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논문검색은 역시 페이퍼서치

보건정보통계학회지검색

Journal of Health Informatics and Statistics


  • - 주제 : 의약학분야 > 예방의학및보건학
  • - 성격 : 학술지
  • - 간기: 계간
  • - 국내 등재 : KCI 등재
  • - 해외 등재 : -
  • - ISSN : 2465-8014
  • - 간행물명 변경 사항 : 한국보건통계학회지(~2003) → 한국보건정보통계학회지(2004~)
논문제목
수록 범위 : 43권 2호 (2018)

한국 보훈대상자의 암발생률

박운제 ( Un Je Park ) , 박소희 ( So Hee Park )
4,500
초록보기
목적: 한국의 초고령화 사회로의 진입이 가속화됨에 따라 고령자가 많은 국가 보훈대상자의 진료 및 치료를 담당하는 보훈병원 내의 암 환자 수가 더욱 증가할 것으로 예상되어 우리나라 보훈대상자의 암 발생률을 파악하고자 한다. 방법: 전국 5개의 보훈병원에서 2013년 1월 1일부터 2016년 6월 30일까지의 자료를 바탕으로 2013년도 초진 암발생 환자의 의무기록 자료를 조사하였다. 보훈대상자 암환자의 인구사회학적 특성, 임상적 특성을 규명하고 조발생률 및 연령표준화 발생률을 구하였다. 결과: 2013년 우리나라 보훈대상자 672,532명 중에서 초진 암환자는 2,070명으로 전체 보훈대상자 중 0.3%를 차지하였으며, 보훈대상자 유형별로는 베트남참전유공자가 가장 많았다. 호발 암 원발 부위별로는 전립샘암이 가장 많았고, 다음은 위암, 폐암, 대장·직장암, 간암 순으로 발생하였다. 보훈대상자의 암 발생률에서 조발생률은 307.8명이었으며, 전립샘암이 59.2명으로 가장 많았고, 위암 51.0명, 폐암 50.6명, 대장·직장암 48.2명, 간암이 22.9명으로 뒤를 이었으며, 연령표준화 발생률은 인구 10만 명당 51.1명, 위암 8.9명, 전립샘암 8.8명이었다. 결론: 2013년 보훈대상자 초진 암환자는 2,070명으로 그 중 60세 이상이 97.9%로서 우리나라 일반국민 암환자 60세 이상의 52.8%보다 암 발생률이 약 1.8배 높았다. 이와 같이 우리나라 전체 국민보다 고령 인구의 비율이 훨씬 높은 보훈대상자들의 특성을 고려했을 때 보훈대상자들의 향후 암 발생률이 지속적으로 증가할 것으로 예상한다.

간호대학생의 건강정보 이해능력과 자가간호역량이 건강증진 행위에 미치는 영향

이순영 ( Soon Young Lee ) , 서순림 ( Soon Rim Suh )
4,500
초록보기
Objectives: This study is a descriptive study to survey the nursing college students for their health literacy, self-care agency, and health promoting behavior and to analyze their related factors. Methods: The questionnaire was administered to 228 students in two nursing colleges. Collected data were analyzed using t-test, ANOVA with scheff’e test, and stepwise multiple regression. Results: In this study, nursing students health literacy 14.37±2.00, self-care agency was 158.10±26.62 points, health promotion behavior were 145.67±35.10 points. This result was higher than the previous study. The subjects’ health literacy had a significant positive correlation with self-care agency (r=0.60, p<0.001), a significant positive correlation with health promoting behavior (r=0.25, p<0.001), and self-care agency had a significant positive correlation with health promoting behavior (r=0.39, p<0.001). Regression analysis to identify factors affecting the health promoting behavior showed that self-care agency was the most significant factor (p=0.001), followed by health literacy (p=0.048). In the regression analysis, self-care agency and health literacy were significant predictors and explained 23.0% (p<0.001) of health promoting behavior. Conclusions: Results of this study have suggested that self-care agency and health literacy were significantly related to health promoting behavior in nursing college students. Therefore, in order to improve the health promoting behaviors of nursing college students, it is necessary to improve the health literacy and self-care agency, and the systematic education strategy and education program should be developed and applied.

기저치를 가진 생물학적 동등성 평가의 통계적 고찰: 내인성 제제 사례연구

박상규 ( Sang-gue Park ) , 김상영 ( Sangyoung Kim )
4,500
초록보기
Objectives: To assess bioequivalence between two endogenous drugs in 2 × 2 crossover trial with baseline measurements. Methods: Two statistical methods are applied to assess bioequivalence between two endogenous drugs in 2 × 2 crossover trials. The first method is based on the current regulatory guideline published by Ministry of Food and Drug Safety (MFDS), which is based on the difference between baseline measurements and responses. The second method is more general approach, so-called general linear model method, which is defined the baseline measurements as covariates. Results: The first method based on current guideline shows that two drugs are not bioequivalent; however, the second method by general linear model shows that two drugs are bioequivalent. When the baselines of the subjects are expected to be highly variable, general linear model approach is more suitable to assess the bioequivalence by adjusting high subjects’ variations. Conclusions: General linear model with covariates should be considered in assessing bioequivalence of endogenous substances when highly subject variations of baseline measurements are expected.

딥러닝 기반 앙상블을 이용한 유방암 분류

최도연 ( Do-yeon Choi ) , 정광모 ( Kwang-mo Jeong ) , 임동훈 ( Dong Hoon Lim )
4,500
초록보기
Objectives: We propose a deep learning-based ensemble for improving breast cancer classification and compare it with existing six models including deep neural network on two UCI data. Methods: We propose a deep learning-based stacking ensemble method. We first applied five classifications methods individually, which were k-nearest neighbor, decision trees, support vector machines, discriminant analysis, and logistic regression analysis and then adopt a deep learning to the predictions derived from these methods after using 5-fold cross validation technique. We compared the proposed deep learning-based ensemble method with these methods for two UCI data through classification accuracy, ROC curves and c-statistics. Results: Experimental results for two UCI data showed that the proposed deep learning-based ensemble outperformed single k-nearest neighbor, decision trees, support vector machines discriminant analysis, and logistic regression analysis as well as deep neural network in terms of various performance measures. Conclusions: We proposed deep learning-based ensemble for improving breast cancer classification. The deep learning-based ensemble outperformed existing single models for all applications in terms of various performance measures.

중년여성의 우울에 영향을 미치는 요인: 갱년기 삶의 질을 중심으로

손정남 ( Jung Nam Sohn )
4,500
초록보기
Objectives: The purpose of this study was to identify its influencing factors of depression in middle aged women. Methods: We analyzed cross-sectional data collected from 142 middle aged women by using self-reported questionnaire Korean version of Center for Epidemiologic Studies Depression Scale (CES-D), Menopause-specific Quality of life (MENQOL), Korean Perceived Stress Scale-10 (KPSS-10), Multiple dimensional Scale of Perceived Social Support (MSPSS), and Perceived health status. Data were analyzed stepwise multiple regression with SPSS 19.0. Results: The mean score for depression was 17.45. There were difference of depression scores in marital satisfaction (F=6.15, p=0.001) and quality of sleep (F=8.12, p≤0.001). There were difference of menopausal specific quality of life that were statistically significant in marital satisfaction (F=5.40, p=0.002) and quality of sleep (F=4.20, p=0.003). Depression was correlated with stress (r=0.69, p<0.001), social support (r=0.52, p<0.001), menopausal specific quality of life (r=0.52, p<0.001) and perceived health status (r=-0.44, p<0.001). The factors related to depression were stress (β=0.48, p<0.001), social support (β=-0.25, p<0.001), quality of life on menopause (β=0.18, p<0.001) which explained 56% of the variance reported in depression. Conclusions: The results indicate that these factors influencing depression should be considered when developing integrated intervention program to cope with depression in middle aged women.
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