• Journal of Preventive Medicine and Public Health
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• v.42 no.6
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• pp.392-402
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• 2009

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.

• Journal of Ginseng Research
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• v.27 no.4
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• pp.158-164
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• 2003

Recently, there are much concerns about ginseng as disease therapeutics. There are no epidemiologic study on relationship between ginseng intake and all cause mortality based from general population Cohort. This study sought to examine relationships between ginseng intake and all cause mortality from Kangwha Cohort data. From March 1985 through December 1999, 2696 males and 3595 females who were aged 55 or over as of 1985 were followed up. We calculate the mortality rate, standardized mortality ratio and risk ratios by ginseng intake. Cox proportional hazard model was used to adjust various confounding factors. Ginseng intake group had the lower all cause mortality(Risk ratio(RR)=0.88, 95%Confidence Interval(CI)=0.79-0.97) among males. Increasing ginseng intake, lower all cause mortality(Low ginseng intake: RR=0.88, 95%CI=0.79-0.98; high ginseng intake : RR=0.87, 95%CI=0.75-1.00) among males. There is no statistically significant difference between ginseng intake and mortality among females. The results of this study suggests that ginseng intake may prolong the human life among males.

• Asian Journal of Atmospheric Environment
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• v.3 no.1
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• pp.9-18
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• 2009

This study aimed at assessing the association between exposure to severe air pollution in the past and the subsequent transition in lung cancer mortality among persons who lived in an industrial city. Vital statistics from 1983 to 2006 and the data on air pollution measurements from 1960 to 1990 in Amagasaki City, Japan, were used. Pearson correlation coefficients were calculated between the standardized mortality ratios (SMRs) for lung cancer and the air pollution levels in 6 wards of Amagasaki City. The associations between changes in air pollution levels and the annual SMRs were also evaluated in the light of a potential latency period. The levels of air pollution were extremely high in the 1960s, and they decreased since 1970. The SMRs for lung cancer in 1989-1993 among females for 6 wards were significantly associated with the amounts of both sulfur oxides and dust fall in the past for each ward. The positive associations were observed between the annual SMRs among females and the amounts of both pollutants when the lag time of 20-30 years was taken into account. These results suggest that severe air pollution in the 1960s in an industrial city affected the subsequent increase in lung cancer mortality.

• Journal of Preventive Medicine and Public Health
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• v.40 no.3
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• pp.233-238
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• 2007

Objectives : We aimed to assess the relationship between long-term exposure to air pollution and lung cancer in the Republic of Korea. Methods : Using the Annual Report of Ambient Air Quality in Korea, Annual Report of National Cancer Registration, and Annual Report on the Cause of Death Statistics, we calculated the standardized mortality ratio (SMR) and standardized incidence ratio (SIR) of lung cancer for both sexes in 74 areas from 7 Korean metropolitan cities. We performed random intercept, Poisson regression using empirical Bayes method. Results : Both SMRs and SIRs in the 7 metropolitan cities were higher in women than in men. Mean SIRs were 99.0 for males and 107.0 for females. The association between $PM_{10}$ and lung cancer risk differed according to gender. $PM_{10}$ was not associated with the risk of lung cancer in males, but both incidence and mortality of lung cancer were positively associated with $PM_{10}$ in females. The estimated percentage increases in the rate of female lung cancer mortality and incidence were 27% and 65% at the highest $PM_{10}$ category $({\geq}70\;{\mu}g/m^3)$, compared to the referent category $({\geq}50\;{\mu}g/m^3)$. Conclusions : Long-term exposure to $PM_{10}$ was significantly associated with female lung cancer incidence in 7 Korean metropolitan cities. Further study is undergoing to estimate the relative risk of $PM_{10}$ using multi-level analysis for controlling individual and regional confounders such as smoking and socioeconomic position.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1531-1538
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• 2014

The causes of cancer are diverse, complex, and only partially understood. Many factors including health behaviors, socioeconomic environments and geographical locations can directly damage genes or combine with existing genetic faults within cells to cause cancerous mutations. Collecting the cancer data and reporting the statistics, therefore, are important to help identify health trends and establish normal health changes in geographical areas. In this article, we analyzed cancer data and demon-strated how spatial patterns of the age-standardized rate and health indicators can be examined visually and simultaneously using linked micromap plots. As a result of data analysis, the age-standardized rate has positive correlativity with thyroid and breast cancer, but the rate has negative correlativity with smoking and drinking. In addition, the regions with high age-standardized rate are located in southwest and the areas of high population density while the standardized mortality ratio is higher in southwest and northeast where there are lots of rural areas.

• 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.

• Journal of Preventive Medicine and Public Health
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• v.54 no.5
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• pp.352-359
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• 2021

Objectives: The aim of this study was to examine the geographic distribution of diabetes mortality in Japan and identify socioeconomic factors affecting differences in municipality-specific diabetes mortality. Methods: Diabetes mortality data by year and municipality from 2013 to 2017 were extracted from Japanese Vital Statistics, and the socioeconomic characteristics of municipalities were obtained from government statistics. We calculated the standardized mortality ratio (SMR) of diabetes for each municipality using the empirical Bayes method and represented geographic differences in SMRs in a map of Japan. Multiple linear regression was conducted to identify the socioeconomic factors affecting differences in SMR. Statistically significant socioeconomic factors were further assessed by calculating the relative risk of mortality of quintiles of municipalities classified according to the degree of each socioeconomic factor using Poisson regression analysis. Results: The geographic distribution of diabetes mortality differed by gender. Of the municipality-specific socioeconomic factors, high rates of single-person households and unemployment and a high number of hospital beds were associated with a high SMR for men. High rates of fatherless households and blue-collar workers were associated with a high SMR for women, while high taxable income per-capita income and total population were associated with low SMR for women. Quintile analysis revealed a complex relationship between taxable income and mortality for women. The mortality risk of quintiles with the highest and lowest taxable per-capita income was significantly lower than that of the middle-income quintile. Conclusions: Socioeconomic factors of municipalities in Japan were found to affect geographic differences in diabetes mortality.

• Korean Journal of Health Education and Promotion
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• v.20 no.4
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• pp.51-65
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• 2003

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.

• Journal of Preventive Medicine and Public Health
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• v.44 no.6
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• pp.242-248
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• 2011

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.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.8
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• pp.3777-3783
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• 2016

Background: The aim of this study was to evaluate the incidence and mortality of stomach cancer, and its relationship with the Human Development Index (HDI) and its components in Asia in 2012. Materials and Methods: This ecological study wa conducted based on GLOBOCAN project of WHO for Asian countries. We assessed the correlations between standardized incidence rates (SIR) and standardized mortality rates (SMR) of stomach Cancer with HDI and its components using SPSS18. Results: A total of 696,231 cases (68.7% in males and 31.3% in females, ratio of 2.19:1) and 524,465 deaths (67.1% in men and 33.0% in women, ratio 2.03:1) were included in 2012. Five countries with the highest SIR of stomach cancer were Republic Korea, Mongolia, Japan, China and Tajikistan. Five countries with the highest SMR of stomach cancer were Mongolia, Tajikistan, Kyrgyzstan, Kazakhstan and China. Correlation between HDI and SIR was 0.241 (p = 0.106), in men 0.236 (p = 0.114) and in women -0.250 (p = 0.094). Also between HDI and SMR -0.250 (p = 0.871) in men -0.018 (p = 0.903) and in women -0.014 (p = 0.927). Conclusions: No significant correlation was observed between the SIR of stomach cancer, and the HDI and its dimensions, such as life expectancy at birth, mean years of schooling, and income level of the population.