• Journal of Preventive Medicine and Public Health
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• v.41 no.5
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• pp.300-306
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• 2008

Objectives : This study was performed to compare the standardized mortality ratios among different small areas and to explore the usefulness of standardized mortality ratios in South Korea. Methods : To calculate the standardized mortality ratio (SMR), we obtained the national deaths certificate data (2004-2006) and national registration population data (2003-2006), and these were provided by the National Statistical Office. The small areas (Eup.Myoun.Dong) were based on the subdivisions of counties. Among the 3,580 small areas classified by the National Statistical Office, 3,571 areas were included in this study. The basic statistics and decile distributions of the SMRs for all the regional levels were calculated, and the small area maps were also produced for some selected regions. To evaluate the precision of SMR, we calculated the 95% confidence intervals of the SMR in selected small areas. Results : The mean and the standard deviation of the SMRs among all small areas were 100.8 and 17.0, respectively. The range was 30.6-211.7 and the inter-quartile range was 20.7. Seoul metropolitan city displayed the lowest mean SMR among 16 regions in South Korea, and 34.6 percent of the small area SMRs belonged to the first decile(the lowest group). On the contrary, the mean SMR of Gyeongsangnam province was highest, and 26.1 percent of the small area SMRs belonged to the tenth decile(the highest group). In some areas, the precision of the SMR, which was calculated by the 95% confidence intervals, remained questionable, yet it was quite stable for almost areas. Conclusions : The standardized mortality ratios can be useful for allocating health resources at the small area level in Korea.

• 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.

• 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 Preventive Medicine and Public Health
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• v.44 no.4
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• pp.185-189
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• 2011

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.

• Health Policy and Management
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• v.22 no.2
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• pp.163-182
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• 2012

This study was performed to identify the difference of the area-based deprivation and the educational level on the cerebrovascular mortality in Korea. Data used in this study was obtained from the Death Certificate Data 2000 and the 2000 Census produced by Korean National Statistics(NSO). We classified the whole country into 246 areas based on the administrative districts. Then, the Standardized Mortality Ratio (SMR) in cerebrovascular disease was calculated according to the sex, education level and 246 areas. Its Predicted SMR was calculated by the Empirical Bayes Methods to reduce the variation of the SMR values. The area-based deprivation of 246 areas were measured using the modified Carstairs index in which the 5 indicators consisted of overcrowding, the unemployment ratio of men, the percentage of households classified low social class, the percentage of non home owners, and finally those houses lacking basic amenities. The correlation between the area-based deprivation and the SMR of the whole country and the correlation between the area-based deprivation and the SMR of each metropolitan cities or provinces was analyzed by the Pearson correlation analysis method. After classifying the deprivation of 246 areas into 5 levels, we performed the random intercept Poisson regression analysis after adjusting education level and age using Empirical Bayes Method to investigate the relationship between the 5 deprivation levels and the cerebrovascular mortality. The SMR was increased in lower education level. Each 246 areas had different values in SMR, Predicted SMR and area-based deprivation. The area-based deprivation and the SMR of the whole country was not correlated in both sexes. The education level of an individual was associated the risk of cerebrovascular mortality in men. The risk of cerebrovascular mortality increased with age compared to the reference(<30). The area-based deprivation was not associated with the risk of cerebrovascular in both sexes. The findings of this study suggest that the SMR had positive and negative correlations with area-based deprivation depending on the metropolitan cities or province. It also suggests that the individual education level and age were related with mortality and finally that the area-based deprivation was not associated to the cerebrovascular mortality in Korea.

• Journal of the Korean Geographical Society
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• v.51 no.3
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• pp.367-380
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• 2016

This study reviewed and compared methods for mapping aggregated low birth weight (LBW) and geographic variations in LBW in South Korea. Based on this review, we produced LBW maps in South Korea. Standardized mortality/morbidity ratios (SMRs) and crude mortality rates have been widely used for many years in epidemiological research. However, SMR-based maps are likely to be affected by sample size of unit area. Therefore, this study adopted a model-based approach using Bayesian estimates to reduce noisy variability in the SMR. By using a Bayesian model, we can calculate a statistically reliable RR values. We used the full Bayes estimator, as well as empirical Bayes estimators. As a result, variations in the two Bayes models were similar. The SMR-based statistics had the largest variation. The result maps can be used to identify regions with a high risk of LBW in South Korea.

• 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.

• Journal of Korean Academy of Nursing
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• v.35 no.1
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• pp.47-55
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• 2005

Purpose: This study was to evaluate the validity of the Pediatric Index of Mortality Ⅱ(PIM Ⅱ). Method: The first values on PIM Ⅱ variables following ICU admission were collected from the patient's charts of 548 admissions retrospectively in three ICUs(medical, surgical, and neurosurgical) at P University Hospital and a cardiac ICU at D University Hospital in Busan from January 1, 2002 to December 31, 2003. Data was analyzed with the SPSSWIN 10.0 program for the descriptive statistics, correlation coefficient, standardized mortality ratio(SMR), validity index(sensitivity, specificity, positive predictive value, negative predictive value), and AUC of ROC curve. Result: The mortality rate was 10.9% (60 cases) and the predicted death rate was 9.5%. The correlation coefficient(r) between observed and expected death rates was .929(p<.01) and SMR was 1.15. Se, Sp, pPv, nPv, and the correct classification rate were .80, .96, .70, .98, and 94.0% respectively. In addition, areas under the curve (AUC) of the receiver operating characteristic(ROC) was 0.954 (95% CI=0.919～0.989). According to demographic characteristics, mortality was underestimated in the medical group and overestimated in the surgical group. In addition, the AUCs of ROC curve were generally high in all subgroups. Conclusion: The PIM Ⅱ showed a good, so it can be utilized for the subject hospital. better.

• 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.43 no.2
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• pp.185-192
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• 2010

Objectives: We conducted a meta-analysis to investigate the relationship between low external doses of ionizing radiation exposure and the risk of cancer mortality among nuclear power plant workers. Methods: We searched MEDLINE using key words related to low dose and cancer risk. The selected articles were restricted to those written in English from 1990 to January 2009. We excluded those studies with no fit to the selection criteria and we included the cited references in published articles to minimize publication bias. Through this process, a total of 11 epidemiologic studies were finally included. A publication bias was tested for using Egger's test. The homogeneity test was performed before the integration of each of the standardized mortality ratios (SMRs) and the result proved that the studies were heterogeneous. Results: We found significant decreased deaths from all cancers (SMR = 0.75, 95% CI = 0.62 - 0.90), all cancers excluding leukemia, solid cancer, mouth and pharynx, esophagus, stomach, rectum, liver and gallbladder, pancreas, lung, prostate, lymphopoietic and hematopoitic cancer. The findings of this meta-analysis were similar with those of the 15 Country Collaborative Study conducted by the International Agency for Research on Cancer. A publication bias was found only for liver and gallbladder cancer (p = 0.015). Heterogeneity was observed for all cancers, all cancers excluding leukemia, solid cancer, esophagus, colon and lung cancer. Conclusions: Our findings of low mortality for stomach, rectum, liver and gallbladder cancers may explained by the health worker effect. Yet further studies are needed to clarify the low SMR of cancers, for which there is no useful screening tool, in nuclear power plant workers.