Fang, Jia-Ying;Dong, Hong-Li;Wu, Ku-Sheng;Du, Pei-Ling;Xu, Zhen-Xi;Lin, Kun
Asian Pacific Journal of Cancer Prevention
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v.16
no.14
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pp.5829-5834
/
2015
Objective: To describe and analyze the epidemiological characteristics of lung cancer mortality in China from 1991 to 2013, forecast the future five-year trend and provide scientific evidence for prevention and management of lung cancer. Materials and Methods: Mortality data for lung cancer in China from 1991 to 2013 were used to describe epidemiological characteristics. Trend surface analysis was applied to analyze the geographical distribution of lung cancer. Four models, curve estimation, time series modeling, gray modeling (GM) and joinpoint regression, were performed to forecast the trend for the future. Results: Since 1991 the mortality rate of lung cancer increased yearly. The rate for males was higher than that for females and rates in urban areas were higher than in rural areas. In addition, our results showed that the trend will continue to increase in the ensuing 5 years. The mortality rate increased from age 45-50 and peaked in the group of 85 years old. Geographical analysis indicated that people living in northeast China provinces and the coastal provinces in eastern China had a higher mortality rate for lung cancer than those living in the centre or western Chinese provinces. Conclusions: The standardized mortality rate of lung cancer has constantly increased from 1991 to 2013, and been predicted to continue in the ensuing 5 years. Further efforts should be concentrated on education of the general public to increase prevention and early detection. Much better prevention and management is needed in high mortality areas (northeastern and eastern parts of China) and high risk populations (45-50-year-olds).
Haghighat, S.;Akbari, M.E.;Ghaffari, S.;Yavari, P.
Asian Pacific Journal of Cancer Prevention
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v.13
no.11
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pp.5525-5528
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2012
Introduction: Breast cancer is the most common cancer in women. Improvements of early diagnosis modalities have led to longer survival rates. This study aimed to determine the 5, 10 and 15 year mortality rates of breast cancer patients compared to the normal female population. Materials and Methods: The follow up data of a cohort of 615 breast cancer patients referred to Iranian Breast Cancer Research Center (BCRC) from 1986 to 1996 was considered as reference breast cancer dataset. The dataset was divided into 5 year age groups and the 5, 10 and 15 year probability of death for each group was estimated. The annual mortality rate of Iranian women was obtained from the Death Registry system. Standardized mortality ratios (SMRs) of breast cancer patients were calculated using the ratio of the mortality rate in breast cancer patients over the general female population. Results: The mean age of breast cancer patients at diagnosis time was 45.9 (${\pm}10.5$) years ranging from 24-74. A total of 73, 32 and 2 deaths were recorded at 5, 10 and 15 years, respectively, after diagnosis. The SMRs for breast cancer patients at 5, 10 and 15 year intervals after diagnosis were 6.74 (95% CI, 5.5-8.2), 6.55 (95%CI, 5-8.1) and 1.26 (95%CI, 0.65-2.9), respectively. Conclusion: Results showed that the observed mortality rate of breast cancer patients after 15 years from diagnosis was very similar to expected rates in general female population. This finding would be useful for clinicians and health policy makers to adopt a beneficial strategy to improve breast cancer survival. Further follow-up time with larger sample size and a pooled analysis of survival rates of different centres may shed more light on mortality patterns of breast cancer.
Wu, Li-Zhu;Han, Ren-Qiang;Zhou, Jin-Yi;Yang, Jie;Dong, Mei-Hua;Qian, Yun;Wu, Ming
Asian Pacific Journal of Cancer Prevention
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v.15
no.6
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pp.2727-2732
/
2014
Objectives: The aim of this study was to describe and analyze the incidence and mortality of female breast cancer in Jiangsu Province of China. Methods: Incidence and mortality data for female breast cancer and corresponding population statistics from eligible cancer registries in Jiangsu from 2006 to 2010 were collected and analyzed. Crude rates, age-specific rates and age-standardized rates of incidence and mortality were calculated, and annual present changes (APCs) were estimated to describe the time trends. Results: From 2006 to 2010, 11,013 new cases and 3,068 deaths of female breast cancer were identified in selected cancer registry areas of Jiangsu. The annual average crude incidence and age-standardized incidence by world population (ASW) were 25.2/ and 17.9/100,000 respectively. The annual average crude and ASW for mortality rates were 7.03/ and 4.81/100,000. The incidence was higher in urban areas than that in rural areas, and this was consistent in all age groups. No significant difference was observed in mortality between urban and rural areas. Two peaks were observed when looking at age-specific rates, one at 50-59 years and another at over 85 years. During the 5 years, incidence and mortality increased with APCs of 4.47% and 6.89%, respectively. Compared to the national level, Jiangsu is an area with relatively low risk of female breast cancer. Conclusion: Breast cancer has become a main public health problem among Chinese females. More prevention and control activities should be conducted to reduce the burden of this disease, even in relatively low risk areas like Jiangsu.
Vulnerability to heat was examined for populations of 6 major cities in South Korea (Seoul, Incheon, Daejeon, Gwangju, Daegu, and Busan). Daily excess mortality and maximum temperature from 1991 to 2005 were employed in this study. The results show that the standardized mortality increase associated with a $1^{\circ}C$ increase in daily maximum temperature above the city-specific threshold explains the heat acclimatization effect better than the threshold temperature itself. The estimated increase in mortality (standardized per 10 million population) associated with a $1^{\circ}C$ increase in temperature above the threshold is 4.8 in Incheon, 4.7 in Seoul, 4.3 in Daejeon, 2.8 in Gwangju, 2.4 in Daegu, and 1.5 in Busan, well reflecting the latitudinal locations and local climates of each city. Climate models project more frequent, more intense, and longer lasting heat waves in most land areas in both hemispheres in the 21st century under increasing greenhouse gas concentrations. In order to mitigate the adverse human health impacts due to excess heat, more detailed characteristics of acclimatization to heat need to be understood and quantified.
Objectives: In 1995, an outbreak survey in Gozan-dong concluded that an association between fiberglass exposure in drinking water and cancer outbreak cannot be established. This study follows the subjects from a study in 1995 using a data linkage method to examine whether an association existed. The authors will address the potential benefits and methodological issues following outbreak surveys using data linkage, particularly when informed consent is absent. Methods: This is a follow-up study of 697 (30 exposed) individuals out of the original 888 (31 exposed) participants (78.5%) from 1995 to 2007 assessing the cancer outcomes and deaths of these individuals. The National Cancer Registry (KNCR) and death certificate data were linked using the ID numbers of the participants. The standardized incidence ratio (SIR) and standardized mortality ratio (SMR) from cancers were calculated by the KNCR. Results: The SIR values for all cancer or gastrointestinal cancer (GI) occurrences were the lowest in the exposed group (SIR, 0.73; 95% CI, 0.10 to 5.21; 0.00 for GI), while the two control groups (control 1: external, control 2: internal) showed slight increases in their SIR values (SIR, 1.18 and 1.27 for all cancers; 1.62 and 1.46 for GI). All lacked statistical significance. All-cause mortality levels for the three groups showed the same pattern (SMR 0.37, 1.29, and 1.11). Conclusions: This study did not refute a finding of non-association with a 13-year follow-up. Considering that many outbreak surveys are associated with a small sample size and a cross-sectional design, follow-up studies that utilize data linkage should become standard procedure.
Taghavi, Afsoon;Fazeli, Zeinab;Vahedi, Mohsen;Baghestani, Ahmad Reza;Pourhoseingholi, Asma;Barzegar, Farnoosh;Pourhoseingholi, Mohamad Amin
Asian Pacific Journal of Cancer Prevention
/
v.13
no.1
/
pp.367-370
/
2012
Background: Breast cancer is the most commonly diagnosed cancer in women worldwide In Iran, it ranks first among cancers diagnosed in women and is the fifth most common cause of death. The aim of this study was to present the mortality trends from breast cancer for Iranian women during a period of almost a decade, in order to provide update information regarding the likely future. Methods: We analyzed National death Statistic reported by the Iranian Ministry of Health and Medical Education from 1995 to 2004 to generate annual mortality rates/100,000, overall, by age group (<15, 15-49 and ${\geq}50$ years of age) and age standardized rate (ASR). Results: The age standardized mortality rate of breast cancer increased dramatically during these years from 1.40 to 3.52 per 100,000 and its mortality was increasing 151.4% for Iranian women, although it seemed that the rate leveled off from 2002 to 2004. Moreover the increasing rate was higher for those aged between 15-49 compared to age >50 years old. Conclusion: There is an increasing trend for breast cancer mortality in Iran. Thus, health education programs to rectify the lack of women awareness about breast cancer signs and effective screening are urgently needed.
Background: Breast cancer is the most common malignancy in women worldwide and its incidence is generally increasing. In 2012, it was the second most common cancer in the world. It is necessary to obtain information on incidence and mortality for health planning. This study aimed to investigate the relationship between the human development index (HDI), and the incidence and mortality rates of breast cancer in the world in 2012. Materials and Methods: This ecologic study concerns incidence rate and standardized mortality rates of the cancer from GLOBOCAN in 2012, and HDI and its components extracted from the global bank site. Data were analyzed using correlation tests and regression with SPSS software (version 15). Results: Among the six regions of WHO, the highest breast cancer incidence rate (67.6) was observed in the PAHO, and the lowest incidence rate was 27.8 for SEARO. There was a direct, strong, and meaningful correlation between the standardized incidence rate and HDI (r=0.725, $p{\leq}0.001$). Pearson correlation test showed that there was a significant correlation between age-specific incidence rate (ASIR) and components of the HDI (life expectancy at birth, mean years of schooling, and GNP). On the other, a non-significant relationship was observed between ASIR and HDI overall (r=0.091, p=0.241). In total, a significant relationship was not found between age-specific mortality rate (ASMR) and components of HDI. Conclusions: Significant positive correlations exist between ASIR and components of the HDI. Socioeconomic status is directly related to the stage of the cancer and patient's survival. With increasing the incidence rate of the cancer, mortality rate from the cancer does not necessariloy increase. This may be due to more early detection and treatment in developed that developing countries. It is necessary to increase awareness of risk factors and early detection in the latter.
Objectives: To examine the regional mortality differences in The Republic of Korea according to geographic location. Methods: All 232 administrative districts of the Republic of Korea in 1998 were studied according to their geographic locations by dividing each district into three categories; "metropolis," "urban," and "rural". Crude mortality rates for doth sexes from total deaths as well as the three major causes of death in Korea (cardiovascular disease, cancer, and external causes) were calculated with raw data from the "1998 report on the causes of death statistics" and resident registration data. Standardized mortality ratios (SMR) were calculated using the indirect standardization method. Poisson regression analyses were performed to examine the effects of geographic locations on the risk of death. To correct for the socioeconomic differences of each region, the percentage of old ($\geq$ 65 years old) population, the number of privately owned cars per 100 population, and per capita manufacturing production industries were included in the model. Results: Most SMRs were the lowest in the metropolis and the highest in the rural areas. These differences were more prominent in men and in deaths from external causes. In deaths from cancer in women, the rural region showed the lowest SMR. In Poisson regression analysis after correcting for regional socioeconomic differences, the risk of death from all causes significantly increased in both urban (OR=1.111) and rural (OR=1.100) regions, except for rural women, compared to the metropolis region. In men, the rural region showed higher risk (OR=1.180) than the urban region (OR=1.l51). For cardiovascular disease and cancer, significant differences were not found between geographic locations, except in urban women for cardiovascular disease (OR=1.151) and in rural women for cancer (OR=0.887), compared to metropolis women. In deaths from external causes, the risk ratios significantly increased in both urban and rural regions and an increasing tendency from the metropolis to the rural region was clearly observed in both sexes. Conclusions: Regional mortality differences according to geographic location exist in The Republic of Korea and further research and policy approaches to reduce these differences are needed. to reduce these differences are needed.
Objectives: Busan is reported to have the highest mortality rate among 16 provinces in Korea, as well as considerable health inequality across its districts. This study sought to examine overall and cause-specific mortality and deprivation at the town level in Busan, thereby identifying towns and causes of deaths to be targeted for improving overall health and alleviating health inequality. Methods: Standardized mortality ratios (SMRs) for all-cause and four specific leading causes of death were calculated at the town level in Busan for the years 2005 through 2008. To construct a deprivation index, principal components and factor analysis were adopted, using 10% sample data from the 2005 census. Geographic information system (GIS) mapping techniques were applied to compare spatial distributions between the deprivation index and SMRs. We fitted the Gaussian conditional autoregressive model (CAR) to estimate the relative risks of mortality by deprivation level, controlling for both the heterogeneity effect and spatial autocorrelation. Results: The SMRs of towns in Busan averaged 100.3, ranging from 70.7 to 139.8. In old inner cities and towns reclaimed for replaced households, the deprivation index and SMRs were relatively high. CAR modeling showed that gaps in SMRs for heart disease, cerebrovascular disease, and physical injury were particularly high. Conclusions: Our findings indicate that more deprived towns are likely to have higher mortality, in particular from cardiovascular disease and physical injury. To improve overall health status and address health inequality, such deprived towns should be targeted.
Objectives : The aims of this paper were to develop the composite deprivation index (CDI) for the sub-district (Eup-Myen-Dong) levels based on the theory of social exclusion and to explore the relationship between the CDI and the standardized mortality ratio (SMR). Methods : The paper calculated the age adjusted SMR and we included five dimensions of social exclusion for CDI; unemployment, poverty, housing, labor and social network. The proxy variables of the five dimensions were the proportion of unemployed males, the percent of recipients receiving National Basic Livelihood Security Act benefits, the proportion of households under the minimum housing standard, the proportion of people with a low social class and the proportion of single-parent household. All the variables were standardized using geometric transformation and then we summed up them for a single index. The paper utilized the 2004-2006 National Death Registry data, the 2003-2006 national residents' registration data, the 2005 Population Census data and the 2005-2006 means-tested benefit recipients' data. Results : The figures were 115.6, 105.8 and 105.1 for the CDI of metropolitan areas (big cities), middle size cities and rural areas, respectively. The distributional variation of the CDI was the highest in metropolitan areas (8.9 - 353.7) and the lowest was in the rural areas (26.8 - 209.7). The extent and relative differences of deprivation increased with urbanization. Compared to the Townsend and Carstairs index, the CDI better represented the characteristics of rural deprivation. The correlation with the SMR was statistically significant and the direction of the CDI effects on the SMR was in accordance with that of the previous studies. Conclusions : The study findings indicated mortality inequalities due to the difference in the CDI. Despite the attempt to improve deprivation measures, further research is warranted for the consensus development of a deprivation index.
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