IntroductionSmoking is an important public health concern. This study is the first that attempts to estimate the economic cost of smoking and secondhand smoke (SHS) exposure at home in Thailand.MethodA prevalence-based cost of illness approach following the guideline by WHO is employed.ResultIn 2017, the direct morbidity cost attributable to smoking and SHS exposure at home in Thailand was estimated to be at least US$265.97 million and US$23.66 million, respectively. Indirect morbidity costs from workday loss totalling US$25.04 million can be linked to smoking, while US$1.72 million was the result of SHS exposure at home. Smoking-attributable premature deaths resulted in an opportunity loss to the country equivalent to US$2.48 billion, while the figure was US$181.41 million for SHS exposure at home. Total years of life lost due to smoking and SHS-attributable premature deaths are estimated to have been at least 390 955 years for males and 82 536 years for females. The total economic cost from both types of tobacco exposure amounted to US$2.98 billion, equivalent to 17.41% of Thailand’s current health expenditure or 0.65% of its gross domestic product in 2017.ConclusionSmoking imposed a substantial economic burden on Thailand in 2017. Seven per cent of this cost was imposed on non-smokers sharing a residence with smokers. Females bore 80% of this SHS-related cost. The findings call for prompt responses from public health agencies in Thailand to launch effective tobacco control policies.
This paper assesses the interaction of family structure and electronic device usage on cognitive and non-cognitive development of children under the age of 5 years old. The study uses the 2015 Multiple Indicators Cluster Survey of Thailand to conduct the analysis. We adopt endogenous probit switching, bivariate probit, and binary probit models in this study. Specification analyses point out that the endogenous probit switching model provides the best fit for our data. Our results demonstrate that when children use electronic device it can increase the probability of having good cognitive development by 28.6% while lower the probability of having good non-cognitive ability by 6.1%. Furthermore, it is found that children residing in skipped generation family may experience 26.1% higher probability of being cognitively on track comparing to their complete family counterparts if there is no electronic device use. Conversely, children living with single mothers are the most vulnerable group in that the probability of achieving good non-cognitive skills drops by 6.3% if they report using any electronic device. Given that Thailand has experienced the fastest growing use of internet in South East Asia during the past two decades as well as having one of the most rapid demographic transition in the region, other developing countries should be able to learn from this unique setting to see strong interplay of electronic device use and family structure towards early childhood development. JEL Classification: I31, J12, J13
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