OBJECTIVES: The objective of this study was to assess the relationship between systolic and diastolic blood pressure (SBP, DBP) and the risk of death from specific causes other than cardiovascular diseases. METHODS: We calculated the risk of specific death by SBP and DBP categories for 506 508 health examinees in 2002-2003 using hazard ratios (HRs) and 95% confidence intervals (CIs) in a Cox proportional hazards model. RESULTS: Compared to normal levels (SBP < 120 or DBP < 90 mmHg), stage I systolic and diastolic hypertension (SBP 140-159, DBP 85- 89 mmHg, respectively) were associated with an increased risk of death from diabetes mellitus, alcoholic liver disease, and renal failure (HR, 1.83; 95% CI, 1.51 to 2.22; HR, 1.24; 95% CI, 1.06 to 1.46; HR, 2.30; 95% CI, 1.64 to 3.21; HR, 1.67; 95% CI, 1.27 to 2.20; HR, 1.99; 95% CI, 1.41 to 2.81; HR, 1.31; 95% CI, 0.99 to 1.73, respectively), but a decreased risk of death from intestinal pneumonia (HR, 0.64; 95% CI, 0.42 to 0.98; HR, 0.59; 95% CI, 0.39 to 0.91). Only stage II systolic hypertension (SBP ≥160 mmHg) was associated with an increased risk of death from pneumonia, liver cirrhosis, and intestinal ischemia (HR, 1.54; 95% CI, 1.19 to 1.98; HR, 1.46; 95% CI, 1.00 to 2.15; HR, 3.77; 95% CI, 1.24 to 11.40, respectively), and stage I and II diastolic hypertension (SBP 140-159 and ≥160 mmHg) were associated with an increased risk of death from intestinal ischemia (HR, 3.07; 95% CI, 1.27 to 7.38; HR, 4.39; 95% CI, 1.62 to 11.88, respectively). CONCLUSIONS: An increase in blood pressure levels may alter the risk of death from certain causes other than cardiovascular diseases, a well-known outcome of hypertension, although the mechanism of these associations is not well documented.
Adult* ; Blood Pressure* ; Cardiovascular Diseases ; Cohort Studies* ; Diabetes Mellitus ; Humans ; Hypertension ; Ischemia ; Liver Cirrhosis ; Liver Diseases, Alcoholic ; Pneumonia ; Proportional Hazards Models ; Renal Insufficiency

Objectives: This study aimed to identify the social and policy determinants of coronavirus disease 2019 (COVID-19) infection across 23 countries. Methods: COVID-19 indicators (incidence, mortality, and fatality) for each country were calculated by direct and indirect standardization. Multivariable regression analyses were used to identify the social and policy determinants of COVID-19 infection. Results: A higher number of doctors per population was related to lower incidence, mortality, and fatality rates of COVID-19 in 23 countries (β=-0.672, -0.445, and -0.564, respectively). The number of nurses/midwives per population was associated with lower mortality and fatality rates of COVID-19 in 23 countries (β=-0.215 and -0.372, respectively). Strengthening of policy restriction indicators, such as restrictions of public gatherings, was related to lower COVID-19 incidence (β=-0.423). A national Bacillus Calmette–Guérin vaccination policy conducted among special groups or in the past was associated with a higher incidence of COVID-19 in 23 countries (β=0.341). The proportion of the elderly population (aged over 70 years) was related to higher mortality and fatality rates (β=0.209 and 0.350, respectively), and income support was associated with mortality and fatality rates (β=-0.362 and -0.449, respectively). Conclusions These findings do not imply causality because this was a country-based correlation study. However, COVID-19 transmission can be influenced by social and policy determinants such as integrated health systems and policy responses to COVID-19. Various social and policy determinants should be considered when planning responses to COVID-19.

PURPOSE: Few studies investigated roles of body mass index (BMI) on gastric cancer (GC) risk according to Helicobacter pylori infection status. This study was conducted to evaluate associations between BMI and GC risk with consideration of H. pylori infection information. MATERIALS AND METHODS: We performed a case-cohort study (n=2,458) that consists of a subcohort, (n=2,193 including 67 GC incident cases) randomly selected from the Korean Multicenter Cancer Cohort (KMCC) and 265 incident GC cases outside of the subcohort. H. pylori infection was assessed using an immunoblot assay. GC risk according to BMI was evaluated by calculating hazard ratios (HRs) and their 95% confidence intervals (95% CIs) using weighted Cox hazard regression model. RESULTS: Increased GC risk in lower BMI group (< 23 kg/m²) with marginal significance, (HR, 1.32; 95% CI, 0.98 to 1.77) compared to the reference group (BMI of 23-24.9 kg/m²) was observed. In the H. pylori non-infection, both lower (< 23 kg/m²) and higher BMI (≥ 25 kg/m²) showed non-significantly increased GC risk (HR, 10.82; 95% CI, 1.25 to 93.60 and HR, 11.33; 95% CI, 1.13 to 113.66, respectively). However, these U-shaped associations between BMI and GC risk were not observed in the group who had ever been infected by H. pylori. CONCLUSION: This study suggests the U-shaped associations between BMI and GC risk, especially in subjects who had never been infected by H. pylori.
Body Mass Index ; Cohort Studies ; Helicobacter pylori ; Helicobacter ; Stomach Neoplasms

Objectives: This study aimed to identify the current patterns of cancer incidence and estimate the projected cancer incidence and mortality between 2020 and 2035 in Korea. Methods: Data on cancer incidence cases were extracted from the Korean Statistical Information Service from 2000 to 2017, and data on cancer-related deaths were extracted from the National Cancer Center from 2000 to 2018. Cancer cases and deaths were classified according to the International Classification of Diseases, 10th edition. For the current patterns of cancer incidence, age-standardized incidence rates (ASIRs) and age-standardized mortality rates were investigated using the 2000 mid-year estimated population aged over 20 years and older. A joinpoint regression model was used to determine the 2020 to 2035 trends in cancer. Results: Overall, cancer cases were predicted to increase from 265 299 in 2020 to 474 085 in 2035 (growth rate: 1.8%). The greatest increase in the ASIR was projected for prostate cancer among male (7.84 vs. 189.53 per 100 000 people) and breast cancer among female (34.17 vs. 238.45 per 100 000 people) from 2000 to 2035. Overall cancer deaths were projected to increase from 81 717 in 2020 to 95 845 in 2035 (average annual growth rate: 1.2%). Although most cancer mortality rates were projected to decrease, those of breast, pancreatic, and ovarian cancer among female were projected to increase until 2035. Conclusions These up-to-date projections of cancer incidence and mortality in the Korean population may be a significant resource for implementing cancer-related regulations or developing cancer treatments.

One of the primary goals of epidemiology is to quantify various aspects of a population’s health, illness, and death status and the determinants (or risk factors) thereof by calculating health indicators that measure the magnitudes of various conditions. There has been some confusion regarding health indicators, with discrepancies in usage among organizations such as the World Health Organization the, Centers for Disease Control and Prevention (CDC), and the CDC of other countries, and the usage of the relevant terminology may vary across papers. Therefore, in this review, we would like to propose appropriate terminological definitions for health indicators based on the most commonly used meanings and/or the terms used by official agencies, in order to bring clarity to this area of confusion. We have used appropriate examples to make each health indicator easy for the reader to understand. We have included practical exercises for some health indicators to help readers understand the underlying concepts.
Centers for Disease Control and Prevention (U.S.) ; Epidemiology ; Exercise ; Reproduction ; World Health Organization

One of the primary goals of epidemiology is to quantify various aspects of a population’s health, illness, and death status and the determinants (or risk factors) thereof by calculating health indicators that measure the magnitudes of various conditions. There has been some confusion regarding health indicators, with discrepancies in usage among organizations such as the World Health Organization the, Centers for Disease Control and Prevention (CDC), and the CDC of other countries, and the usage of the relevant terminology may vary across papers. Therefore, in this review, we would like to propose appropriate terminological definitions for health indicators based on the most commonly used meanings and/or the terms used by official agencies, in order to bring clarity to this area of confusion. We have used appropriate examples to make each health indicator easy for the reader to understand. We have included practical exercises for some health indicators to help readers understand the underlying concepts.

BACKGROUND: This study aimed to evaluate the current overall preventable trauma death rate (PTDR) in Korea and identify factors associated with preventable trauma death (PTD). METHODS: The target sample size for review was designed to be 1,131 deaths in 60 emergency medical institutions nationwide. The panels for the review comprised trauma specialists working at the regional trauma centers (RTCs); a total of 10 teams were formed. The PTDR and factors associated with PTD were analyzed statistically. RESULTS: Of the target cases, 943 were able to undergo panel review and be analyzed statistically. The PTDR was 30.5% (6.1% preventable and 24.4% possibly preventable). Those treated at a RTC showed a significantly lower PTDR than did those who were not (21.9% vs. 33.9%; P = 0.002). The PTDR was higher when patients were transferred from other hospitals than when they directly visited the last hospital (58.9% vs. 28.4%; P = 0.058; borderline significant). The PTDR increased gradually as the time from accident to death increased; a time of more than one day had a PTDR 14.99 times higher than when transferred within one hour (95% confidence interval, 4.68 to 47.98). CONCLUSION: Although the PTDR in Korea is still high compared to that in developed countries, it was lower when the time spent from the accident to the death was shorter and the final destined institution was the RTC. To reduce PTDR, it is necessary to make an effort to transfer trauma patients to RTCs directly within an appropriate time.
Developed Countries ; Emergencies ; Humans ; Korea ; Mortality ; Sample Size ; Specialization ; Trauma Centers ; Wounds and Injuries