• Asian Pacific Journal of Cancer Prevention
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• 제16권12호
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• pp.5125-5135
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• 2015

Background: Total fat intake may be associated with increased risk of breast cancer, and fish oil has been suggested as a protection factor to breast cancer. But the effect of vegetable oils is inconclusive. We aimed to investigate the association with high vegetable oils consumption and breast cancer risk, and evaluated their dose-response relationship. Design: We systematically searched the MEDLINE, EMBASE, Cochrane databases, and CNKI updated to December 2014, and identified all observational studies providing quantitative estimates between breast cancer risk and different vegetable oils consumption. Fixed or random effect models were used to estimate summary odds ratios for the highest vs. lowest intake, and dose-response relationship was assessed by restricted cubic spline model and generalized least-squares trend (GLST) model. Results: Five prospective cohort studies and 11 retrospective case-control studies, involving 11,161 breast cancer events from more than 150,000 females, met the inclusion criteria. Compared with the lowest vegetable oils consumption, higher intake didn't increased the risk of breast cancer with pooled OR of 0.88 (95% CIs:0.77-1.01), and the result from dose-response analyses didn't show a significant positive or negative trend on the breast cancer risk for each 10g vegetable oil/day increment (OR=0.98, 95% CIs: 0.95-1.01). In the subgroup analyses, the oils might impact on females with different strata of BMI. Higher olive oil intake showed a protective effect against breast cancer with OR of 0.74 (95% CIs: 0.60-0.92), which was not significant among the three cohort studies. Conclusions: This meta-analyses suggested that higher intake of vegetable oils is not associated with the higher risk of breast cancer. Olive oil might be a protective factor for the cancer occurrence among case-control studies and from the whole. Recall bias and imbalance in study location and vegetable oils subtypes shouldn't be ignored. More prospective cohort studies are required to confirm the interaction of the impact of vegetable oils on different population and various cancer characteristic, and further investigate the relationship between different subtype oils and breast cancer.

• Asian Pacific Journal of Cancer Prevention
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• 제16권10호
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• pp.4339-4345
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• 2015

Occupational exposure to wood dust is one cause of nasopharyngeal cancer (NPC); however, assessing this exposure remains problematic. Therefore, the objective of this study was to develop a semi-quantitative exposure assessment method and then utilize it to evaluate the association between occupational exposure to wood dust and the development of NPC. In addition, variations in risk by histology were examined. A case-control study was conducted with 327 newly diagnosed cases of NPC at the National Cancer Institute and regional cancer centers in Thailand with 1:1 controls matched for age, gender and geographical residence. Occupational information was obtained through personal interviews. The potential probability, frequency and intensity of exposure to wood dust were assessed on a job-by-job basis by experienced experts. Analysis was performed by conditional logistic regression and presented in odds ratio (ORs) estimates and 95% confidence intervals (CI). Overall, a non significant relationship between occupational wood dust exposure and NPC risk for all subjects was observed (ORs=1.61, 95%CI 0.99-2.59); however, the risk became significant when analyses focused on types 2 and 3 of NPC (ORs=1.62, 95%CI 1.03-2.74). The significant association was stronger for those exposed to wood dust for > 10 year (ORs=2.26, 95%CI 1.10-4.63), for those with first-time exposure at age > 25 year (ORs=2.07, 95%CI 1.08-3.94), and for those who had a high cumulative exposure (ORs=2.17, 95%CI 1.03-4.58) when compared with those considered unexposed. In conclusion, wood dust is likely to be associated with an increased risk of type 2 or 3 NPC in the Thai population. The results of this study show that semi-quantitative exposure assessment is suitable for occupational exposure assessment in a case control study and complements the information from self-reporting.

• Asian-Australasian Journal of Animal Sciences
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• 제30권3호
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• pp.320-327
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• 2017

Objective: The objective of this research was to estimate genetic correlations between number of piglets born alive in the first parity (NBA1), litter birth weight in the first parity (LTBW1), number of piglets weaned in the first parity (NPW1), litter weaning weight in the first parity (LTWW1), number of piglets born alive from second to last parity (NBA2+), litter birth weight from second to last parity (LTBW2+), number of piglets weaned from second to last parity (NPW2+) and litter weaning weight from second to last parity (LTWW2+), and to identify the percentages of animals (the top 10%, 25%, and 50%) for first parity and sums of second and later parity traits. Methods: The 9,830 records consisted of 2,124 Landrace (L), 724 Yorkshire (Y), 2,650 LY, and 4,332 YL that had their first farrowing between July 1989 and December 2013. The 8-trait animal model included the fixed effects of first farrowing year-season, additive genetic group, heterosis of the sow and the litter, age at first farrowing, and days to weaning (NPW1, LTWW1, NPW2+, and LTWW2+). Random effects were animal and residual. Results: Heritability estimates ranged from $0.08{\pm}0.02$ (NBA1 and NPW1) to $0.29{\pm}0.02$ (NPW2+). Genetic correlations between reproduction traits in the first parity and from second to last parity ranged from $0.17{\pm}0.08$ (LTBW1 and LTBW2+) to $0.67{\pm}0.06$ (LTWW1 and LTWW2+). Phenotypic correlations between reproduction traits in the first parity and from second to last parity were close to zero. Rank correlations between LTWW1 and LTWW2+ estimated breeding value tended to be higher than for other pairs of traits across all replacement percentages. Conclusion: These rank correlations indicated that selecting boars and sows using genetic predictions for first parity reproduction traits would help improve reproduction traits in the second and later parities as well as lifetime productivity in this swine population.

• 한국산학기술학회논문지
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• 제20권12호
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• pp.574-580
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• 2019

본 논문에서는 제주국제자유도시 및 경제자유구역의 경제적 성과를 외국인직접투자(FDI), 지역내총생산(GRDP), 고용률(EPR) 데이터를 이용하여 통계적 검정과 패널분석의 이중차분모형(Difference-In-Difference model)으로 살펴보고, 세 변수의 관계를 지역별 데이터 및 패널 벡터오차수정모형(PVECM: Panel Vector Error Correction Model)을 이용하여 살펴보았다. FDI 신고액 대비 도착액의 비율인 실투자율 연평균증가율의 경우 수도권이 비수도권보다 높게 나타났다. FDI 도착액의 성장과 상대적 규모를 살펴보면 16개 지역 중 7개 지역이 성장도 낮고, 규모도 작은 것으로 나타났다. 통계적 분석 결과 지구지정 전후의 변화에서 2개 지역을 제외하고는 일부 변수에서 통계적으로 유의한 차이가 나타났으나 순수한 지구지정 정책효과인 지를 판단할 수 있는 이중차분 추정치는 통계적 유의성이 없는 것으로 나타났다. 한편, PVECM을 이용하여 세 변수의 상호 관계를 분석해 본 결과 상호 설명력은 상당히 제한적이었으나 수도권 지역보다는 비수도권 지역에서, 광역지역 보다는 시도지역에서 크게 나타났다. 이상의 결과를 종합해 볼 때, FDI 유입이 GRDP 증가 및 고용률 상승 등 지역경제 활성화로 연결될 수 있는 FDI 유치 메커니즘을 구축하는 것이 필요하다고 하겠다.

• 한국농공학회지
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• 제22권3호
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• pp.75-87
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• 1980

Most hydro]ogic phenomena are the complex and organic products of multiple causations like climatic and hydro-geological factors. A certain significant correlation on the run-off in river basin would be expected and foreseen in advance, and the effect of each these causual and associated factors (independant variables; present-month rainfall, previous-month run-off, evapotranspiration and relative humidity etc.) upon present-month run-off(dependent variable) may be determined by multiple regression analysis. Functions between independant and dependant variables should be treated repeatedly until satisfactory and optimal combination of independant variables can be obtained. Reliability of the estimated function should be tested according to the result of statistical criterion such as analysis of variance, coefficient of determination and significance-test of regression coefficients before first estimated multiple regression model in historical sequence is determined. But some error between observed and estimated run-off is still there. The error arises because the model used is an inadequate description of the system and because the data constituting the record represent only a sample from a population of monthly discharge observation, so that estimates of model parameter will be subject to sampling errors. Since this error which is a deviation from multiple regression plane cannot be explained by first estimated multiple regression equation, it can be considered as a random error governed by law of chance in nature. This unexplained variance by multiple regression equation can be solved by stochastic approach, that is, random error can be stochastically simulated by multiplying random normal variate to standard error of estimate. Finally hybrid model on estimation of monthly run-off in nonhistorical sequence can be determined by combining the determistic component of multiple regression equation and the stochastic component of random errors. Monthly run-off in Naju station in Yong-San river basin is estimated by multiple regression model and hybrid model. And some comparisons between observed and estimated run-off and between multiple regression model and already-existing estimation methods such as Gajiyama formula, tank model and Thomas-Fiering model are done. The results are as follows. (1) The optimal function to estimate monthly run-off in historical sequence is multiple linear regression equation in overall-month unit, that is; Qn=0.788Pn+0.130Qn-1-0.273En-0.1 About 85% of total variance of monthly runoff can be explained by multiple linear regression equation and its coefficient of determination (R2) is 0.843. This means we can estimate monthly runoff in historical sequence highly significantly with short data of observation by above mentioned equation. (2) The optimal function to estimate monthly runoff in nonhistorical sequence is hybrid model combined with multiple linear regression equation in overall-month unit and stochastic component, that is; Qn=0. 788Pn+0. l30Qn-1-0. 273En-0. 10+Sy.t The rest 15% of unexplained variance of monthly runoff can be explained by addition of stochastic process and a bit more reliable results of statistical characteristics of monthly runoff in non-historical sequence are derived. This estimated monthly runoff in non-historical sequence shows up the extraordinary value (maximum, minimum value) which is not appeared in the observed runoff as a random component. (3) "Frequency best fit coefficient" (R2f) of multiple linear regression equation is 0.847 which is the same value as Gaijyama's one. This implies that multiple linear regression equation and Gajiyama formula are theoretically rather reasonable functions.

• Journal of Preventive Medicine and Public Health
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• 제35권1호
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• pp.1-12
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• 2002

Objective : To estimate the socioeconomic costs of obesity in Korea,1998. Methods : The 1998 National Health and Nutrition Examination Survey(1998 NHNES) data was used and 10,880 persons who had taken health examinations were selected for study. Essential hypertension, NIDDM(non insulin-dependent diabetes mellitus), dyslipidemia, osteoarthritis, coronary heart disease, stroke were included as obesity related disease. The data of direct costs of obesity was obtained from the National Federation of Medical Insurance. The category of indirect costs was the loss of productivity caused by premature death and admission, time costs, traffic costs, nursing fees due to obesity. Multiple logistic regression model was developed to estimate prevalence odds ratio by obesity class adjusted demographic and socio-ecnomic factors and calculate PAF(Population Attributable Fraction) of obesity on obesity related disease. And we finally calculated the socioeconomic costs of obesity in relation to BMI with PAF. Results : The direct costs of obesity were 2,126 billion${\sim}965$ billion Won in considering out of pocket payment to uninsured services, and the indirect costs of obesity were 2,099 billion${\sim}1,086$ billion Won. Consequently, in considering out of pocket payment to uninsured services, the socioeconomic costs of obesity were 4.225 billion${\sim}2,050$ billion Won, which corresponded to about $0.094%{\sim}0.046%$ of GDP and $1.88%{\sim}0.91$ of total health care costs in Korea. Conclusions : Obesity represents a major health problem with significant economic implications for the society. This results are conservative estimates as far as all obesity related disease and all health care and indirect costs were not included due to missing information. further studies are needed to caculate socioeconomic costs of obesity more exactly.

• Toxicological Research
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• 제6권2호
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• pp.205-213
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• 1990

The regulation of neurotoxicants has usually been based upon setting reference doses by dividing a no observed adverse effect level (NOAEL) by uncertainty factors that theoretically account for interspecies and intraspecies extraploation of experimental results in animals to humans. Recently, we have proposed a four-step alternative procedure which provides quantitative estimates of risk as a function of dose. The first step is to establish a mathematical relationship between a biological effect or biomarker and the dose of chemical administered. The second step is to determine the distribution (variability) of individual measurements of biological effects or their biomarkers about the dose response curve. The third step is to define an adverse or abnormal level of a biological effect or biomarker in an untreated population. The fourth and final step is to combine the information from the first three steps to estimate the risk (proportion of individuals exceeding on adverse or abnormal level of a biological effect or biomarker) as a function of dose. The primary purpose of this report is to enhance the certainty of the first step of this procedure by improving our understanding of the relationship between a biomarker and dose of administered chemical. Several factors which need to be considered include: 1) the pharmacokinetics of the parent chemical, 2) the target tissue concentrations of the parent chemical or its bioactivated proximate toxicant, 3) the uptake kinetics of the parent chemical or metabolite into the target cell(s) and/or membrane interactions, and 4) the interaction of the chemical or metabolite with presumed receptor site(s). Because these theoretical factors each contain a saturable step due to definitive amounts of required enzyme, reuptake or receptor site(s), a nonlinear, saturable dose-response curve would be predicted. In order to exemplify this process, effects of the neurotoxicant, methlenedioxymethamphetamine (MDMA), were reviewed and analyzed. Our results and those of others indicate that: 1) peak concentrations of MDMA and metabolites are ochieved in rat brain by 30 min and are negligible by 24 hr, 2) a metabolite of MDMA is probably responsible for its neurotoxic effects, and 3) pretreatment with monoamine uptake blockers prevents MDMA neurotoxicity. When data generated from rats administerde MDMA were plotted as bilolgical effect (decreases in hippocampal serotonin concentrations) versus dose, a saturation curve best described the observed relationship. These results support the hypothesis that at least one saturable step is involved in MDMA neurotoxicity. We conclude that the mathematical relationship between biological effect and dose of MDMA, the first step of our quantitative neurotoxicity risk assessment procedure, should reflect this biological model information generated from the whole of the dose-response curve.

• Journal of Radiation Protection and Research
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• 제30권4호
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• pp.185-196
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• 2005

의료 목적으로 X선 촬영이나 CT, PET과 같은 진단방사선 피폭은 불가피하지만 선진국에서 의료 방사선이 최대의 인공 피폭원을 구성하고 있고 또 빠르게 증가하는 경향에 있음을 고려하면 의료상 피폭의 특성이나 그 결과로 인한 환자 선량 크기를 이해하는 것은 매우 중요하다. 이에 2002년도를 기준으로 단위 진료행위별 선량과 국내 의료보험 통계자료를 결합하여 방사선 진료절차별 집단선량과 1인당 유효선량 평가하였다. 절차의 유효선량 값은 NRPB 보고서, ICRP 80, MIRDOSE3.1 및 우리가 독립적으로 산출한 자료들로부터 편집하였다. 평가 결과 연간 집단선량은 진단방사선 22880man-Sv, 핵의학 4560man-Sv로서 총 27440 man-Sv로 나타났으며 따라서 인구 4770만 명을 나눈 1인당 연평균 의료상 피폭선량은 0.58mSv였다. 이 집단선량은 2002년 16기의 원전을 가동한 우리나라의 직업상피폭 70man-Sv보다 크게 많다. 특히 CT 촬영만의 집단선량도 9960man-Sv에 이름은 주목할 일이다. 이 결과는 국가의 방사선방호 정책이 의료에서 환자선량 최적화에 보다 주목해야 함을 시사한다.

• 한국임상수의학회지
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• 제24권2호
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• pp.77-81
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• 2007

본 연구는 개에서 심장사상충을 검출하기 위하여 표준검사를 적용하지 않은 상황에서 중합연쇄반응검사 (PCR)의 진단 능력을 평가하였다. 효소면역검사법 (ELISA)과 PCR 검사를 동시에 사용한 경우 PCR 검사의 민감도와 특이도는 두 검사의 조건부 독립을 가정한 상태에서expectation-maximization (EM) 알고리즘을 이용한 최대우도법과 Bayesian 기법으로 두 집단 검사 모형으로 분석하였다 2002-2004년 기간 중 심장사상충검사 결과를 기록한 의무기록에서 무작위로 266개 결과를 추출하여 133개씩 2회의 시험으로 배치하였다. 2회의 분석결과를 종합할 때 EM 알고리즘에서 PCR 검사의 민감도와 특이도는 각각 96.4-96.7%와 97.6-98.8%, Bayesian기법에서는 94.4-94.8h와 97.1-98%로 추정되었다. PCR 검사는 심장사상충을 스크리닝하는 도구로 유용하며, 표준검사를 적용하지 않은 상황에서 진단검사의 특성을 추론하는 방법으로 Bayesian 기법은 매우 유용함을 확인하였다.

• 한국물환경학회지
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• 제23권4호
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• pp.474-481
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• 2007

With population growth, industrialization, and urbanization within the watershed, the hydrologic response changed dramatically, resulting in increases in peak flow with lesser time to peak and total runoff with shortened time of concentration. Infiltration is directly affected by initial soil moisture condition, which is a key element to determine runoff. Influence of the initial soil moisture condition on hydrograph analysis should be evaluated to assess land use change impacts on runoff and non-point source pollution characteristics. The Long-Term Hydrologic Impact Assessment (L-THIA) model has been widely used for the estimation of the direct runoff worldwide. The L-THIA model was applied to the Little Eagle Creek (LEC) watershed and Its estimated direct runoff values were compared with the BFLOW filtered direct runoff values by other researchers. The $R^2$ value Was 0.68 and the Nash-Sutcliffe coefficient value was 0.64. Also, the L-THIA estimates were compared with those separated using optimized $BFI_{max}$ value for the Eckhardt filter. The $R^2$ value and the Nash-Sutcliffe coefficient value were 0.66 and 0.63, respectively. Although these higher statistics could indicate that the L-THIA model is good in estimating the direct runoff reasonably well, the Antecedent Moisture Condition (AMC) was not adjusted in that study, which might be responsible for mismatches in peak flow between the L-THIA estimated and the measured peak values. In this study, the L-THIA model was run with AMC adjustment for direct runoff estimation. The $R^2$ value was 0.80 and the Nash-Sutcliffe coefficient value was 0.78 for the comparison of L-THIA simulated direct runoff with the filtered direct runoff. However there was 42.44% differences in the L-THIA estimated direct runoff and filtered direct runoff. This can be explained in that about 80% of the simulation period is classified as 'AMC I' condition, which caused lower CN values and lower direct runoff estimation. Thus, the coefficients of the equation to adjust CN II to CN I and CN III depending on AMC condition were modified to minimize adjustments impacts on runoff estimation. The $R^2$ and the Nash-Sutcliffe coefficient values increase, 0.80 and 0.80 respectively. The difference in the estimated and filtered direct runoff decreased from 42.44% to 7.99%. The results obtained in this study indicate the AMC needs to be considered for accurate direct runoff estimation using the L-THIA model. Also, more researches are needed for realistic adjustment of the AMC in the L-THIA model.