Department of Global Health, Research School of Population Health, Australian National University, 339/4 Hutton St, Acton, ACT 2601, Australia.
School of Human Ecology, Sukhothai Thammathirat Open University, Nonthaburi, Thailand.
BMC Public Health. 2020 Nov 16;20(1):1714. doi: 10.1186/s12889-020-09803-1.
Thailand is a high injury burden setting. In 2015 it had the world's second highest rate of road traffic fatalities. In order to develop strategies to reduce this burden an accurate understanding of the development of injury risk over the life course is essential.
A national cohort of adult Thais was recruited in 2005 (n = 87,151). Participants completed a health questionnaire covering geodemographic, behavioural, health and injury data. Citizen ID numbers were matched with death registration records, identifying deaths from any injury. Adjusted logistic regression models were used to measure associations between baseline exposures and injury deaths between 2005 and 2015.
Injury mortality comprised 363 individuals, the majority (36%) from traffic injuries. Predictors of all-injury mortality were being male (AOR 3.55, 95% CI 2.57-4.89), Southern Thai (AOR 1.52, 95% CI 1.07-2.16), smoking (AOR 1.55, 95% CI 1.16-2.17), depression (AOR 1.78, 95% CI 1.07-2.96), previous injury (AOR 1.37, 95% CI 1.03-1.81) and drink driving history (AOR 1.37, 95%CI 1.02-1.85). Age and region of residence were stronger predictors for men, while anxiety/depression was a stronger predictor for women. Among males in the far south, assault caused the largest proportion of injury mortality, elsewhere traffic injury was most common.
This study identifies that a history of drink driving, but not regular alcohol consumption, increased injury risk. The associations between smoking and depression, and injury mortality also need further consideration.
泰国是一个高伤害负担的地区。2015 年，泰国的道路交通死亡率位居世界第二。为了制定减少这一负担的策略，准确了解伤害风险在整个生命过程中的发展至关重要。
2005 年，一项针对泰国成年人的全国队列研究招募了 87151 名参与者。参与者完成了一份涵盖地理人口统计学、行为、健康和伤害数据的健康问卷。公民身份证号码与死亡登记记录相匹配，以确定任何伤害导致的死亡。使用调整后的逻辑回归模型来衡量 2005 年至 2015 年期间基线暴露与伤害死亡之间的关联。
伤害死亡率包括 363 人，其中大多数（36%）死于交通事故。所有伤害死亡的预测因素包括男性（AOR3.55，95%CI2.57-4.89）、泰国南部人（AOR1.52，95%CI1.07-2.16）、吸烟（AOR1.55，95%CI1.16-2.17）、抑郁（AOR1.78，95%CI1.07-2.96）、既往伤害（AOR1.37，95%CI1.03-1.81）和酒后驾车史（AOR1.37，95%CI1.02-1.85）。年龄和居住地区是男性的更强预测因素，而焦虑/抑郁是女性的更强预测因素。在最南端的男性中，袭击是伤害死亡的最大比例原因，而其他地区最常见的是交通事故。
本研究表明，酒后驾车史而非定期饮酒会增加伤害风险。吸烟和抑郁与伤害死亡率之间的关联也需要进一步考虑。
