Analyzing temperature, humidity, and precipitation trends in six regions of Thailand using innovative trend analysis.

The change of temperature and weather parameters is a major concern affecting sustainable development and impacting various sectors, such as agriculture, tourism, and industry. Changing weather patterns and their impact on water resources are important climatic factors that society is facing. In Thailand, climatological features such as ambient temperature, relative humidity, and precipitation play a substantial role in affecting extreme weather events, which cause damage to the economy, agriculture, tourism, and livelihood of people. To investigate recent serious changes in annual trends of temperature, relative humidity, and precipitation in Thailand, this study used the Mann-Kendall (MK) test and innovative trend analysis (ITA) methods. The MK test showed that all six regions had an upward trend in temperature and humidity index (humidex, how hot the weather feels to the average person), while relative humidity and precipitation showed both upward and downward trends across different regions. The ITA method further confirmed the upward trend in temperature and humidex and showed that most data points fell above the 1:1 line. However, the upward trend in most variables was not significant at the 5% level. The southern and eastern regions showed a significant upward trend in relative humidity and humidex at a 5% level of significance according to the MK test. The output of this study can help in the understanding of weather variations and predict future situations and can be used for adaptation strategies.

Association of cause-specific hospital admissions with high and low temperatures in Thailand: a nationwide time series study.

Background: Non-optimum temperatures are associated with a considerable mortality burden. However, evidence of temperature with all-cause and cause-specific hospital admissions in tropical countries like Thailand is still limited. Methods: Daily all-cause and cause-specific hospital admissions for outpatient and inpatient visits were collected from 77 provinces in Thailand from January 2013 to August 2019. A two-stage time-series approach was applied to assess the association between non-optimum temperatures and hospital admission. We first fitted the province-specific temperature-morbidity association and then obtained the national association in the second stage using a random-effects meta-analysis regression. The attributable fraction (AF) of hospital admissions with 95% empirical confidence interval (eCI) was calculated. Findings: A total of 878,513,460 all-cause outpatient admissions and 32,616,600 all-cause inpatient admissions were included in this study. We observed a J-shaped relationship with the risk of hospital admissions increasing for both cold and hot temperatures. The overall AFs of all-cause hospital admissions due to non-optimum temperatures were 7.57% (95% eCI: 6.47%, 8.39%) for outpatient visits and 6.17% (95% eCI: 4.88%, 7.20%) for inpatient visits. Hot temperatures were responsible for most of the AFs of hospital admissions, with 6.71% (95% eCI: 5.80%, 7.41%) for outpatient visits and 4.50% (95% eCI: 3.62%, 5.19%) for inpatient visits. The burden of hospital admissions was greater in females and in children and adolescents (0-19 years). The fractions of hospital admissions attributable to non-optimum temperatures exhibited variation among disease categories and geographical areas. Interpretation: The results indicate that low and high temperature has a significant impact on hospital admissions, especially among the females, and children and adolescents (0-19 years). The current investigation could provide evidence for policymakers to develop adaptation strategies and mitigate the adverse effects of climate change on public health in Thailand and other tropical countries. Funding: National Research Council of Thailand (NRCT): E-Asia Joint Research Program: Climate change impact on natural and human systems (N33A650979).

Occurrence, distribution, and ecological risk assessment of heavy metals in Chao Phraya River, Thailand.

Understanding heavy metals in rivers is crucial, as their presence and distribution impact water quality, ecosystem health, and human well-being. This study examined the presence and levels of nine heavy metals (Cd, Cr, Cu, Fe, Hg, Mn, Ni, Pb, and Zn) in 16 surface water samples along the Chao Phraya River, identifying Fe, Mn, Zn, and Cr as predominant metals. Although average concentrations in both rainy and dry seasons generally adhered to WHO guidelines, Mn exceeded these limits yet remained within Thailand's acceptable standards. Seasonal variations were observed in the Chao Phraya River, and Spearman's correlation coefficient analysis established significant associations between season and concentrations of heavy metals. The water quality index (WQI) demonstrated varied water quality statuses at each sampling point along the Chao Phraya River, indicating poor conditions during the rainy season, further deteriorating to very poor conditions in the dry season. The hazard potential index (HPI) was employed to assess heavy metal contamination, revealing that during the dry season in the estuary area, the HPI value exceeded the critical threshold index, indicating the presence of heavy metal pollution in the water and unsuitable for consumption. Using the species sensitivity distribution model, an ecological risk assessment ranked the heavy metals' HC5 values as Pb > Zn > Cr > Cu > Hg > Cd > Ni, identifying nickel as the most detrimental and lead as the least toxic. Despite Cr and Zn showing a moderate risk, and Cu and Ni posing a high risk to aquatic organisms, the main contributors to ecological risk were identified as Cu, Ni, and Zn, suggesting a significant potential ecological risk in the Chao Phraya River's surface water. The results of this study provide fundamental insights that can direct future actions in preventing and managing heavy metal pollution in the river ecosystem.

The association of meteorological parameters and AirQ+ health risk assessment of PM2.5 in Ratchaburi province, Thailand.

Air quality is heavily influenced by rising pollution distribution levels which are a consequence of many artificial activities from numerous sources. This study aims to determine the relationship between meteorological data and air pollutants. The health effects of long-term PM2.5 were estimated on expected life remaining (ELR) and years of life lost (YLL) indices in Ratchaburi province during the years 2015-2019 using AirQ+ software. Values obtained from the PM2.5 averaging, and YLL data were processed for the whole population in the age range of 0-29, 30-60 and over 60. These values were entered into AirQ+ software. The mean annual concentration of PM2.5 was highly variable, with the highest concentration being 136.42 µg/m3 and the lowest being 2.33 µg/m3. The results estimated that the highest and lowest YLL in the next 10 years for all age groups would be 24,970.60 and 11,484.50 in 2017 and 2019, respectively. The number of deaths due to COPD, IHD, and stroke related to long-term exposure to ambient PM2.5 were 125, 27 and 26, respectively. The results showed that older people (> 64) had a higher YLL index than the groups aged under 64 years. The highest and lowest values for all ages were 307.15 (2015) and 159 (2017). Thus, this study demonstrated that the PM2.5 effect to all age groups, especially the the elderly people, which the policy level should be awared and fomulated the stratergies to protecting the sensitive group.

Biomarker-Determined Nonylphenol Exposure and Associated Risks in Children of Thailand, Indonesia, and Saudi Arabia.

Nonylphenol (NP) is an endocrine disruptor and environmental contaminant. Yet, data on individual body burdens and potential health risks in humans, especially among children, are scarce. We analyzed two specific urinary NP metabolites, hydroxy-NP (OH-NP) and oxo-NP. In contrast to parent NP, OH-NP has a much higher urinary excretion fraction (Fue), and both are insusceptible to external contamination. We investigated spot urine samples from school children of Thailand (n = 104), Indonesia (n = 89), and Saudi Arabia (n = 108) and could quantify OH-NP in 100% of Indonesian and Saudi children (median concentrations: 8.12 and 8.57 µg/L) and in 76% of Thai children (1.07 µg/L). Median oxo-NP concentrations were 0.95, 1.10, and <0.25 µg/L, respectively, in line with its lower Fue. Median daily NP intakes (DIs), back-calculated from urinary OH-NP concentrations, were significantly higher in Indonesia and Saudi Arabia [0.47 and 0.36 µg/(kg bw·d), respectively] than in Thailand [0.06 µg/(kg bw·d)]. Maximum DIs were close to the preliminary tolerable DI of 5 µg/(kg bw·d) from the Danish Environmental Protection Agency. Dominant sources of exposure or relevant exposure pathways could not be readily identified by questionnaire analyses and also potentially varied by region. The novel biomarkers provide long-needed support to the quantitative exposure and risk assessment of NP.

The Elemental Characteristics and Human Health Risk of PM2.5 during Haze Episode and Non-Haze Episode in Chiang Rai Province, Thailand.

Fine particle matter (PM2.5) was directly related to seasonal weather, and has become the influencing factor of air quality that is harmful for human health in Chiang Rai province. The aims were determining the elemental composition in PM2.5 and human health risk in haze (March 2021) and non-haze episodes (July-August 2021). Nine elements in PM2.5 were measured by using an Atomic Absorption Spectrophotometer, and an enrichment factor was used to identify the emission source. The results showed that the average concentration of PM2.5 was 63.07 µg/m3 in haze episodes, and 25.00 µg/m3 in a non-haze episode. The maximum concentration was 116.7 µg/m3 in March. The majority of elements originated from anthropogenic sources. In haze episodes, PM2.5 mean concentration was approximately 4.2 times that of the WHO guidelines (15 µg/m3 24 h), and 1.3 times that of the Thai Ambient Air Quality Standard (50 µg/m3). The analysis of backward air mass trajectory showed that transboundary and local sources significantly influenced PM2.5 at the monitoring site in the sampling period. In the health risk assessment, the non-carcinogenic risk of Cd was the highest, with a Hazard Quotient (HQ) of 0.048, and the cancer risk of Cr was classified as the highest cancer risk, with the values of 1.29 × 10-5, higher than the minimum acceptable level.

Characteristics of Gases Emitted from Chicken Manure Wastewater and Potential Effects on Human Health.

Hazardous and odorous gas emissions from chicken manure wastewater are a public preoccupation. Odor composition measurements are crucial steps to provide appropriate air pollution control measures and design strategies to minimize the human health impact. In this study, chicken manure wastewater samples were extensively analyzed in a closed system by a portable handheld gas detector to characterize the odor and chemical compositions. A portable detector was calibrated prior to sampling. The total number of 153 chemical compounds found in the chicken manure wastewater samples had various olfactory characteristics, including strong, pleasant, and odorless smells. Depending on the route of exposure, most of these chemical compounds could cause human health effects, such as irritation, burns, and severe symptoms including carcinogenic.

Research Priorities of Applying Low-Cost PM2.5 Sensors in Southeast Asian Countries.

The low-cost and easy-to-use nature of rapidly developed PM2.5 sensors provide an opportunity to bring breakthroughs in PM2.5 research to resource-limited countries in Southeast Asia (SEA). This review provides an evaluation of the currently available literature and identifies research priorities in applying low-cost sensors (LCS) in PM2.5 environmental and health research in SEA. The research priority is an outcome of a series of participatory workshops under the umbrella of the International Global Atmospheric Chemistry Project-Monsoon Asia and Oceania Networking Group (IGAC-MANGO). A literature review and research prioritization are conducted with a transdisciplinary perspective of providing useful scientific evidence in assisting authorities in formulating targeted strategies to reduce severe PM2.5 pollution and health risks in this region. The PM2.5 research gaps that could be filled by LCS application are identified in five categories: source evaluation, especially for the distinctive sources in the SEA countries; hot spot investigation; peak exposure assessment; exposure-health evaluation on acute health impacts; and short-term standards. The affordability of LCS, methodology transferability, international collaboration, and stakeholder engagement are keys to success in such transdisciplinary PM2.5 research. Unique contributions to the international science community and challenges with LCS application in PM2.5 research in SEA are also discussed.

Influencing factors of COVID-19 spreading: a case study of Thailand.

Aim: A novel corona virus disease 2019 (COVID-19) was declared as pandemic by WHO as global level and local levels in many countries. The movement of people might be one influencing factor, this paper aims to report the situation COVID-19 and spreading in Thailand, including influencing factors of spreading and control. Subject and method: Infected, confirmed COVID-19 data were obtained from the official website of the Department of Disease Control, Ministry of Public Health. Tourist data was downloaded from Ministry of Tourism and Sports. Researchers analyzed the situation from the first found case in Thailand until 15 April 2020 with the timeline of important influencing factors. Correlation coefficients of tourist data and infected case was calculated by person correlation coefficient. Results: The number of infected cases was significant associated (correlation coefficient > 0.7) with economic factor, namely; number of visitors, generated income from both Thai and foreigner tourist (p value <0.01). The influencing factors of slow increased rate were the enforcement and implementation of both central and local government regulation, the strength of the Thai health care system, the culture and social relation, the partnership among various governmental and private sectors. Conclusion: We found that the number of tourist and their activities were significant associated with number of infected, confirmed COVID-19 cases. The public education and social supporting were the key roles for regulation enforcement and implementation.

Association of climate factors and air pollutants with pneumonia incidence in Lampang province, Thailand: findings from a 12-year longitudinal study.

This study attempted to understand the associations between pneumonia, climate, and environmental air pollutants in Thailand. A 12-year longitudinal study was performed between 2003 and 2014 in Lampang province, the Northern region of Thailand. Spearman correlation and negative binomial regression modelling were used to explore the relationships between climate factors and environmental air pollutants and pneumonia incidence. Spearman correlation shows that pneumonia incidence was positively correlated with humidity and negatively correlated with temperature, NO2, and O3. The regression modelling produced a series of models to predict pneumonia incidence based on information on climate and air quality. The result of the models shows that humidity and PM10 were associated with pneumonia incidence. To better protect the health, public health policy and risk assessment approach for pneumonia incidence should include considerations of the effect of air pollution. This result can be used for further intervention to take care of human health.

Children's exposures to boron and biocides from slime products in Asian regions.

BACKGROUND: Chemical exposure from slime toys can cause potential health effects. Although slime toys are popular in Asia, the regulation of boron, chloromethylisothiazolinone (CMIT), and methylisothiazolinone (MIT) in these toys has been implemented only in Korea. OBJECTIVE: In this study, we investigated boron migration levels and CMIT and MIT concentrations in 127 slime products from Asian cities and estimated children's exposure to boron and the biocides in Korea. METHODS: Slime boron migration levels were analyzed by inductively coupled plasma optical emission spectrometry (ICP-OES), according to Part 3 of the European Standard on the safety of toys (EN 71-3:2013). CMIT and MIT concentrations were analyzed using liquid chromatography tandem mass spectrometry (LC-MS/MS). Exposure doses of boron, CMIT, and MIT were calculated using the exposure pattern of children slime users in Korea. RESULTS: Average boron migration levels of the slime products in Seoul, Bangkok, Hong Kong, Taipei, and Yokohama were 691.9, 851.1, 806.6, 509.0, and 956.2 mg/kg, respectively. Of the 127 slime products tested, 70.1% exceeded the EU boron migration limit of 300 mg/kg for toys made with sticky material. Boron migration levels in slime products in Korea did not differ significantly by manufacturing date, although the Korean boron regulations were enacted in January 2019. CMIT and MIT were detected from 51.2% and 36.2% of all products, respectively, and tended to be detected simultaneously. Exposure doses of boron, CMIT, and MIT were highest among infants. SIGNIFICANCE: Oral exposure was the most important for boron exposure. It is necessary to manage boron level in slime products and minimize exposure from hand to mouth action in infants.

Urinary Concentrations of Major Phthalate and Alternative Plasticizer Metabolites in Children of Thailand, Indonesia, and Saudi Arabia, and Associated Risks.

Phthalates are widely used in consumer products and are well-known for adverse endocrine outcomes. Di-(2-ethylhexyl) phthalate (DEHP), one of the most extensively used phthalates, has been rapidly substituted with alternative plasticizers in many consumer products. The aim of this study was to assess urinary phthalate and alternative plasticizer exposure and associated risks in children of three Asian countries with different geographical, climate, and cultural characteristics. Children were recruited from elementary schools of Saudi Arabia (n = 109), Thailand (n = 104), and Indonesia (n = 89) in 2017-2018, and their urine samples were collected. Metabolites of major phthalates and alternative plasticizers were measured in the urine samples by HPLC-MS/MS. Urinary metabolite levels differed substantially between the three countries. Metabolite levels of diisononyl phthalate (DiNP), diisodecyl phthalate (DiDP), di(2-ethylhexyl) terephthalate (DEHTP), and 1,2-cyclohexane dicarboxylic acid diisononyl ester (DINCH) were the highest in Saudi children: Median urinary concentrations of oxo-MiNP, OH-MiDP, 5cx-MEPTP, and OH-MINCH were 8.3, 8.4, 128.0, and 2.9 ng/mL, respectively. Urinary DEHP metabolite concentrations were the highest in the Indonesian children. The hazard index (HI) derived for the plasticizers with antiandrogenicity based reference doses (RfDAA) was >1 in 86%, 80%, and 49% of the Saudi, Indonesian, and Thai children, respectively. DEHP was identified as a common major risk driver for the children of all three countries, followed by DnBP and DiBP depending on the country. Among alternative plasticizers, urinary DEHTP metabolites were detected at levels comparable to those of DEHP metabolites or higher among the Saudi children, and about 4% of the Saudi children exceeded the health based human biomonitoring (HBM)-I value. Priority plasticizers that were identified among the children of three countries warrant refined exposure assessment for source identification and relevant exposure reduction measures.

Particulate matter (PM10) prediction based on multiple linear regression: a case study in Chiang Rai Province, Thailand.

BACKGROUND: The northern regions of Thailand have been facing haze episodes and transboundary air pollution every year in which particulate matter, particularly PM10, accumulates in the air, detrimentally affecting human health. Chiang Rai province is one of the country's most popular tourist destinations as well as an important economic hub. This study aims to develop and compare the best-fitted model for PM10 prediction for different seasons using meteorological factors. METHOD: The air pollution and weather data acquired from the Pollution Control Department (PCD) spanned from the years 2011 until 2018 at two stations on an hourly basis. Four different stepwise Multiple Linear Regression (MLR) models for predicting the PM10 concentration were then developed, namely annual, summer, rainy, and winter seasons. RESULTS: The maximum daily PM10 concentration was observed in the summer season for both stations. The minimum daily concentration was detected in the rainy season. The seasonal variation of PM10 was significantly different for both stations. CO was moderately related to PM10 in the summer season. The PM10 summer model was the best MLR model to predict PM10 during haze episodes. In both stations, it revealed an R2 of 0.73 and 0.61 in stations 65 and 71, respectively. Relative humidity and atmospheric pressure display negative relationships, although temperature is positively correlated with PM10 concentrations in summer and rainy seasons. Whereas pressure plays a positive relationship with PM10 in the winter season. CONCLUSIONS: In conclusion, the MLR models are effective at estimating PM10 concentrations at the local level for each seasonal. The annual MLR model at both stations indicates a good prediction with an R2 of 0.61 and 0.52 for stations 65 and 73, respectively.

Influence of the meteorological conditions and some pollutants on PM10 concentrations in Lamphun, Thailand.

Particulate matter (PM) has been occurring regularly during the dry season in the upper north of Thailand including Lamphun Province that might be influenced by various factors including climatologic and other pollutants. This paper aims to investigate the climatologic and gaseous factors influencing the occurrence of PM10 concentration using Pollution Control Department (PCD) data. The secondary data of 2009 to 2017 obtained from the PCD was used for analysis. We used descriptive statistics, Pearson's correlation coefficient, multiple regression and graphic presentation using R program (R packages of 'open air' and 'ncdf4') and Microsoft Excel Spreadsheet®. In addition, the periodic measurement of PM2.5 and PM10 were investigated to determine the ratio of PM2.5/PM10. The results indicated that haze episodes (daily PM10 concentration always over the PCD standard) normally occur during the dry season from February to April. The maximum concentration was always found in March. The PM10 concentration was negatively associated with relative humidity and temperature while the PM10 concentration showed a strongly positive association with CO and NO2 concentration with correlation values of 0.70 and 0.57, respectively. Furthermore, we found CO and PM10 concentration was associated with ozone concentration. This finding will benefit local communities and the public health sector to provide a warning system for preparation and response plans to react to PM10 episodes in their responsible areas.

The Health Risks of Airborne Polycyclic Aromatic Hydrocarbons (PAHs): Upper North Thailand.

Every year, Northern Thailand faces haze pollution during the haze episode. The particulate matter (PM), including fine fraction (PM2.5), a coarse fraction (PM2.5-10), and 16 polycyclic aromatic hydrocarbons (PAHs), was measured in six provinces in upper north Thailand during the haze and non-haze episodes in 2018. Eighty-three percent of the PM2.5 measurements (21.8-194.0 µg/m3) during the haze episode exceeded the national ambient air quality standard in Thailand. All 16 PAHs were detected in the study area in both periods. The average concentration of total PAHs (particle-bound and gas-phase) during the haze episode was 134.7 ± 80.4 ng/m3, which was about 26 times higher than those in the non-haze (5.1 ± 9.7 µg/m3). Naphthalene and acenaphthene were the dominant PAHs in the gas phase; whereas, indeno[123-cd] pyrene, benzo[a]pyrene, and Benzo[ghi]Perylene were dominant in the particle-bound phase. The estimated inhalation excess cancer risk from PAHs exposure was 9.3 × 10-4 and 2.5 × 10-5 in the haze episode and non-haze, respectively. Diagnostic ratios and principal component analysis revealed that PAHs were derived from mixed sources of vehicle emission and solid combustion in the haze episode and vehicle emission in the non-haze period. High pollution levels of PM and large cancer risk attributable to the exposure of PAHs in the haze episode suggest urgent countermeasures to reduce the source emission, especially from the solid combustion in the area.

Non-linear effect of different humidity types on scrub typhus occurrence in endemic provinces, Thailand.

BACKGROUND: Reported monthly scrub typhus (ST) cases in Thailand has an increase in the number of cases during 2009-2014. Humidity is a crucial climatic factor for the survival of chiggers, which is the disease vectors. The present study was to determine the role of humidity in ST occurrence in Thailand and its delayed effect. METHODS: We obtained the climate data from the Department of Meteorology, the disease data from Ministry of Public Health. Negative binomial regression combined with a distributed lag non-linear model (NB-DLNM) was employed to determine the non-linear effects of different types of humidity on the disease. This model controlled overdispersion and confounder, including seasonality, minimum temperature, and cumulative total rainwater. RESULTS: The occurrence of the disease in the 6-year period showed the number of cases gradually increased summer season (Mid-February - Mid-May) and then reached a plateau during the rainy season (Mid-May - Mid-October) and then steep fall after the cold season (Mid-October - Mid-February). The high level (at 70%) of minimum relative humidity (RHmin) was associated with a 33% (RR 1.33, 95% CI 1.13-1.57) significant increase in the number of the disease; a high level (at 14 g/m3) of minimum absolute humidity (AHmin) was associated with a 30% (RR 1.30, 95% CI 1.14-1.48); a high level (at 1.4 g/kg) of minimum specific humidity (SHmin) was associated with a 28% (RR 1.28, 95% CI 1.04-1.57). The significant effects of these types of humidity occurred within the past month. CONCLUSION: Humidity played a significant role in enhancing ST cases in Thailand, particularly at a high level and usually occurred within the past month. NB-DLNM had good controlled for the overdispersion and provided the precise estimated relative risk of non-linear associations. Results from this study contributed the evidence to support the Ministry of Public Health on warning system which might be useful for public health intervention and preparation in Thailand.

Exposure to ambient particulate matter and biomass burning during pregnancy: associations with birth weight in Thailand.

BACKGROUND: There is a growing evidence that exposure to ambient particulate air pollution during pregnancy is associated with adverse birth outcomes, including reduced birth weight (BW). The objective of this study was to quantify associations between BW and exposure to particulate matter (PM) and biomass burning during pregnancy in Thailand. METHODS: We collected hourly ambient air pollutant data from ground-based monitors (PM with diameter of <10 µm [PM10], Ozone [O3], and nitrogen dioxide [NO2]), biomass burning from satellite remote sensing data, and individual birth weight data during 2015-2018. We performed a semi-ecological analysis to evaluate the association between mean trimester exposure to air pollutants and biomass burning with BW and low-birth weight (LBW) (<2500 g), adjusting for gestation age, sex, previous pregnancies, mother's age, heat index, season, year, gaseous pollutant concentrations, and province. We examined potential effect modification of PM10 and biomass burning exposures by sex. RESULTS: There were 83,931 eligible births with a mean pregnancy PM10 exposure of 39.7 µg/m3 (standard deviation [SD] = 7.7). The entire pregnancy exposure was associated with reduced BW both for PM10 (-6.81 g per 10 µg/m3 increase in PM10 [95% CI = -12.52 to -1.10]) and biomass burning (-6.34 g per 1 SD increase in fires/km2 [95% CI = -11.35 to -1.34]) only after adjustment for NO2. In contrast with these findings, a reduced odds ratio (OR) of LBW was associated with PM10 exposure only in trimesters one and two, with no relationship across the entire pregnancy period. Associations with biomass burning were limited to increased ORs of LBW with exposure in trimester three, but only for male births. CONCLUSION: Based on our results, we encourage further investigation of air pollution, biomass burning and BW in Thailand and other low-income and middle-income countries.

In Utero Exposure to Particulate Air Pollution during Pregnancy: Impact on Birth Weight and Health through the Life Course.

In high-income countries, and increasingly in lower- and middle-income countries, chronic non-communicable diseases (NCDs) have become the primary health burden. It is possible that in utero exposure to environmental pollutants such as particulate matter (PM) may have an impact on health later in life, including the development of NCDs. Due to a lack of data on foetal growth, birth weight is often used in epidemiologic studies as a proxy to assess impacts on foetal development and adverse birth outcomes since it is commonly recorded at birth. There are no research studies with humans that directly link PM exposure in utero to birth weight (BW) and subsequently, the effects of lower BW on health outcomes in old age. It is, however, plausible that such associations exist, and it is thus important to assess the potential public health impacts of PM across the life course, and it is plausible to use birth weight as an indicator of risk. We therefore split this narrative review into two parts. In the first part, we evaluated the strength of the evidence on the impact of PM exposure during the entire pregnancy on birth weight outcomes in ten meta-analyses. In the second part, we reviewed the literature linking lower birth weight to childhood and adult chronic cardiovascular disease to explore the potential implications of PM exposure in utero on health later in life. Within the reviewed meta-studies on birth weight, there is sufficient evidence that PM pollution is associated with lower birth weight, i.e., the majority of meta-studies found statistically significant reductions in birth weight. From the second part of the review, it is evident that there is good evidence of associations between lower birth weight and subsequent cardiovascular disease risk. It is thus plausible that in utero exposure to PM is associated with lower birth weight and persisting biological changes that could be associated with adverse health effects in adulthood. Based on the reviewed evidence, however, the magnitude of later life cardiovascular health impacts from in utero exposure and its impact on BW are likely to be small compared to health effects from exposure to particulate air pollution over a whole lifetime.

Challenging the spread of COVID-19 in Thailand.

Coronavirus disease (COVID-19) has been identified as a pandemic by the World Health Organization (WHO). It was initially detected in Wuhan, China and spread to other cities of China and all countries. It has caused many deaths and the number of infections became greater than 18 million as of 5 August 2020. This study aimed to analyze the situation of COVID-19 in Thailand and the challenging disease control by employing a dynamic model to determine prevention approaches. We employed a statistical technique to analyze the ambient temperature influencing the cases. We found that temperature was significantly associated with daily infected cases (p-value <0.01). The SEIR (Susceptible Exposed Infectious and Recovered) dynamic approach and moving average estimation were used to forecast the daily infected and cumulative cases until 16 June as a base run analysis using STELLA dynamic software and statistical techniques. The movement of people, both in relation to local (Thai people) and foreign travel (both Thai and tourists), played a significant role in the spread of COVID-19 in Thailand. Enforcing a state of emergency and regulating social distancing were the key factors in reducing the growth rate of the disease. The SEIR model reliably predicted the actual infected cases, with a root mean square error (RMSE) of 12.8. In case of moving average approach, RMSE values were 0.21, 0.21, and 0.35 for two, three and five days, respectively. The previous records were used as input for prediction that caused lower values of RMSE. Two-days and three-days moving averages gave the better results than SEIR model. The SEIR model is suitable for longer period prediction, whereas the moving average approach is suitable for short term prediction. The implementation of interventions, such as governmental regulation and restrictions, through collaboration among various sectors was the key factor for controlling the spreading of COVID-19 in Thailand.

Exposure to Heavy Metals in Electronic Waste Recycling in Thailand.

Electronic waste recycling can release heavy metals into the environment and cause adverse health effects. We assessed the association between exposure to heavy metals from electronic waste recycling and the prevalence of asthma in a nested case-control study of 51 subject pairs with and without asthma. House dust, airborne dust, blood, and urine were collected from residents of two neighboring sites in Ubon Ratchathani province, Thailand. Multiple electronic waste-handling activities are conducted in the first site, while the second site is mostly agricultural. Concentrations of chromium, mercury, nickel, and lead in house dust and airborne dust were higher in the electronic waste-handling site (p < 0.05), but levels of exposure were similar in subjects with and without asthma. Although we did not find an association between exposure to these metals and the prevalence of asthma, control measures should be implemented to reduce health risks from long-term exposure to heavy metals.