Spatial Association Patterns of Smoking, Tobacco Outlet Density, and Secondhand Smoke in Thailand

Thammawongsa, Pittaya; Laohasiriwong, Wongsa; Prasit, Nakarin; Phimha, Surachai

doi:10.35741/issn.0258-2724.56.5.30

Cited by 4 publications

(3 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Social interactions involving smoking behaviours may contribute to the spread of tobacco and cigarette usage. This decreases the likelihood of quitting smoking and avoiding nicotine exposure and increases older adults' desire for social smoking [32][33][34] . In addition, socialisation increases the likelihood of obtaining alcohol in a working and aging society.…”

Section: Discussionmentioning

confidence: 99%

Health determinant factors associated with smoking behaviour of older adults in Thailand

Yanarueng¹,

Laohasiriwong²,

Phimha³

et al. 2023

JPHD

View full text Add to dashboard Cite

The health burden caused by smoking behaviour among older adults is an uncontrollable problem worldwide. In particular, the trend of smoking among the aging population is rapidly growing. It affects individuals, families, economies, and societies. Changes in health determinants influence the smoking behaviour of older adults who require health promotion so that they can take care of themselves. This cross-sectional study was performed using secondary data from the National Statistical Office of Thailand: Report of a survey of older adults in Thailand in 2017. The present study aimed to examine the health determinant factors associated with smoking behaviour of older adults in Thailand. Data were collected from 32,030 older adults using a structured questionnaire. Multi-level analysis was performed to identify the health determinants of smoking behaviour of older adults in Thailand by controlling the effect of other covariates. The results were presented as adjusted odds ratio (AOR) and 95 % confidence intervals (CI). Among the 32,030 older adults, 15.11% of the respondents were smokers. Factors associated with smoking behaviour of older adults in Thailand were male sex (AOR: 6.36, 95% CI: 5.80–6.94, P-value < 0.001), younger age (AOR: 4.35, 95% CI: 3.59–5.25, P-value < 0.001), currently working status (AOR: 1.40, 95% CI: 1.23–1.59, P-value < 0.001), very good physical health (AOR: 2.64, 95% CI:2.05-3.40, -value < 0.001), alcohol consumption (AOR: 7.06, 95% CI: 6.44–7.43, P-value < 0.001), and participation in group/club activities in the community (AOR: 1.17, 95% CI: 1.08–1.28, P-value < 0.001). There were significant differences in the risk of smoking among the older adults according to their health conditions and socialisation levels. This outcome reinforces the need to be alert for and respond to sex-related differences in the risk pattern and protective factors for smoking in older adults. Thus, it is critical to establish and implement an active and effective tobacco control program to protect the health of older adults, particularly considering Thailand's measures towards chronic disease prevention and increased life expectancy.

show abstract

Section: Discussionmentioning

confidence: 99%

Health determinant factors associated with smoking behaviour of older adults in Thailand

Yanarueng¹,

Laohasiriwong²,

Phimha³

et al. 2023

JPHD

View full text Add to dashboard Cite

show abstract

“…From the previous result, which according to Thailand situations, clearly present that growth economy cities are more pandemic than the middle-small economy cities [13], which make the pandemic control of Coronavirus Disease 2019 are not successfully, made it turn to be the one factor to make policy draft Distancing, Mask wearing, Hand washing, Testing and Thai Chana to adjust social situations, especially social office, citizens necessary to work for their lives, refer to life quality, struggling for a living [1] [21] and [22]. Except from the topic of the light, health consciousness building is also main factor too, ISSN: 1686-6576 (Printed) | ISSN 2673-0014 (Online) | © Geoinformatics International especially smoking behavior, and Thailand is face to this problem to fix smoking behavior of Thai people [23]. Smoking is directly cause harmful to lounge and respiratory tract, which make worse to resist the Coronavirus Disease 2019 and other chronic diseases [14] moreover, smoking is not only harm the people who smoke, but it also harms other people and social in from of second-hand smoking, the cigarette's smoke can cause skin irritation and harm lounge, decrease bodies immunity and respiratory tract, the damage is highly rising if the smoker is pandemic from Coronavirus Disease 2019 [24] and [25].…”

Section: Discussionmentioning

confidence: 99%

Spatial Association Patterns with Cultural and Behaviour with the Situations of COVID-19

2023

IJG

View full text Add to dashboard Cite

This study was a cross-sectional study. The study of spatial association patterns and the influences on the Coronavirus Disease 2019 (COVID-19) epidemic situation in Thailand was performed using secondary data from the COVID-19 interactive dashboard, Department of Disease Control, Ministry of Public Health, between January 1st, 2020, and December 31st, 2021. Moran’s I, Local Indicators of Spatial Association (LISA), and Spatial Regression was applied for statistical analysis. In the epidemic situation of COVID-19, the highest of 11,512.65 per one hundred thousand population, and the spatial association between the nighttime light average, the prevalence of smokers in Thailand, the proportion of population per village health volunteer, and the proportion of population per health care center with the epidemic situation of COVID-19 has Moran’s I = 0.309, 0.396, 0.081 and 0.424, respectively. From the Spatial Lag Model (SLM), a factor that has a spatial association with the epidemic situation of COVID-19 is the nighttime light average, the prevalence of smokers in Thailand, and the proportion of population per healthcare center, which can predict the epidemic situation of COVID-19 by 47.8 percent (R2 =0.478). The growth factor of a large city is an important factor for population density which is a major cause of spread of the coronavirus easily. Moreover, smoking behavior has encouraged the epidemic to spread rapidly. The situation is serious as the number of hospitals is not enough to support the treatment and screening of patients to cover the entire population of Thailand. Therefore, it is urgent that the government plan to mitigate the situation with maximum efficiency by having Covid-19 centers and increase the number of beds and facilities.

show abstract

“…This will allow Thailand to realize its objective of successfully developing and resolving health problems in each region (Khashoggi and Murad, 2020). ISSN: 1686-6576 (Printed) | ISSN 2673-0014 (Online) | © Geoinformatics International Currently, several studies have applied GIS in health systems and medicine Thammawongsa et al, 2021) . The socio-economic condition in each area is an index that represents the living conditions and the living environment of the people in that area.…”

Section: Introductionmentioning

confidence: 99%

Spatial Factors Associated with fall among the Elderly in Thailand

2022

IJG

View full text Add to dashboard Cite

Falls are the leading cause of injury-related visits to emergency departments around the world, including in Thailand, and the primary etiology of accidental deaths in elderly people. Falls among the elderly is an increasing problem, causing a high degree of morbidity, mortality, and use of health care services. This study statistically identified aimed to determine the association of the spatial factors with falls among elderly people in Thailand. The participant consisted of 40,489 elderly people and was conducted using a data set from the national statistical office of Thailand in 2017 and other data. A Moran’s I and local indicators of spatial association (Lisa) were used to identify the spatial autocorrelation between poverty incidence, the proportion of patients with non-communicable diseases, and the population-to- village health volunteers’ ratio with falls among elderly people in Thailand. The results showed that there was spatial global autocorrelation between poverty incidence, the proportion of patients with non-communicable diseases, and the population-to- village health volunteers among elderly people in Thailand with Moran’s I values of 0.176, 0.049, and 0.034, respectively. Therefore, the focus should be on promoting and preventing non-communicable diseases, as well as promoting income-generating jobs for the elderly by closely supervising village health volunteers and elderly caregivers to reduce the risk of falls among the elderly and improve their quality of life.

show abstract

Spatial Association Patterns of Smoking, Tobacco Outlet Density, and Secondhand Smoke in Thailand

Cited by 4 publications

References 2 publications

Health determinant factors associated with smoking behaviour of older adults in Thailand

Health determinant factors associated with smoking behaviour of older adults in Thailand

Spatial Association Patterns with Cultural and Behaviour with the Situations of COVID-19

Spatial Factors Associated with fall among the Elderly in Thailand

Contact Info

Product

Resources

About