Socio-economic and environmental factors are related to acute exacerbation of chronic obstructive pulmonary disease incidence in Thailand
| Autor: | Phuricha Phacharathonphakul, Kittipong Sornlorm |
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| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | Geospatial Health, Vol 19, Iss 2 (2024) |
| Druh dokumentu: | article |
| ISSN: | 1827-1987 1970-7096 |
| DOI: | 10.4081/gh.2024.1300 |
| Popis: | Chronic Obstructive Pulmonary Disease (COPD) is a significant global health issue, leading to high rates of sickness and death worldwide. In Thailand, there are over 3 million patients with the COPD, with more than a million patients admitted to hospitals due to symptoms of the disease. This study investigated factors influencing the incidence of acute exacerbations among COPD patients in Thailand, including the spatial autocorrelation between socioeconomic and environmental factors. We conducted a spatial analysis using Moran’s I, Local Indicators Of Spatial Association (LISA), and spatial regression models, specifically the Spatial Lag Model (SLM) and the Spatial Error Model (SEM), to explore the relationships between the variables. The univariate Moran’s I scatter plots showed a significant positive spatial autocorrelation of 0.606 in the incidence rate of COPD among individuals aged 15 years and older across all 77 provinces in Thailand. High-High (HH) clusters for the COPD were observed in the northern and southern regions, while Low-Low (LL) clusters were observed in the northern and north-eastern regions. Bivariate Moran’s I indicated a spatial autocorrelation between various factors and acute exacerbation of COPD in Thailand. LISA analysis revealed 4 HH clusters and 5 LL clusters related to average income, 12 HH and 8 LL clusters in areas where many people smoke, 5 HH and 8 LL clusters in areas with industrial factory activities, 11 HH and 9 LL clusters associated with forested areas, and 6 LL clusters associated with the average rice field. Based on the Akaike information criterion (AIC). The SLM outperformed the SEM but only slightly so, with an AIC value of 1014.29 compared to 1019.56 and a Lagrange multiplier value of p |
| Databáze: | Directory of Open Access Journals |
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