Browsing by Subject "pääkomponenttianalyysi"

Background: Obesity is increasing rapidly all over the world. Obesity is becoming more common even in very young children. It has been estimated that globally approximately twenty percent of children have problems with their weight. Studies that have examined the association between obesity and nutrition have typically been focused to single nutrients or food groups. The knowledge from dietary pattern analysis considers also the synergistic effect between different components in foods, thus giving more information about food behaviour and the effect of the whole diet. Childhood and youth are critical time in shaping food choices and food habits learned at a young age often follow to adulthood. It is important to recognize differences in food consumption between obese and normal weight children and adolescents. Analysing dietary patterns gives information about the whole diet and makes it possible to identify harmful eating habits. Goals: The purpose of this study was to identify differences in the diets of normal weight and obese Finnish adolescents. The main goal was to determine if the dietary patterns between obese and normal weight adolescents differ and to determine if the dietary patterns are related to obesity. The research also studied the correlation of lifestyle and socioeconomic factors to obesity and to dietary patterns. Subjects and methods: The subjects consist of two different groups; patients, who had been diagnosed with severe obesity before the age of seven (n=68) and controls whose weight had been normal in childhood (n=73). Subjects were 15- to 25-year old in the time of the study. The study design is a comparative study in a cross-sectional design. Subjects filled a research form that asked information about socioeconomic and lifestyle factors from subjects and their parents. A food frequency questionnaire was used to assess food consumption from the previous month. Principal component analysis was used to define major dietary patterns. Logistic regression and Spearman´s rank correlation (rs) was used to determine associations between dietary patterns and obesity. Associations between lifestyle and socioeconomic factors and obesity were assessed with Spearman´s rank correlation. Obesity was determined by using BMI classification, waist circumference and body fat percentage. Results: Two major dietary patterns were identified; health conscious pattern and snacking pattern. The dietary patterns between patients and controls differed in women, where controls more often followed the health conscious pattern (p=0,008). After adjusting for confounding factors, the health conscious pattern was inversely associated to overweight. Subjects who represented the highest tertile of the health conscious pattern had lower risk of overweight (OR=0,21, 95 % CI 0,06 - 0,76) and high body fat percentage (OR=0,16, 95 % CI 0,03 - 0,89) compared to subjects who represented the lowest tertile. The analysis was also done separately for men and women, but no association was found after adjusting for all confounding factors. A positive correlation was found between snacking pattern and BMI (rs=0,36, p=0,05) and waist circumference (rs=0,43, p=0,02) in men patients and a negative correlation was found between health conscious pattern and BMI in women patients (rs=-0,43, p=0,018). A positive correlation was found between patient BMI and mother´s BMI (rs=0,42, p=0,001) and waist circumference (rs=0,47, p<0,0001) and a negative correlation between patients BMI and mother´s education (rs=-0,34, p=0,02). Conclusions: The association between obesity and nutrition might be more complex in adolescents than in adults. A diet that includes fresh and cooked vegetables, fruits, berries, seeds, beans, fish, dairy products and whole grain products may be inversely associated to overweight and higher body fat percentage. A diet that includes lots of snacking products may be associated to obesity in men. In researches that study obesity in children or adolescents, results should be examined, if possible, separately for both sexes.

Background: In middle-income countries, such as Kenya there are signs of a nutrition transition towards a Western diet. From the public health perspective, it is important to understand the sociodemographic factors behind the whole diet. The nutrition research should therefore focus on the big picture of the diet rather than on the single nutrients. Dietary patterns can be used to explore the whole diet. With data-based dietary patterns, it is possible to investigate which food items are used or disused together. Based on previous studies, the differences in dietary patterns might be explained by sociodemographic factors. However, there are only few studies examining the association between sociodemographic factors and children’s dietary patterns in middle-income countries. Aims: The aim of the study was to investigate what kind of dietary patterns can be recognized among Kenyan children living in Nairobi. Additionally, this study aimed to investigate the association between sociodemographic factors (gender, education, wealth and living area) and dietary patterns. Materials and methods: The data used in this study is from the cross-sectional study of KENFIN-EDURA project. The data was collected with a food frequency questionnaire and background forms. 160 participants were recruited and 149 (93 %) of them completed the questionnaire. The participants were 914-year-olds, of whom 52 % were girls and 48 % were boys. Participants lived in Nairobi, either in a low-income area called Kayole or in a middle-income area called Langata. The participants reported the consumption frequencies of 174 food items, of which 39 were left out from the analyses. The food items that no one or only one person used were left out from the analyses. Also, the food items for which a big variance on reporting was suspected, were left out. The remaining 135 food items were collapsed into 19 food groups. Dietary patterns were formed with principal component analysis, and factor scores for participants for each dietary pattern were calculated. A higher value for factor score indicates a higher correlation between participant’s diet and dietary pattern. The mean factor scores were investigated by t-test for area and gender, and by analysis of variance for parent’s education and household’s wealth. The associations between sociodemographic factors and dietary patterns were examined by linear regression analysis. Finally, the examination was done separately for both areas. Results: Three dietary patterns were recognized, and these explained 36 % of the total variance in food consumption of the study population. The recognized dietary patterns were named based on food items loading most strongly in the patterns. The patterns were labelled 1) snacks, fast food and meat, 2) dairy products and plant protein, and 3) traditional Kenyan. Snacks, fast food and meat and traditional Kenyan dietary patterns were associated to living in Langata. The children from wealthier families scored higher on the dairy products and plant protein dietary pattern. When analyses were done separately for both areas, the only statistically significant result was the positive association between snacks, fast food and meat dietary pattern and wealth in Langata. Conclusions: Three dietary patterns were recognized among Nairobian children and two of these were similar to the patterns recognized in previous studies. One of them included energy-dense foods and meat, and the other plant-based products and dairy products. Living area and wealth appeared to be the most important sociodemographic factors associated with children’s diet. Nevertheless, the association between sociodemographic factors and children’s dietary patterns should be investigated more in order to reduce sociodemographic differences in diets.