Abstract
Abstract
Background
Thailand has experienced major shifts in food consumption patterns due to rapid socioeconomic development, urbanization, and globalization, with implications for population nutrition. However, empirical evidence on long-term patterns from survey data is scarce.
Methods
We analyzed nationally representative household expenditure data on 13 food groups from the Annual Household Socio-Economic Survey (HSES) for 19 waves from 2000-2021, with three waves (2011, 2015, 2019) also including granular data on 257 individual foods. HDDI was calculated at the household level as the count of distinct food groups consumed, based on expenditure data, and to evaluate the nutritional significance of the patterns, HDDI was also correlated with pattern adherence. To all 13 food groups and 257 individual foods, we applied principal component analysis to derive household “food consumption” and “food composition” patterns (FCPs and FCoPs, based on daily expenditures and proportions of total household expenditures, respectively). Patterns were grouped into five diets and mapped to explore spatiotemporal differences and trends. Generalized linear model (GLM) regression was used to identify associations between patterns and household demographics and socioeconomics.
Results
Analysis of 13 major food groups from 2000 to 2021 identified four main diet categories for FCPs and FCoPs: Traditional Thai meals, mixed/diversified diets, convenience/prepared foods, and alcohol/lifestyle-related diets. In a detailed analysis of 257 individual foods, five major diets were recognized: four remained consistent from 2000 to 2021, and a fifth was a meat-dominant diet that grouped all patterns with high loadings for meats, specifically red meat. Traditional Thai/home-cooked patterns remained prevalent in rural households and in the Northern and Northeastern regions, though they are gradually declining. Mixed/diversified diets were more common in urban areas, especially in the Bangkok Metropolitan Region (BMR), but adherence decreased in other regions. Consumption of convenience and prepared foods increased over time as urbanization and changing lifestyles progressed. Alcohol/lifestyle-related diets showed lower adherence, whereas meat-dominant diets were more prevalent in the Northern and Northeastern regions. HDDI was positively correlated with traditional and mixed diets but only weakly or negatively associated with convenience-based dietary patterns.
Conclusions
Results reveal persisting consumption of traditional foods in Thai rural and low-income households, while urbanites increasingly consume mixed and convenience diets. Growing reliance on prepared foods and generational and regional differences in alcohol consumption patterns have important implications for public health and policy.