Spatial association of socioeconomic and health service factors with antibiotic self-medication in Thailand

Antibiotic Self-Medication (ASM) is a major contributing factor to Antimicrobial Resistance (AMR) that can lead to both mortality and long-term hospitalizations. High provincial ASM proportions associated with mortality due to AMR have been observed in Thailand but there is a lack of studies on geographic factors contributing to ASM. The present study aimed to quantify the distribution of ASM in Thailand and its correlated factors. Socioeconomic and health services factors were included in the spatial analysis. Moran's I was performed to identify global autocorrelation with the significance level set at p=0.05 and spatial regression were applied to identify the factors associated with ASM, the proportion of which is predominant in the north-eastern, central and eastern regions with Phitsanulok Province reporting the highest proportion of Thailand's 77 provinces. Autocorrelation between Night-Time Light (NTL) and the proportion of ASM was observed to be statistically significant at p=0.030. The Spatial Lag Model (SLM) and the Spatial Error Model (SEM) were used with the latter providing both the lowest R2 and Akaike Information Criterion (AIC). It was demonstrated that the proportion of alcohol consumption significantly increased the proportion of ASM. The annual number of outpatient department visits and the average NTL decreased the proportion of ASM by 1.5% and 0.4%, respectively. Average monthly household expenditures also decreased the ASM proportion. Policies to control alcohol consumption while promoting healthcare visits are essential strategies to mitigate the burden of AMR in Thailand.

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Publication Details

Journal
Geospatial health
Published
2025-01-27
DOI
https://doi.org/10.4081/gh.2025.1329
Citations
1
Primary Topic
Antibiotic Use and Resistance
Type
article
Field-Weighted Citation Impact
1.26
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article

Spatial association of socioeconomic and health service factors with antibiotic self-medication in Thailand

Wongsa Laohasiriwong, Roshan Kumar Mahato, Kittipong Sornlorm, Worrayot Darasawang et al.
1 citations
Geospatial health
Antibiotic Use and Resistance
1.26
article

Spatial association of socioeconomic and health service factors with antibiotic self-medication in Thailand

Wongsa Laohasiriwong, Roshan Kumar Mahato, Kittipong Sornlorm, Worrayot Darasawang, Warangkana Sungsitthisawad
article en
1 citations

Abstract

Antibiotic Self-Medication (ASM) is a major contributing factor to Antimicrobial Resistance (AMR) that can lead to both mortality and long-term hospitalizations. High provincial ASM proportions associated with mortality due to AMR have been observed in Thailand but there is a lack of studies on geographic factors contributing to ASM. The present study aimed to quantify the distribution of ASM in Thailand and its correlated factors. Socioeconomic and health services factors were included in the spatial analysis. Moran's I was performed to identify global autocorrelation with the significance level set at p=0.05 and spatial regression were applied to identify the factors associated with ASM, the proportion of which is predominant in the north-eastern, central and eastern regions with Phitsanulok Province reporting the highest proportion of Thailand's 77 provinces. Autocorrelation between Night-Time Light (NTL) and the proportion of ASM was observed to be statistically significant at p=0.030. The Spatial Lag Model (SLM) and the Spatial Error Model (SEM) were used with the latter providing both the lowest R2 and Akaike Information Criterion (AIC). It was demonstrated that the proportion of alcohol consumption significantly increased the proportion of ASM. The annual number of outpatient department visits and the average NTL decreased the proportion of ASM by 1.5% and 0.4%, respectively. Average monthly household expenditures also decreased the ASM proportion. Policies to control alcohol consumption while promoting healthcare visits are essential strategies to mitigate the burden of AMR in Thailand.

Geospatial healthVol. 20(1)
Khon Kaen University (TH)
Good health and well-being
Openalex Percentile: Top 23%
Antibiotic Use and Resistance
1.26
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Spatial association of socioeconomic and health service factors with antibiotic self-medication in Thailand — Wongsa Laohasiriwong, Roshan Kumar Mahato, et al. · Geospatial health (2025) | TGRS Research Map | TGRS