Effectiveness of the “Increase Healthy People” Operational Model Among the Working-Age Population in Maha Sarakham Province

Abstract

Purposes : To evaluate the effectiveness of the “Increase Healthy People” operational model in Maha Sarakham Province.

Research design: Quasi Experimental research.

Materials and Methods : This study focuses on the application of the “Increase Healthy People” operational model. The sample group consists of 1,559 working-age individuals. Health data was collected through body composition measurements, risk assessments, and behavior modification according to individual risk profiles. The program's effectiveness was evaluated after 6 months by comparing the results before and after the intervention. The tools used in this study include health records, body composition measurement devices, and quantitative data analysis methods. Data was analyzed using frequency distribution, percentage, mean, and standard deviation. The McNemar test was employed to compare proportions before and after the implementation.

Main finding : A total of 1,559 participants received health behavior modification as part of the “Increase Healthy People” operational model. The majority of the participants were female (70.6%), aged 50-59 years (37.3%), and were primarily community or local leaders (41.5%). A comparison of health conditions before and after the implementation revealed statistically significant improvements in body mass index (BMI), waist circumference, muscle mass, and body fat levels (p<.001, p=.018, p <.001, p <.001, respectively). Specifically, the proportion of participants with a normal BMI increased from 35.8% before the intervention to 38.2% after; normal waist circumference rose from 47.1% to 48.8%; normal muscle mass improved from 88.9% to 93.5%; and normal body fat levels increased from 76.2% to 78.1%.

Conclusion and Recommendations : The operational model for increasing the number of healthy people in Maha Sarakham Province serves as an effective incentive for promoting changes in health behaviors based on individual risk profiles. By providing personalized feedback and information, the model helps create knowledge that encourages appropriate health behavior changes at the individual level.