Avoidable mortality pattern in a Chinese population - Hong Kong, China

23Citations
Citations of this article
34Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Background: We examined the avoidable mortality pattern in Hong Kong, and the influence of age and gender. Comparison with Paris, Inner London and Manhattan was performed, and we discussed the findings in terms of prevention programmes, ethnicity and lifestyles. Methods: Mortality and population data by age and gender were obtained from vital statistics sources. Two periods, 1999-2003 and 2004-06, were selected for analysis. Negative binomial regression and logistic regression were used to model, respectively, the number and proportion of avoidable mortality, in relation to age and gender. Results: The standardized total mortality rates (per 1000 population) were 2.51 in the period 1999-2003 and 2.25 in the period 2004-06, whereas the standardized avoidable mortality rates (per 1000 population) were 0.85 and 0.77 for the two periods, respectively. Cerebrovascular disease (stroke) was the leading cause of avoidable mortality. Women in the age range of 65-74 years had the highest avoidable mortality proportion. In 1999-2003, Hong Kong had the second lowest standardized avoidable mortality rate among the four cities compared, whereas the avoidable mortality proportion was the highest. Conclusion: There might be room for improvement in the primary care system in Hong Kong, particularly in the development of effective prevention programmes targeting the leading causes of avoidable mortality. © The Author 2010.

Cite

CITATION STYLE

APA

Chau, P. H., Woo, J., Chan, K. C., Weisz, D., & Gusmano, M. K. (2011). Avoidable mortality pattern in a Chinese population - Hong Kong, China. European Journal of Public Health, 21(2), 215–220. https://doi.org/10.1093/eurpub/ckq020

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free