Browsing by Subject "varallisuusindeksi"

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.