Children orphaned from COVID-19 in Thailand: maximize use of civil registration database for policies.

Orphans, especially those who experience maternal loss at a young age, face significant long-term negative impacts on their lives and psychological well-being, extending beyond the age of 18. As of July 2023, the global death toll of COVID-19 has reached 6.9 million, leaving behind an unknown number of orphans who require immediate attention and support from policymakers. In Thailand, from April 2020 to July 2022, the total number of COVID-19-related deaths reached 42,194, resulting in 4,139 parental orphans. Among them, 452 (10.9%) were children under the age of five, who are particularly vulnerable and necessitate special policy attention and ongoing support. While the provision of 12 years of free education for all and Universal Health Coverage helps alleviate the education and health expenses borne by households supporting these orphans, the monthly government support of 2,000 Baht until the age of 18 is insufficient to cover their living costs and other education-related expenditures. We advocate for adequate financial and social support for COVID-19 orphans, emphasizing the importance of placing them with relatives rather than institutional homes. In the context of post-pandemic recovery, this perspective calls upon governments and global communities to estimate the number of orphans and implement policies to safeguard and support them in the aftermath of COVID-19.

Are exposure to health information and media health literacy associated with fruit and vegetable consumption?

BACKGROUND: Health information promotes a healthy lifestyle; however, media health literacy (MHL) is essential to personal intake, especially fruit and vegetables (F&V). This study aimed to determine how exposure to health information and MHL affect F&V consumption among Thai youth aged 10-14 years. Health behavior at this age can be an important determinant of consumption habits when transitioning into adulthood. METHODS: A stratified two-stage sample survey was conducted to recruit 1,871 youth across regions to be nationally representative. Qualtrics offline survey application was used for data collection face-to-face with all respondents. Multiple linear regression was used to analyze the explanatory variables on fruit consumption and vegetable consumption. RESULTS: This study found that almost 70% of Thai youth were exposed to health-related content via the Internet, and had low analytical skills to process that information. Grade Point Average (GPA), exposure to health information, various media types, frequency of exposure to health information, and MHL influenced the frequency of F&V intake. Health status related to fruit intake, age, place of residence, amount of pocket money, and body mass index (BMI) were associated with F&V consumption. CONCLUSION: Exposure to health information and MHL are associated with F&V intake. Therefore, exposure to health information and MHL should be addressed for policy formulation in Thai schools and the health system.

A Bayesian approach to combining multiple information sources: Estimating and forecasting childhood obesity in Thailand.

We estimate and forecast childhood obesity by age, sex, region, and urban-rural residence in Thailand, using a Bayesian approach to combining multiple source of information. Our main sources of information are survey data and administrative data, but we also make use of informative prior distributions based on international estimates of obesity trends and on expectations about smoothness. Although the final model is complex, the difficulty of building and understanding the model is reduced by the fact that it is composed of many smaller submodels. For instance, the submodel describing trends in prevalences is specified separately from the submodels describing errors in the data sources. None of our Thai data sources has more than 7 time points. However, by combining multiple data sources, we are able to fit relatively complicated time series models. Our results suggest that obesity prevalence has recently starting rising quickly among Thai teenagers throughout the country, but has been stable among children under 5 years old.

Obesity and occupation in Thailand: using a Bayesian hierarchical model to obtain prevalence estimates from the National Health Examination Survey.

BACKGROUND: Like many developing countries, Thailand has experienced a rapid rise in obesity, accompanied by a rapid change in occupational structure. It is plausible that these two trends are related, with movement into sedentary occupations leading to increases in obesity. National health examination survey data contains information on obesity and socioeconomic conditions that can help untangle the relationship, but analysis is challenging because of small sample sizes. METHODS: This paper explores the relationship between occupation and obesity using data on 10,127 respondents aged 20-59 from the 2009 National Health Examination Survey. Obesity is measured using waist circumference. Modelling is carried out using an approach known as Multiple Regression with Post-Stratification (MRP). We use Bayesian hierarchical models to construct prevalence estimates disaggregated by age, sex, education, urban-rural residence, region, and occupation, and use census population weights to aggregate up. The Bayesian hierarchical model is designed to protect against overfitting and false discovery, which is particularly important in an exploratory study such as this one. RESULTS: There is no clear relationship between the overall sedentary nature of occupations and obesity. Instead, obesity appears to vary occupation by occupation. For instance, women in professional occupations, and men who are agricultural or fishery workers, have relatively low rates of obesity. CONCLUSION: Bayesian hierarchical models plus post-stratification offers new possibilities for using surveys to learn about complex health issues.

Kinlessness Around the World.

OBJECTIVES: The first and second demographic transitions have led to profound changes in family networks. However, the timing and extent of these transitions vary widely across contexts. We examine how common it is for contemporary older adults to lack living kin and whether such individuals are uniformly disadvantaged around the world. METHODS: Using surveys from 34 countries that together contain 69.6% of the world's population over age 50 and come from all regions of the world, we describe the prevalence and correlates of lacking immediate kin. We examine macro-level demographic indicators associated with the prevalence of kinlessness as well as micro-level associations between kinlessness and sociodemographic and health indicators. RESULTS: There is great variation in levels of kinlessness, from over 10% with neither a spouse nor a biological child in Canada, Ireland, the Netherlands, and Switzerland to levels below 2% in China and the Republic of Korea. There are strong macro-level relationships between kinlessness and lagged or contemporaneous fertility, mortality, and nuptiality measures and more marginal relationships with other demographic forces. Micro-level associations between kinlessness and respondent attributes are varied. The kinless are more likely to live alone than those with kin in all countries. In most countries, they have equivalent or worse self-rated health and lower education, although there are notable exceptions. There is substantial variation in the gender composition of the kinless population. DISCUSSION: As demographic changes affecting kinlessness continue, we expect the scale of the kinless population to grow around the world.

From whom do older persons prefer support? The case of rural Thailand.

This study explores rural elderly preferences for support across a multi-dimensional measure of elderly care needs. Applying a framework developed in the U.S. to Thailand for the first time, five diverse types of support are considered: meal preparation, personal care, transportation, financial support, and emotional support. The emphasis is on preferences for care and not actual care received. The data are from focus group discussions conducted in seven villages in Nang Rong district, northeastern Thailand. Thailand and the study site represent the social and economic conditions faced by many rapidly industrializing places-where there has been a dramatic demographic transition (lowered fertility and substantial out-migration), growing numbers of older persons remaining in rural settings, and limited publically-financed elderly care or market-based elder care available for purchase. For this study, in each village, male and female older persons aged 60 and over participated in the focus group discussions. As part of the discussion, focus group participants were asked to rank their first four preferences by type of support. Male and female older persons' preferences were slightly different for genderized tasks. In addition, social closeness and geographical proximity mattered. Traditional matrilocal residence patterns contributed to the perceptions of the older persons. Neighbors were preferred when kin were not available. Preferences inform strategic choices by older persons given the context of available resources. Understanding preferences and strategic choices among the older persons can help policy makers tailor programs more effectively and efficiently, without jeopardizing elderly well-being.