No abstract available.

No abstract available.
Cytomegalovirus Infections* ; Cytomegalovirus*

It is very important to estimate the future medical care expenditure, because medical care expenditure escalation is a big problem not only in the health industry but also in the Korean economy today. This study was designed to project the medical care expenditure in view of population age change. The data of this study were the population projection data based on National Census Data (1990) of the National Statistical Office and the Statistical Reports of the Korea Medical Insurance Corporation. The future medical care expenditure was eatimated by the regression model and the optional simulation model. The significant results are as follows; 1. The future medical care expenditure will be 3,963 billion Won in the year 2000, 4,483 billion Won in 2010, and 4,826 billion Won in 2020, based on the 1990 market price considering only the population age change. 2. The proportion of the total medical care expenditure in the elderly over 65 will be 10. 4% in 2000, 13.5% in 2010, and 16.9% in 2020. 3. The future medical care expenditure will be 4,306 billion Won in the year 2000, 5,1101 billion Won in 2010, and 5, 699 billion Won in 2020 based on the 1990 market price considering the age structure change and the change of the case-cost estimated by the regression model. 4. When we consider the age-structure change and inflation compared with the preceding year, the future medical care expenditurein 2020 will be 21 trillion Won based on a 5% inflation rate, 42 trillion Won based on a 7.5% inflation rate, and 84 trillion Won based on a 10% inflation rate. Consideration of the aged (65 years old and over)will be essential to understand the acute increase of medical care expenditure due to changes in age structure of the population. Therefore, alternative policies and programs for the caring of the aged should be further studied.
Aged ; Censuses ; Population Forecast ; Health Expenditures* ; Humans ; Inflation, Economic ; Insurance ; Korea

No abstract available.
Bone Morphogenetic Proteins*

Total 7,446 pedicle measurements were made from T1 to L6. Direct dimensional measurements were obtained from dried adult human spinal columns. Parsmeters considered were the pedicle isthmus diameter in the coronal and sagittal planes, pedicle angles in the transverse and sagittal planes, and the depth to the anterior cortex in a line parallel to the midline of the vertetral body and along the pedicle axis. The results were as follows. 1. The widest pedicle transverse diameters were seen at L6, the narrowest at T4. 2. The widest pedicle superoinferior diameters were seen at T12, the narrowes at T1. 3. In the transverse plane, the posterolateral to anteromedial pedicle axis orientations were seen at all levels except at T12 and T12. 4. In the sagittal plane, the pedicles angled caudally at L5 and cephaladly from L3 to T1. 5. In the thoracolumbar junction, the percentage less than 6mm in the transverse diameters of pedicles is most high at L1(27%) and followed by at the level L2, T11 and T12. 6. The use of 6mm transpedicular screws can be expected to violate the cortex of the pedicles in a significant number in the upper lumbar spine. 7. The 5mm transpedicular screws can be used safely below the T11 level. 8. It is advisable to use roentgen image intensifier during insertion of the transpedicular screws.
Adult ; Humans ; Lumbar Vertebrae ; Spine

OBJECTIVES: This study was designed to integrate the results of community based studies which assessed a relationship between depression and alcoholism by meta-analysis. METHODS: We identified the previons studies and included in meta-analysis by searching MEDLINE. Overall, 21 results of the studies for relationship between depression and alcoholism were selected for quantitative meta-analysis. Before the integration of the each effect size of the relationship between depression and alcoholism, a homogeneity test was conducted. For the publication bias, we also conducted the analyses of funnel plot, normal quantile plot, rank correlation test and the fail-safe n. RESULTS: We used the random effect model to estimate the overall effect size, because the homogeneity of studies was rejected in a fixed effect model. Our quantitative meta-analysis yielded that integrated odds ratio between depression and alcoholism was 2.42 (95% C.I. 1.98-2.97). From the results of analyses of the publication bias, the probability of publication bias is considered low. CONCLUSION: The published evidences suggested that there may be a significant positive relationship between depression and alcoholism.
Alcoholism* ; Depression* ; Odds Ratio ; Publication Bias

OBJECTIVES: This study was designed to integrate the results of community based studies which assessed a relationship between depression and alcoholism by meta-analysis. METHODS: We identified the previons studies and included in meta-analysis by searching MEDLINE. Overall, 21 results of the studies for relationship between depression and alcoholism were selected for quantitative meta-analysis. Before the integration of the each effect size of the relationship between depression and alcoholism, a homogeneity test was conducted. For the publication bias, we also conducted the analyses of funnel plot, normal quantile plot, rank correlation test and the fail-safe n. RESULTS: We used the random effect model to estimate the overall effect size, because the homogeneity of studies was rejected in a fixed effect model. Our quantitative meta-analysis yielded that integrated odds ratio between depression and alcoholism was 2.42 (95% C.I. 1.98-2.97). From the results of analyses of the publication bias, the probability of publication bias is considered low. CONCLUSION: The published evidences suggested that there may be a significant positive relationship between depression and alcoholism.
Alcoholism* ; Depression* ; Odds Ratio ; Publication Bias

OBJECTIVES: This retrospective cohort study aimed at calculating some parameters of changes in the findings of the subsequent screening mammography (SSM) in female Korean volunteers. METHODS: The study included screenees aged 30 to 79 years who underwent SSM voluntarily after testing negative in the baseline screenings performed between January 2007 and December 2011. A change to a positive result was defined as category 4 or 5 by using the American College of Radiology Breast Imaging Reporting and Data System. The proportion of results that had changed to positive (CP, %) was calculated by dividing the number of cases with results that were positive in the SSM by the total number of study participants. The rate of results that had changed to positive (CR, cases per 100 000 screenee-months) was calculated by dividing the number of cases with results that were positive in the SSM by the total number of months of the follow-up period. RESULTS: The overall CP and CR in all age groups (n=77 908) were 2.26% and 93.94 cases per 100 000 screenee-months, respectively. The median CP interval in the subjects who had positive SSM results was 30 to 36 months, while that in the age group of 30 to 39 years was shorter. CONCLUSIONS: Different screening intervals should be considered among women aged between 30 and 59 years. In addition, a strategy for a screening program should be developed for the age group of 30 to 39 years, in particular.
Adult ; Aged ; Asian Continental Ancestry Group ; Breast Neoplasms/*diagnosis/epidemiology ; Early Detection of Cancer ; Female ; Follow-Up Studies ; Humans ; Incidence ; *Mammography ; Mass Screening ; Middle Aged ; Republic of Korea/epidemiology ; Retrospective Studies ; Women

OBJECTIVES: This retrospective observational study evaluated the distribution of dense breasts by age group among healthy Korean women. METHODS: Participants were women aged 30 years and older who voluntarily underwent screening mammography between January 2007 and December 2011. Women who received the Breast Imaging Reporting and Data System for mammographic density of 3 or 4 were defined as having dense breasts. The proportion of women with dense breasts (PDB, %) was calculated by dividing the number of participants with dense breasts by the total number of participants. RESULTS: Among the 231,058 women who participated, 78.15% were classified as having dense breasts. PDB was highest in the youngest age group (PDB=94.87%) and lowest in the oldest age group. The greatest difference in PDB between adjacent age groups was observed in the group aged 60-64 years. CONCLUSIONS: The results show that the proportion of dense breasts by age group increased in all age groups, except in those aged 35-39 years. These findings suggest an association between the age distribution of dense breasts and trends in breast cancer incidence. Further studies are needed to estimate the change in breast cancer incidence rate by age and the accumulation of fatty breast tissue in Korean women.
Age Distribution ; Breast Neoplasms ; Breast* ; Early Detection of Cancer ; Female ; Humans ; Incidence ; Information Systems ; Mammography* ; Mass Screening* ; Observational Study* ; Retrospective Studies*

OBJECTIVE: To examine the relationship between cigarette smoking, alcohol and cancer mortality in men in the Kangwha cohort after 12 years and 10 months of follow up. METHODS: The subjects consisted of 2,681 men in the Kangwha cohort aged over 55 in 1985. Number of deaths and the time to death from all cancers and other cause were measured and the data for the smoking and drinking habits were obtained from the baseline survey data in 1985. All subjects were categorized into four groups according to their smoking habits: non-smokers, ex-smokers, moderate-smokers (1-19 cigarettes per day), heavy-smokers (> or =20 cigarettes per day). In addition, they were also categorized according to their drinking habits: non-drinkers, light-drinkers (< or =1 drink per week), moderate-drinkers (<3 drinks per day), heavy-drinkers (> or =3 drinks per day). The cancer specific death rates were calculated according to their smoking and drinking status. The adjusted risk ratio for all cancer deaths according to their smoking and drinking status were estimated using the Cox's proportional hazard regression model. RESULTS: Using nonsmokers as the reference category, the adjusted risk ratio for all cancer deaths were 1.573(95% CI=1.003-2.468) for heavy-smokers. For lung cancer deaths, the adjusted risk ratios were 3.540(95% CI=1.251-10.018) for moderate-smoker and 4.114(95% CI=1.275-13.271) for heavy-smokers. Compared to non-drinkers, the adjusted risk ratio for stomach cancer was 2.204(95% CI=1.114-4.361) for light-drinkers. CONCLUSION: Smoking is the most significant risk factor for cancer deaths particularly lung cancer.
Alcohols ; Cohort Studies* ; Surveys and Questionnaires ; Drinking ; Follow-Up Studies ; Humans ; Lung Neoplasms ; Male ; Mortality* ; Odds Ratio ; Risk Factors ; Smoke ; Smoking* ; Stomach Neoplasms ; Tobacco Products*