Geographical patterns of cancer mortality in China

Nina Sui-Ngan Lam

Social Science & Medicine, 1986, vol. 23, issue 3, 241-247

Abstract: This research note discusses the China cancer mortality data and the methodological problems involved in spatial analysis of these data. Some of the research findings produced by mapping and analyses of the cancer data at the provincial level are also summarized. The two most common cancers in China, stomach and esophagus, were found to have no significant correlation with some selected physical variables and population density, suggesting the need to examine other socio-economic variables such as dietary habit. The study also suggests that the type of diet which may be responsible for these two cancers could be very different from each others. Colon and rectum, leukemia, and breast cancers were found to have very high positive spatial autocorrelation and high correlation with population density--a result contrary to previous findings in the West. Future research using a geographic information system approach and county data is suggested.

Keywords: China; cancer; mortality; geographic; information; systems; computer; mapping; spatial; autocorrelation; factor; analysis (search for similar items in EconPapers)
Date: 1986
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0277-9536(86)90344-8
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:socmed:v:23:y:1986:i:3:p:241-247

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
http://www.elsevier. ... _01_ooc_1&version=01

Access Statistics for this article

Social Science & Medicine is currently edited by Ichiro (I.) Kawachi and S.V. (S.V.) Subramanian

More articles in Social Science & Medicine from Elsevier
Bibliographic data for series maintained by Catherine Liu ().