Effect of an Education Program on Nutrition Knowledge, Attitudes toward Nutrition, Diet Quality, Lifestyle, and Body Composition in Polish Teenagers. The ABC of Healthy Eating Project: Design, Protocol, and Methodology

Hamułka, Jadwiga; Wądołowska, Lidia; Hoffmann, Monika; Kowalkowska, Joanna; Gutkowska, Krystyna

doi:10.3390/nu10101439

Cited by 110 publications

(147 citation statements)

References 66 publications

(92 reference statements)

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“…Increasing the dietary knowledge of the general population is an important way to improve their dietary habits and lifestyle while reducing incidences of obesity-related non-communicable diseases throughout the whole lifespan [31]. Using the large-scale CHNS data, this study measured the proportion of residents who were aware of dietary guidelines and who correctly answered the dietary knowledge questions.…”

Section: Discussionmentioning

confidence: 99%

Explaining Income-Related Inequalities in Dietary Knowledge: Evidence from the China Health and Nutrition Survey

Zhu

Zhang

et al. 2020

IJERPH

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Lack of adequate dietary knowledge may result in poor health conditions. This study aims to measure income-related inequality in dietary knowledge, and to explain the sources of the inequality. Data were from the China Health and Nutrition Survey (CHNS) conducted in 2015. A summary of the dietary knowledge score and dietary guideline awareness was used to measure the dietary knowledge of respondents. The concentration index was employed as a measure of socioeconomic inequality and was decomposed into its determining factors. The study found that the proportion of respondents who correctly answered questions on dietary knowledge was significantly low for some questions. Compared to rural residents, urban residents had a higher proportion of correctly answered dietary knowledge questions. In addition, there are pro-rich inequalities in dietary knowledge. This observed inequality is determined not only by individual factors but also high-level area factors. Our study recommends that future dietary education programs could take different strategies for individuals with different educational levels and focus more on disadvantaged people. It would be beneficial to consider local dietary habits in developing education materials.

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Section: Discussionmentioning

confidence: 99%

Explaining Income-Related Inequalities in Dietary Knowledge: Evidence from the China Health and Nutrition Survey

Zhu

Zhang

et al. 2020

IJERPH

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“…Obesity and overweight have a multi-factorial aetiology, but the most important factor appears to be the shift in the environmental and socioeconomic conditions in the last century with unlimited access to hypercaloric food and decreased physical activity (3). Current data point to the fact that although genetic factors contribute to the risk of obesity, the influence is modest with an average difference of only 2.7 kg/m 2 between individuals with high genetic risk and those with low genetic risk (4).…”

Section: Introductionmentioning

confidence: 99%

Risk factors for adiposity in the urban population and influence on the prevalence of overweight and obesity

et al. 2020

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Obesity and overweight are major contributors to the morbidity and mortality of modern civilization. This study determined the prevalence of certain risk factors for adiposity and assesses their impact on overweight/obesity prevalence. Nine hundred individuals were evaluated, aged between 18-65 years, including clinical examination, evaluation of medical history, BMI determination and completion on questionnaires assessing nutritional intake and presence of depression symptoms. Overweight prevalence was 29.56% and obesity prevalence was 21.33%. Fast-food consumption was the most frequent risk factor for adiposity found in 61.67% of individuals, eating <3 meals/day was found in 58.89%, sedentary lifestyle in 53.33%, sleeping time <6 h/day in 44.22%, hypercaloric nutrition in 43.56%, excessive alcohol consumption in 42.89% and depression symptoms in 31.78%. Unhealthy lifestyle a composite risk factor was identified in 67.33% of individuals. Fast-food consumption increases the risk for adiposity by 1.85-fold while sedentary lifestyle by 1.79-fold. Risk factors for adiposity play an important role in increasing the prevalence of overweight and obesity. Public health measures are necessary in order to educate the general population regarding the importance of healthy nutrition and physical exercise.

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“…The SF-FFQ4PolishChildren is a self-administered tool developed for schoolchildren by Kowalkowska, Wadolowska, and Hamulka in 2015 and previously published by Hamulka et al [22]. The questionnaire consisted of a total of 44 items regarding: Dietary habits (11 items), nutrition knowledge (18 items), active/sedentary lifestyle (3 items), demographics (4 items), the Family Affluence Scale (FAS) components (6 items), anthropometric data (2 items).…”

Section: A Short-form Multicomponent Dietary Questionnaire (Sf-ffq4pmentioning

confidence: 99%

“…Respondents reported its consumption choosing one of four categories: Less than once a week, 1-2 times/week, 3-4 times/week, every school day (5 times/week). For food items, respondents could choose one of seven consumption frequency categories (converted into daily frequency, times/day): Never/almost never (0), less than once a week (0.06), once a week (0.14), 2-4 times/week (0.43), 5-6 times/week (0.79), every day (1), a few times a day (2) [22].…”

Section: Dietary Habitsmentioning

confidence: 99%

“…To evaluate overall diet quality, a pro-healthy diet index (pHDI) and a non-healthy diet index (nHDI) were established based on previous knowledge and other studies [15,23]. The diet quality scores were created a priori by summing the consumption frequencies (times/day) of the following food items: The pHDI-dairy products, fish, vegetables, fruit; the nHDI-fast food, sweetened soft drinks, energy drinks and sweets [22]. Each diet quality score was expressed in % points and categorized as follows: Low (0-33.32% points), moderate (33.33-66.65% points), high (66.66-100% points).…”

Section: Dietary Habitsmentioning

confidence: 99%

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Reproducibility of a Short-Form, Multicomponent Dietary Questionnaire to Assess Food Frequency Consumption, Nutrition Knowledge, and Lifestyle (SF-FFQ4PolishChildren) in Polish Children and Adolescents

et al. 2019

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The aim of the study was to assess the reproducibility of a short-form, multicomponent dietary questionnaire (SF-FFQ4PolishChildren) in Polish children and adolescents. The study involved 437 children (6–10 years old) and 630 adolescents (11–15 years old) from rural and urban areas of Poland. The self-administered questionnaire was related to nutrition knowledge, dietary habits, active/sedentary lifestyle, self-reported weight and height, and socioeconomic data. The questionnaire was completed with a two-week interval—twice by parents for their children (test and retest for children), twice by adolescents themselves (adolescent’s test and retest) and once by adolescents’ parents (parent’s test). The strength of agreement measured using the kappa statistic was interpreted as follows: 0–0.20 slight, 0.21–0.40 fair, 0.41–0.60 moderate, 0.61–0.80 good, and 0.81–1.00 excellent. Regarding the frequency of consumption of food items and meals, kappa statistics were 0.46–0.81 (the lowest: fruit/mixed fruit and vegetable juices; the highest: Energy drinks) in test–retest for children, 0.30–0.54 (fruit/mixed fruit and vegetable juices; breakfast, respectively) in adolescent’s test–retest, 0.27–0.56 (the lowest: Sweets, fruit, dairy products; the highest: Breakfast) in adolescent’s test and parent’s test. Lower kappa statistics were found for more frequently consumed foods (juices, fruit, vegetables), higher kappa statistics were found for rarely consumed foods (energy drinks, fast food). Across study groups, kappa statistics for diet quality scores were 0.31–0.55 (pro-healthy diet index, pHDI) and 0.26–0.45 (non-healthy diet index, nHDI), for active/sedentary lifestyle items they were 0.31–0.72, for components of the Family Affluence Scale (FAS) they were 0.55–0.93, for BMI categories (based on self-reported weight and height) they were 0.64–0.67, for the nutrition knowledge (NK) of adolescents the kappa was 0.36, for the nutrition knowledge of children’s parents it was 0.62. The Spearman’s correlations for diet quality scores were 0.52–0.76 (pHDI) and 0.53–0.83 (nHDI), for screen time score they were 0.45–0.78, for physical activity score they were 0.51–0.77, for the FAS score they were 0.90–0.93, and for the NK score they were 0.68–0.80. The questionnaire can be recommended to evaluate dietary and lifestyle behaviors among children and adolescents.

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Effect of an Education Program on Nutrition Knowledge, Attitudes toward Nutrition, Diet Quality, Lifestyle, and Body Composition in Polish Teenagers. The ABC of Healthy Eating Project: Design, Protocol, and Methodology

Cited by 110 publications

References 66 publications

Explaining Income-Related Inequalities in Dietary Knowledge: Evidence from the China Health and Nutrition Survey

Explaining Income-Related Inequalities in Dietary Knowledge: Evidence from the China Health and Nutrition Survey

Risk factors for adiposity in the urban population and influence on the prevalence of overweight and obesity

Reproducibility of a Short-Form, Multicomponent Dietary Questionnaire to Assess Food Frequency Consumption, Nutrition Knowledge, and Lifestyle (SF-FFQ4PolishChildren) in Polish Children and Adolescents

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