Factors affecting stroke mortality in Thailand
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2020
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2563
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eng
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91 leaves
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b212174
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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National Institute of Development Administration. Library and Information Center
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Pimchanok Puthkhao (2020). Factors affecting stroke mortality in Thailand. Retrieved from: https://repository.nida.ac.th/handle/662723737/6835.
Title
Factors affecting stroke mortality in Thailand
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Abstract
This dissertation aimed to compare the socioeconomic and health-related
characteristics of stroke and non-stroke deaths and to determine the factors affecting
stroke mortality, with non-stroke death considered as a competing risk. Secondary
data with a 10-12 years follow-up period from the Thai Epidemiologic Stroke (TES)
Study were used.
The Thai Epidemiologic Stroke (TES) Study is a prospective community-based
cohort study that recruited participants from the general population from five Thai
regions. Between 2004 and 2006, 19,620 participants aged 45-80 years, free of stroke,
participated in the baseline survey. The participants were followed up for mortality
from the survey date until the date of death or the end of follow-up of December 31,
2016, whichever came firsts. During a median follow-up time of 11.08 years (202,803
person-years at risk), 305 participants died of a stroke (1.55% of total participants and
accounted for 8.76% of total deaths), and 3,176 participants died of non-stroke cause
(16.19% of total participants and 91.24% of total deaths). Stroke mortality was
150.39/100,000 (95% confidence interval [95% CI], 134.43-168.25/100,000) personyears, and the non-stroke mortality was 1,566.05/100,000 (95% CI, 1,512.52- 1,621.47/100,000) person-years.
Multivariate cause-specific Cox regression and Fine-Gray competing risk
regression analyses were used to identify the factors affecting stroke mortality, with
non-stroke mortality considered as a competing event. Cause-specific hazard ratios
(HR) and the Subdistribution hazard ratio (SHR) with their 95% confidence intervals
(CI) were used to illustrate the associations.
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Thesis (Ph.D (Applied Statistics))--National Institute of Development Administration, 2020