Numerous studies have established a correlation between sociodemographic characteristics and water usage, identifying population as a primary independent variable in mid- to long-term demand forecasting. Recent dramatic sociodemographic changes, including urban concentration-rural depopulation, low birth rates-aging population, and the rise in single-person households, are expected to impact water demand and supply patterns. This underscores the necessity for operational and managerial changes in existing water supply systems. While sociodemographic characteristics are regularly surveyed, the conducted surveys use aggregate units that do not align with the actual system. Consequently, many water demand forecasts have been conducted at the administrative district level without adequately considering the water supply system. This study presents an upward water demand forecasting model that accurately reflects real water facilities and consumers. The model comprises three key steps. Firstly, Statistics Korea’s SGIS (Statistical Geological Information System) data was reorganized at the DMA level. Secondly, DMAs were classified using the SOM (Self-Organizing Map) algorithm to consider differences in water facilities and consumer characteristics. Lastly, water demand forecasting employed the PCR (Principal Component Regression) method to address multicollinearity and overfitting issues. The performance evaluation of this model was conducted for DMAs classified as rural areas due to the insufficient number of DMAs. The estimation results indicate that the correlation coefficients exceeded 0.9, and the MAPE remained within approximately 10% for the test dataset. This method is expected to be useful for reorganization plans, such as the expansion and contraction of existing facilities.

This study aims to explore the diverse characteristics of obese groups of Korean males in their 20’s to 40’s. A total of 201 males who each had a BMI (Body Mass Index) of 23 or over were recruited through a convenient sampling. Samples were categorized into groups of overweight, slightly obese, and severely obese, and submitted for data analysis. Results are summarized as follows. First, in terms of demographic characteristics, slightly and severely obese males were older than overweight males. There were also group differences in marital status and household income. Second, slightly and severely obese groups demonstrated a higher perception of obesity and a lower perception of health than did the overweight group. Third, there were no group differences in body satisfaction, socio-cultural attitudes toward appearance, and self-esteem. Based on these results, we concluded that overweight, slightly obese, and severely obese groups were distinguishable from each other in terms of their demographic characteristics, whereas the slightly obese group and the severely obese group were not different in terms of perception of obesity, perception of health, weight control behaviors, body satisfaction, body image, socio-cultural attitudes toward appearance, and self-esteem. These findings may reflect that people may not become increasingly sensitive to socio-psychological stimulations as they gain more weight if they have exceeded a certain level of obesity. This observation provides meaningful implications for the differences among obesity groups given the lack of prior research focusing on this issue.