Background: Ultra-processed foods (UPF) are associated with adverse health outcomes. This study aimed to analyse the national trends in retail sales, consumer expenditure and nutritional quality of UPFs in Thailand.
Methods: The study used data from the Euromonitor Passport database for analysis of retail sales and consumer expenditure, and from the Mintel Global New Products Database for nutritional analysis using the WHO Southeast Asian Region nutrient profile model.
Front Nutr
May 2023
Introduction: This study aimed to assess the nutritional quality of food and beverage products in Thailand by comparing four different food classification systems: the nutrient profiling-based food classification systems by the Department of Health (DOH), the WHO South-East Asia Region (WHO SEA), the Healthier Choice Logo (HCL), and the food-processing-based food classification system, NOVA.
Methods: This study used secondary data from the Mintel Global New Products Database ( = 17,414). Food subgroups were classified differently based on these four systems.
This study aimed to generate sex-specific percentile curves for the percentage of body fat (PBF) in Thai children using a bioelectrical impedance analysis (BIA). The secondary objective of this study was to determine the association between body fat and other anthropometric measurements. A cross-sectional study was conducted on 3455 Thai school children aged 6-18 years.
View Article and Find Full Text PDFObjectives: To study the prevalence of anemia among healthy infants, and outcomes of giving a therapeutic trial of iron to anemic infants in thalassemia-endemic area.
Methods: A cross sectional study was conducted in 6-9-month-old, full-term healthy infants who attended the well child clinics at 2 tertiary care centers in southern Thailand. Complete blood count and serum ferritin were performed in every infant, and hemoglobin typing was performed only in anemic cases.
We estimate and forecast childhood obesity by age, sex, region, and urban-rural residence in Thailand, using a Bayesian approach to combining multiple source of information. Our main sources of information are survey data and administrative data, but we also make use of informative prior distributions based on international estimates of obesity trends and on expectations about smoothness. Although the final model is complex, the difficulty of building and understanding the model is reduced by the fact that it is composed of many smaller submodels.
View Article and Find Full Text PDF