Continuing comprehensive assessment of population health gap is essential for effective health planning. This paper assessed changes in the magnitude and pattern of disease burden in Thailand between 1999 and 2004. It further drew lessons learned from applying the global burden of disease (GBD) methods to the Thai context for other developing country settings.

Growing urbanisation and population requiring enhanced electricity generation as well as the increasing numbers of fossil fuel in Thailand pose important challenges to air quality management which impacts on the health of the population. Mortality attributed to ambient air pollution is one of the sustainable development goals (SDGs). We estimated the spatial pattern of mortality burden attributable to selected ambient air pollution in 2009 based on the empirical evidence in Thailand. We estimated the burden of disease attributable to ambient air pollution based on the comparative risk assessment (CRA) framework developed by the World Health Organization (WHO) and the Global Burden of Disease study (GBD). We integrated geographical information systems (GIS)-based exposure assessments into spatial interpolation models to estimate ambient air pollutant concentrations, the population distribution of exposure and the concentration-response (CR) relationship to quantify ambient air pollution exposure and associated mortality. We obtained air quality data from the Pollution Control Department (PCD) of Thailand surface air pollution monitoring network sources and estimated the CR relationship between relative risk (RR) and concentration of air pollutants from the epidemiological literature. We estimated 650–38,410 ambient air pollution-related fatalities and 160–5,982 fatalities that could have been avoided with a 20 reduction in ambient air pollutant concentrations. The summation of population-attributable fraction (PAF) of the disease burden for all-causes mortality in adults due to NO₂ and PM_2.5 were the highest among all air pollutants at 10% and 7.5%, respectively. The PAF summation of PM_2.5 for lung cancer and cardiovascular disease were 16.8% and 14.6% respectively and the PAF summations of mortality attributable to PM₁₀ was 3.4% for all-causes mortality, 1.7% for respiratory and 3.8% for cardiovascular mortality, while the PAF summation of mortality attributable to NO₂ was 7.8% for respiratory mortality in Thailand. Mortality due to ambient air pollution in Thailand varies across the country. Geographical distribution estimates can identify high exposure areas for planners and policy-makers. Our results suggest that the benefits of a 20% reduction in ambient air pollution concentration could prevent up to 25% of avoidable fatalities each year in all-causes, respiratory and cardiovascular categories. Furthermore, our findings can provide guidelines for future epidemiological investigations and policy decisions to achieve the SDGs.

Thailand has achieved remarkable improvement in health status since the achievement of universal health coverage in 2002. Health equity has improved significantly. However, challenges on health inequity still remain.This study aimed to determine the trends of geographical inequalities in disease specific mortality in Thailand after the country achieved universal health coverage. National vital registration data from 2001 to 2014 were used to calculate age-adjusted mortality rate and standardized mortality ratio (SMR). To minimize large variations in mortality across administrative districts, the adjacent districts were systematically grouped into “super-districts” by taking into account the population size and proximity. Geographical mortality inequality among super-districts was measured by the coefficient of variation. Mixed effects modeling was used to test the difference in trends between super-districts. The overall SMR steadily declined from 1.2 in 2001 to 0.9 in 2014. The upper north and upper northeast regions had higher SMR whereas Greater Bangkok achieved the lowest SMR. Decreases in SMR were mostly seen in Greater Bangkok and the upper northern region. Coefficient of variation of SMR rapidly decreased from 20.0 in 2001 to 12.5 in 2007 and remained close to this value until 2014. The mixed effects modelling revealed significant differences in trends of SMR across super-districts. Inequality in mortality declined among adults (≥15 years old) but increased in children (0–14 years old). A declining trend in inequality of mortality was seen in almost all regions except Greater Bangkok where the inequality in SMR remained high throughout the study period. A decline in the adult mortality inequality across almost all regions of Thailand followed universal health coverage. Inequalities in child mortality rates and among residents of Greater Bangkok need further exploration.

Despite achievement of universal health coverage in Thailand, socioeconomic inequality in health has been a major policy concern. This study examined mortality patterns across different socioeconomic strata in Thailand. We conducted a cross-sectional analysis of the 2010 Population and Housing Census on area-level socioeconomic deprivation against the 2010 mortality from the vital registration database at the super-district level. We used principal components analysis to construct a socioeconomic deprivation index and K-mean cluster analysis to group socioeconomic status and cause-specific mortality. Excess mortality rates from all diseases, except colorectal cancer, were observed among super-districts with low socioeconomic status. Spatial clustering was evident in the distribution of socioeconomic status and mortality rates. Cluster analysis revealed that super-districts which were predominantly urban tended to have low all-cause standardize mortality ratio but a high colorectal cancer-specific mortality rate. Deaths due to liver cancer, diabetes, and renal diseases were common in the low socioeconomic super-districts which hosted one third of the total Thai population. Socially deprived areas have an excess of overall and cause specific deaths. Populations living in more affluent areas, despite low general mortality, still have many preventable deaths such as colorectal cancer. These findings warrant future epidemiological studies investigating various causes of excessive deaths in non-deprived areas and implementation of policies to reduce the mortality gap between rich and poor areas.

Despite substantial positive impacts of Thailand’s tobacco control policies on reducing the prevalence of smoking, current trends suggest that further reductions are needed to ensure that WHO’s 2025 voluntary global target of a 30% relative reduction in tobacco use is met. In order to confirm this hypothesis, we aim to estimate the effect of tobacco control policies in Thailand on the prevalence of smoking and attributed deaths and assess the possibilities of achieving WHO’s 2025 global target. This paper addresses this knowledge gap which will contribute to policy control measures on tobacco control. Results of this study can help guide policy makers in implementing further interventions to reduce the prevalence of smoking in Thailand. A Markov chain model was developed to examine the effect of tobacco control policies, such as accessibility restrictions for youths, increased tobacco taxes and promotion of smoking cessation programs, from 2015 to 2025. Outcomes included smoking prevalence and the number of smoking-attributable deaths. Due to the very low prevalence of female smokers in 2014, this study applied the model to estimate the smoking prevalence and attributable mortality among males only. Given that the baseline prevalence of smoking in 2010 was 41.7% in males, the target of a 30% relative reduction requires that the prevalence be reduced to 29.2% by 2025. Under a baseline scenario where smoking initiation and cessation rates among males are attained by 2015, smoking prevalence rates will reduce to 37.8% in 2025. The combined tobacco control policies would further reduce the prevalence to 33.7% in 2025 and 89,600 deaths would be averted. Current tobacco control policies will substantially reduce the smoking prevalence and smoking-attributable deaths. The combined interventions can reduce the smoking prevalence by 19% relative to the 2010 level. These projected reductions are insufficient to achieve the committed target of a 30% relative reduction in smoking by 2025. Increased efforts to control tobacco use will be essential for reducing the burden of non-communicable diseases in Thailand.

The cadmium (Cd) contaminated rice fields in Mae Sot District, Tak Province, Thailand has been one of the major environmental problems in Thailand for the last 10 years. We used disability adjusted life years (DALYs) to estimate the burden of disease attributable to Cd in terms of additional DALYs of Mae Sot residents. Cd exposure data included Cd and β₂–microglobulin (β₂-MG) in urine (as an internal exposure dose) and estimated cadmium daily intake (as an external exposure dose). Compared to the general Thai population, Mae Sot residents gained 10%–86% DALYs from nephrosis/nephritis, heart diseases, osteoporosis and cancer depending on their Cd exposure type and exposure level. The results for urinary Cd and dietary Cd intake varied according to the studies used for risk estimation. The ceiling effect was observed in results using dietary Cd intake because of the high Cd content in rice grown in the Mae Sot area. The results from β₂-MG were more robust with additional DALYs ranging from 36%–86% for heart failure, cerebral infraction, and nephrosis/nephritis. Additional DALYs is a useful approach for assessing the magnitude of environmental Cd exposure. The Mae Sot population lost more healthy life compared to populations living in a non- or less Cd polluted area. This method should be applicable to various types of environmental contamination problems if exposure assessment information is available.