Health literacy and high blood pressure among Myanmar migrant workers in Northeastern Thailand.

Hypertension, related to serious consequences unless diagnosed and treated, is a global concern, also affecting migrant workers. Due to the high prevalence of hypertension among migrant workers in Thailand, the influences of health literacy and other factors on blood pressure were needed to explore among Myanmar migrant workers in Northeastern Thailand. Hence, this study aimed to identify the prevalence of high blood pressure (HBP), its association with health literacy and other factors among Myanmar migrant workers in Northeastern Thailand. A cross-sectional analytical study was conducted in Northeastern Thailand. A multistage sampling procedure was applied. Data was gathered through interviews utilizing validated and reliable structured questionnaire. Descriptive statistics and inferential statistics with multiple logistic regression were used. Among 406 participants, about 60% were male and about 70% of them were married. The prevalence of overall HBP was 63.3% (95% CI: 58.49-67.86), 52% in females and 71.86% in males. Participants with limited health literacy were 79% more likely to have HBP than those with excellent and adequate health literacy (AOR = 1.79, 95% CI: 1.13-2.84). Other factors substantially linked with having HBP were being male gender (AOR = 4.68, 95% CI: 2.81-7.78), being overweight (AOR = 2.23, 95% CI: 1.18-4.23), being obese (AOR = 5.69, 95% CI: 2.96-10.96), not having health insurance (AOR = 2.01, 95% CI: 1.11-3.66), staying in Thailand for more than 48 months (AOR = 2.4, 95% CI: 1.48-3.9), and having family history of hypertension (AOR = 2.07, 95% CI: 1.28-3.35). In conclusion, more than half of Myanmar migrant workers had HBP. Factors associated with HBP were limited health literacy, male gender, overnutrition, lack of health insurance, longer duration of stay in Thailand and having family history of hypertension. Therefore, there is a need for a multifaceted strategy to prevent hypertension and its consequences by promoting health literacy as well as by enhancing good behavioural practice among this community.

Spatial associations between chronic kidney disease and socio-economic factors in Thailand.

Chronic kidney disease (CKD) is a persistent, progressive condition characterized by gradual decline of kidney functions leading to a range of health issues. This research used recent data from the Ministry of Public Health in Thailand and applied spatial regression and local indicators of spatial association (LISA) to examine the spatial associations with night-time light, Internet access and the local number of health personnel per population. Univariate Moran's I scatter plot for CKD in Thailand's provinces revealed a significant positive spatial autocorrelation with a value of 0.393. High-High (HH) CKD clusters were found to be predominantly located in the North, with Low-Low (LL) ones in the South. The LISA analysis identified one HH and one LL with regard to Internet access, 15 HH and five LL clusters related to night-time light and eight HH and five LL clusters associated with the number of health personnel in the area. Spatial regression unveiled significant and meaningful connections between various factors and CKD in Thailand. Night-time light displayed a positive association with CKD in both the spatial error model (SEM) and the spatial lag model (SLM), with coefficients of 3.356 and 2.999, respectively. Conversely, Internet access exhibited corresponding negative CKD associations with a SEM coefficient of - 0.035 and a SLM one of -0.039. Similarly, the health staff/population ratio also demonstrated negative associations with SEM and SLM, with coefficients of -0.033 and -0.068, respectively. SEM emerged as the most suitable spatial regression model with 54.8% according to R2. Also, the Akaike information criterion (AIC) test indicated a better performance for this model, resulting in 697.148 and 698.198 for SEM and SLM, respectively. These findings emphasize the complex interconnection between factors contributing to the prevalence of CKD in Thailand and suggest that socioeconomic and health service factors are significant contributing factors. Addressing this issue will necessitate concentrated efforts to enhance access to health services, especially in urban areas experiencing rapid economic growth.

Safely managed sanitation practice and childhood stunting among under five years old children in Myanmar.

In 2020, 149 million children under the age of five were estimated to be stunted globally. Around half of deaths among children under 5 years of age are related to under-nutrition. Objective of this study is to determine the association between safely managed sanitation and childhood stunting among under-five years old children in Myanmar. This cross-sectional analytical study was conducted in 16 townships across three regions and five states in Myanmar. Multiple logistic regressions analysis was performed to determine the associations. This study found that 327 (27.09%) under-five children were stunted among a total of 1207 children in Myanmar. Children with unsafely managed sanitation were 2.88 times more likely to be stunting compared with children who access to safely managed sanitation services (AOR = 2.88, 95% CI: 2.16 to 3.85; p-value <0.01). Other associated factors for childhood stunting were needs 1-15 minutes for water collection (AOR = 2.07, 95% CI: 1.46 to 2.94; p-value <0.01), 15-60 minutes for water collection times (AOR = 1.55, 95% CI: 1.08 to 2.23; p-value 0.02), improper waste water disposal (AOR = 1.99, 95% CI: 1.47 to 2.70; p-value <0.01), boys children (AOR = 4.49, 95% CI: 3.30 to 6.12; p-value <0.01), did not take vitamin A supplements(AOR = 1.64, 95% CI: 1.22 to 2.20; p-value <0.01), mothers height shorter than 153.4cm (AOR = 1.94, 95% CI: 1.45 to 2.58; p-value <0.01), and the lower minimal diet diversity (AOR = 1.47, 95% CI: 1.08 to 2.01; p-value 0.02). More access to safely managed sanitation facilities, technical sharing for proper waste water disposal, promoting household water supply system, health promotion for children's diet eating pattern, and regular support for Vitamin A supplementation are critical to reduce childhood stunting among children under the age of five in Myanmar.

Spatial association and modelling of under-5 mortality in Thailand, 2020.

Under-5 mortality rate (U5MR) is a key indicator of child health and overall development. In Thailand, despite significant steps made in child health, disparities in U5MR persist across different provinces. We examined various socio-economic variables, health service availability and environmental factors impacting U5MR in Thailand to model their influences through spatial analysis. Global and Local Moran's I statistics for spatial autocorrelation of U5MR and its related factors were used on secondary data from the Ministry of Public Health, National Centers for Environmental Information, National Statistical Office, and the Office of the National Economic and Social Development Council in Thailand. The relationships between U5MR and these factors were modelled using ordinary least squares (OLS) estimation, spatial lag model (SLM) and spatial error model (SEM). There were significant spatial disparities in U5MR across Thailand. Factors such as low birth weight, unemployment rate, and proportion of land use for agricultural purposes exhibited significant positive spatial autocorrelation, directly influencing U5MR, while average years of education, community organizations, number of beds for inpatients per 1,000 population, and exclusive breastfeeding practices acted as protective factors against U5MR (R2 of SEM = 0.588).The findings underscore the need for comprehensive, multi-sectoral strategies to address the U5MR disparities in Thailand. Policy interventions should consider improving socioeconomic conditions, healthcare quality, health accessibility, and environmental health in high U5M areas. Overall, this study provides valuable insights into the spatial distribution of U5MR and its associated factors, which highlights the need for tailored and localized health policies and interventions.

Spatial association between socio-economic health service factors and sepsis mortality in Thailand.

Sepsis is a significant global health issue causing organ failure and high mortality. The number of sepsis cases has recently increased in Thailand making it crucial to comprehend the factors behind these infections. This study focuses on exploring the spatial autocorrelation between socio-economic factors and health service factors on the one hand and sepsis mortality on the other. We applied global Moran's I, local indicators of spatial association (LISA) and spatial regression to examine the relationship between these variables. Based on univariate Moran's I scatter plots, sepsis mortality in all 77 provinces in Thailand were shown to exhibit a positive spatial autocorrelation that reached a significant value (0.311). The hotspots/ high-high (HH) clusters of sepsis mortality were mostly located in the central region of the country, while the coldspots/low-low (LL) clusters were observed in the north-eastern region. Bivariate Moran's I indicated a spatial autocorrelation between various factors and sepsis mortality, while the LISA analysis revealed 7 HH clusters and 5 LL clusters associated with population density. Additionally, there were 6 HH and 4 LL clusters in areas with the lowest average temperature, 4 HH and 2 LL clusters in areas with the highest average temperature, 8 HH and 5 LL clusters associated with night-time light and 6 HH and 5 LL clusters associated with pharmacy density. The spatial regression models conducted in this study determined that the spatial error model (SEM) provided the best fit, while the parameter estimation results revealed that several factors, including population density, average lowest and highest temperature, night-time light and pharmacy density, were positively correlated with sepsis mortality. The coefficient of determination (R2) indicated that the SEM model explained 56.4% of the variation in sepsis mortality. Furthermore, based on the Akaike Information Index (AIC), the SEM model slightly outperformed the spatial lag model (SLM) with an AIC value of 518.1 compared to 520.

Spatial pattern and heterogeneity of chronic respiratory diseases and relationship to socio-demographic factors in Thailand in the period 2016 to 2019.

Chronic respiratory diseases (CRDs) constitute 4% of the global disease burden and cause 4 million deaths annually. This cross-sectional study used QGIS and GeoDa to explore the spatial pattern and heterogeneity of CRDs morbidity and spatial autocorrelation between socio-demographic factors and CRDs in Thailand from 2016 to 2019. We found an annual, positive, spatial autocorrelation (Moran's I >0.66, p<0.001) showing a strong clustered distribution. The local indicators of spatial association (LISA) identified hotspots mostly in the northern region, while coldspots were mostly seen in the central and north-eastern regions throughout the study period. Of the socio-demographic factors, the density of population, households, vehicles, factories and agricultural areas, correlated with the CRD morbidity rate, with statistically significant negative spatial autocorrelations and coldspots in the north-eastern and central areas (except for agricultural land) and two hotspots between farm household density and CRD in the southern region in 2019. This study identified vulnerable provinces with high risk of CRDs and can guide prioritization of resource allocation and provide target interventions for policy makers.

Spatial autocorrelation and heterogenicity of demographic and healthcare factors in the five waves of COVID-19 epidemic in Thailand.

A study of 2,569,617 Thailand citizens diagnosed with COVID-19 from January 2020 to March 2022 was conducted with the aim of identifying the spatial distribution pattern of incidence rate of COVID-19 during its five main waves in all 77 provinces of the country. Wave 4 had the highest incidence rate (9,007 cases per 100,000) followed by the Wave 5, with 8,460 cases per 100,000. We also determined the spatial autocorrelation between a set of five demographic and health care factors and the spread of the infection within the provinces using Local Indicators of Spatial Association (LISA) and univariate and bivariate analysis with Moran's I. The spatial autocorrelation between the variables examined and the incidence rates was particularly strong during the waves 3-5. All findings confirmed the existence of spatial autocorrelation and heterogenicity of COVID-19 with the distribution of cases with respect to one or several of the five factors examined. The study identified significant spatial autocorrelation with regard to the COVID-19 incidence rate with these variables in all five waves. Depending on which province that was investigated, strong spatial autocorrelation of the High-High pattern was observed in 3 to 9 clusters and of the Low-Low pattern in 4 to 17 clusters, whereas negative spatial autocorrelation was observed in 1 to 9 clusters of the High-Low pattern and in 1 to 6 clusters of Low-High pattern. These spatial data should support stakeholders and policymakers in their efforts to prevent, control, monitor and evaluate the multidimensional determinants of the COVID-19 pandemic.

COVID-19 Vaccine Acceptance and Its Determinants among Myanmar Migrant Workers in Southern Thailand.

Success in eradicating COVID-19 will rely on the rate of vaccination adoption worldwide. Vaccine acceptance among vulnerable groups is critical for preventing the spread of COVID-19 and decreasing unnecessary deaths. The purpose of this study was to report on the willingness to obtain COVID-19 immunization and the factors related to its acceptance among Myanmar migrant workers in southern Thailand. This cross-sectional study consisted of 301 samples collected between October and November 2021 and analyzed using multiple logistic regression. Thirty-nine percent of workers intended to receive the COVID-19 vaccine within a year. The following factors were associated with obtaining the COVID-19 vaccine: a high level of perception of COVID-19 (AOR = 5.43), income less than or equal to 10,000 baht/month (AOR = 6.98), financial status at a sufficient level (AOR = 7.79), wearing a face mask in the previous month almost all the time (AOR =4.26), maintaining 1-2 m of distance from anyone in the last month (AOR =2.51), and measuring temperature in the previous month (AOR = 5.24). High reluctance to accept the COVID-19 vaccine among Myanmar migrant workers can influence efforts to eliminate COVID-19. Collaboration with all stakeholders is critical to helping Myanmar workers understand COVID-19, social measures, and preventive beliefs to increase vaccine uptake.