURE (Prospective Urban and Rural Epidemiology) study at baseline.
METHOD: The PURE (Prospective Urban and Rural Epidemiology) baseline study conducted in the North-West province in 2005, was identified as a suitable dataset of food intake. For the first objective the proportion of respondent’s diets consisting of healthy or unhealthy food, as classified by the NPM, was calculated. The respondents were divided into four groups based on their dietary quality as characterised by the Diet Quality Index (DQI), the lower the DQI-score the better the diet quality. The proportion of healthy or unhealthy foods were compared to the DQI-scores using one-way ANOVA’s, p-values were calculated using the Tukey post-hoc test. For the second objective the diet quality of four different diets consisting of either YES foods (according to NPM), NO foods, a combination of YES and NO were calculated and compared.
RESULTS: The model displayed good construct validity by showing a statistically significant positive relationship between the proportion of ‘healthy’ (p<0.0001) and ‘unhealthy’ (p<0.0001) foods, as classified by the NPM, and participants’ DQI-scores. The second objective was also confirmed and a diet consisting of ‘healthy’ foods or a diet where ‘unhealthy’ foods were substituted by ‘healthy’ foods, had a better DQI than diets consisting only of ‘unhealthy’ foods CONCLUSION: Construct validity was confirmed by proving that the better the diet quality of the respondents the bigger their proportion of foods categorised as ‘healthy’ by the NPM and vice versa. / MSc (Dietetics), North-West University, Potchefstroom Campus, 2014
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