The relationship between cancer incidence and cancer mortality in Taiwan

• Main Authors: Chang-Pi Wang, 王昶弼
• Other Authors: wen-miin Liang
• Format: Others
• Language: zh-TW
• Published: 2001
• Online Access: http://ndltd.ncl.edu.tw/handle/10477985573865204061

碩士 === 中國醫藥學院 === 環境醫學研究所 === 89 === Throughout the world cancer is one of the leading causes of death. Many countries have collected data with regard to cancer mortality and cancer incidence for the past several decades in order to better understand this important disease. In recent years many studies have used these data to access cancer mortality and cancer incidence separately, but there is little literature about their relationship. The purpose of this study was to access the relationship between cancer mortality and cancer incidence with regard to temporal and spatial factors, and build a model to explain their relationship. The cancer data included in our study were from 1979-1999 and as follows: total cancer, lung cancer, liver cancer, colon/rectal cancer, stomach cancer, oral cancer, leukemia, cervical cancer and breast cancer. The indices for cancer mortality and incidence included rates for each 5-year age group, age standardized rate, 5-year cumulative age standardized rate, 5-scaled risk (at percentiles 20th, 40th, 60th and 80th), 2-scaled risk (at the 60th percentile), odds ratio and death/incidence (D/I) ratio. The spatial factors were urbanization, topographic area (outlying islands, mountainous regions and plains), proportion of elderly (aged 65 years and over), medical resources and population density. The temporal factors were time period, age effect, cohort effect and survival rates. The statistical methods used were as follows: spatial correlation index (Moran’s I), time-series correlation index, chi-squared test for trends, proportional hazards model, log-linear model and generalized linear model, Geographical Information System (GIS) was used to create the cancer map. The spatial analyses showed that there were positive correlations between cancer mortalities and cancer incidences. The cancer map indicated that the distribution of cancers varied among different cancers. There was a greater clustering effect for cancer incidence than for cancer mortality. There was a positive correlation of total cancer incidence with urbanization, topographic area (outlying islands, mountainous regions and plains), proportion of elderly, medical resources and population density, but proportion of elderly negatively. The temporal analyses showed that cancer mortality rates have been generally stable compared to cancer incidence rates which have risen at a faster rate. The ratio of mortality to incidence (D/I) was found to be a good index to show the relationship of cancer mortalities and cancer incidences with temporal factors such as time periods, age and survival rates and spatial factors such as urbanization, topographical areas, and population. Our proposal model shows that there were negative correlations of D/I ratio with time period effect and 5-year survival rate. There was a positive correlation of D/I ratio with age effect. Our model did not indicate a direct relationship between D/I ratio and spatial factors. However, this relationship may be determined indirectly. It is possible to systematically predict trends for different cancers according to their 5-year survival rates. Predictions can be made for different ages and time periods. Therefore, our proposed model allows for a comprehensive understanding of the relationship between different trends of cancer mortalities and cancer incidences and the impact factors such as age, time period survival rate and spatial factors. It would be helpful us to predict the future trend or evaluate the outcomes for the health policy.