Objective:Sick building syndrome(SBS)is a significant health concern among healthcare workers,exacerbated by prolonged exposure to indoor air pollutants and inadequate environmental conditions.Our study aims to explore the prevalence of SBS and its association with indoor air quality and workplace environments among healthcare workers in five hospital departments in Nakhon Si Thammarat,Thailand.Methods:Indoor air quality was assessed over eight days,measuring microbial concentrations(bacteria,fungi),temperature,humidity,and carbon dioxide levels.Demographic data and SBS symptoms were also collected from healthcare workers.Results:The findings revealed that fungal concentrations were highest in the pharmacy(51.95±37.59)colony forming units(CFU)per m3,while bacterial concentrations peaked in the outpatient department(265.06±49.46)CFU/m3.The study identified Staphylococcus hominis and Micrococcus luteus as the dominant microbial species in the air environment.A moderate positive correlation was found between bacterial concentra-tions and humidity(r=0.43,P=0.046).SBS symptoms were prevalent among healthcare workers,with 75.58％reporting issues like dry eyes and fatigue.The total complaint score for SBS correlated positively with indoor pol-lutant levels,especially fungi(r=0.38,P＜0.001).Frequent cleaning reduced SBS complaints significantly(P＜0.001).Conclusion:Hospital departments with more frequent cleaning practices exhibited lower SBS complaints,high-lighting the importance of cleaning frequency in reducing SBS-related issues.These findings provide actionable insights for improving workplace safety and indoor air quality in healthcare settings.

Objective:Sick building syndrome(SBS)is a significant health concern among healthcare workers,exacerbated by prolonged exposure to indoor air pollutants and inadequate environmental conditions.Our study aims to explore the prevalence of SBS and its association with indoor air quality and workplace environments among healthcare workers in five hospital departments in Nakhon Si Thammarat,Thailand.Methods:Indoor air quality was assessed over eight days,measuring microbial concentrations(bacteria,fungi),temperature,humidity,and carbon dioxide levels.Demographic data and SBS symptoms were also collected from healthcare workers.Results:The findings revealed that fungal concentrations were highest in the pharmacy(51.95±37.59)colony forming units(CFU)per m3,while bacterial concentrations peaked in the outpatient department(265.06±49.46)CFU/m3.The study identified Staphylococcus hominis and Micrococcus luteus as the dominant microbial species in the air environment.A moderate positive correlation was found between bacterial concentra-tions and humidity(r=0.43,P=0.046).SBS symptoms were prevalent among healthcare workers,with 75.58％reporting issues like dry eyes and fatigue.The total complaint score for SBS correlated positively with indoor pol-lutant levels,especially fungi(r=0.38,P＜0.001).Frequent cleaning reduced SBS complaints significantly(P＜0.001).Conclusion:Hospital departments with more frequent cleaning practices exhibited lower SBS complaints,high-lighting the importance of cleaning frequency in reducing SBS-related issues.These findings provide actionable insights for improving workplace safety and indoor air quality in healthcare settings.

Introduction: Dengue fever (DF) is a prominent vector-borne disease spread by mosquitos of the Aedes genus (mainly Aedes aegypti, and even Aedes albopictus), a tropical regions vector. The purpose of this research was to establish the spatial and temporal distribution patterns of DF cases in the study area between 2010 and 2020. Methods: The correlation between the Kuantan sub-district and dengue haemorrhagic fever (DHF) incidence is examined in this study using spatial analysis. The correlation was calculated using spatial autocorrelation, Moran’s Index (Moran’s I) and Spatial Autocorrelation of Local Indicators (LISA). Moran’s index is a worldwide indicator used to determine whether or not disease transmission has geographical autocorrelation in disease transmission. Results: The results indicated that between 2011 and 2020, the monthly Moran’s I of dengue transmission in Kuantan was estimated to range between -0.685 and 0.338. The lowest reading of Moran’s index was -0.685 in May 2015, whereas the highest reading was 0.338 in May 2019. This reflects the strong spatial autocorrelation of dengue transmission in Kuantan over the last decade. The LISA analysis revealed significant spatial autocorrelations on DF cases in Kuantan for three (3) out of six (6) sub-districts (50%) with a significance level of 2%. This suggests that there are spatial autocorrelations in Kuala Kuantan, Beserah and Penor sub-district that influence the distribution of DHF transmission. Conclusion: The results reveal that the spatial autocorrelation analysis method can be a tool for relevant researchers to understand the pattern of DF transmission study and establish the direction for further study.