title: Clustering of disability caused by unintentional injury among 15- to 60-year-old: a challenge in rapidly developing countries.
abstract: Little is known about disability caused by unintentional injury (accidents) worldwide. This study estimates the prevalence of disability caused by unintentional injury amongst people aged 15-60 years across different cities in the People's Republic of China with the aim of providing a scientific basis for developing prevention and control programmes. The prevalence of disability caused by unintentional injury in this target group in sampled cities across the country was estimated from data from the Second Chinese National Sample Survey on Disability. Using the statistical evolution tree approach, cities automatically clustered into a tree structure according to the level of social security and industrial structure. The Kruskal- Wallis test was applied to compare the prevalence in various types of city. The results show that the prevalence of disability due to unintentional injury in the target population group varied significantly across the 16 types of city investigated, but that it was particularly common among the unemployed and poor. With regard to occupational structure, cities with activities oriented towards transport and construction had the highest average prevalence despite access to local, relatively sound social security systems and adequate medical resources. It was also found that people struck by unintentional injury were treated in various ways depending on the availability of social assistance, medical care and job training, which differed widely between cities depending on each city's main occupational activity. High-risk cities areas were identified for that would benefit particularly by additional medical resource allocation as it would reduce their burden of unintentional injury.
authors.forename: Yi-Lan
authors.initials: YL
authors.lastname: Liao
authors.forename: Jin-Feng
authors.initials: JF
authors.lastname: Wang
authors.forename: Gong
authors.initials: G
authors.lastname: Chen
authors.forename: Wei
authors.initials: W
authors.lastname: Du
authors.forename: Xin-Ming
authors.initials: XM
authors.lastname: Song
authors.forename: Xiao
authors.initials: X
authors.lastname: Yun
authors.forename: Xiao-Ying
authors.initials: XY
authors.lastname: Zheng
mesh_terms: D000059:Accidents / Q000706:statistics & numerical data*; D000293:Adolescent; D000328:Adult; D002681:China / Q000453:epidemiology; D016000:Cluster Analysis; D003906:Developing Countries; D006233:Persons with Disabilities / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015995:Prevalence; D014505:Urban Population; D014947:Wounds and Injuries / Q000453:epidemiology*