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    μ‹œνŠΈλ₯΄μ‚° 회둜 단일 μ—ΌκΈ° λ‹€ν˜•μ„± 및 ν™˜κ²½μš”μΈ κ°„ μƒν˜Έμž‘μš©κ³Ό λŒ€μž₯μ•” λ°œμƒ μœ„ν—˜ 탐색

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    ν•™μœ„λ…Όλ¬Έ (박사) -- μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› : μ˜κ³ΌλŒ€ν•™ μ˜ν•™κ³Ό, 2021. 2. μ‹ μ• μ„ .Colorectal cancer is one of the most common malignancies worldwide. Risk factors for the development of colorectal cancer include major contributors to energy balance, such as obesity and reduced physical activity. Based on these findings, physical activity, weight loss, and a healthy diet are recommended for the prevention of colorectal cancer. Even though there are individual differences in preventive effects, changes in lifestyle can affect cancer development with respect to metabolism in both the human body and cells. This study aimed to evaluate the association between genetic variants in the mitochondrial citric acid cycle and colorectal cancer to augment the explanation regarding individual differences in energy metabolism as genetic polymorphisms of mitochondria, which has a central role in the energy metabolism at the cellular level. Interactions of single nucleotide polymorphisms (SNPs) in genes of the citric acid cycle with obesity, physical activity, and energy intake on colorectal cancer were also assessed. Furthermore, pairwise SNP-SNP interactions were examined to account for some missing heritability. Data from the UK Biobank study were used. The study participants comprised of 3,523 colorectal cancer cases and matched 10,522 controls. Obesity was defined using body mass index (BMI) and waist-to-hip ratio (WHR). The participants were classified as obese if BMI is greater than or equal to 30 and severely obese if BMI is greater than or equal to 40. Participants with abdominal obesity were defined as men with a WHR > 0.9 and women with a WHR > 0.85. Participants who had excess energy intake were classified as having an estimated daily energy consumption of more than 2,000 kcal per day for women and 2,500 for men. Participants who performed over 150 minutes of moderate physical activity or 75 minutes of vigorous physical activity throughout the week were classified as those who achieved physical activity for general health benefits. The main effects of the citric acid cycle SNPs were evaluated in the codominant, dominant, and additive models. Odds ratios (ORs) and 95% confidence intervals (95% CIs) for colon and rectal cancer were estimated using a conditional logistic regression model. The false discovery rate was used to correct multiple comparisons. SUCLG2-rs35494829 was associated with a decreased risk of colon cancer in the dominant model (OR [95% CI]: 0.82 [0.74–0.92]) and additive model (0.82 [0.74–0.92]). The association between SUCLG2-rs35494829 and colon cancer was statistically significant after correcting for multiple comparisons (p=0.0206). The interaction between SDHC-rs17395595 and obesity for colon cancer was found (pinteraction=0.0023), and the significance of this interaction remained after correcting multiple comparisons (corrected pinteraction=0.047). Pairwise SNP-SNP interactions were also evaluated using the attributable proportion (AP) owing to interaction. Negative AP between the citric acid cycle SNPs for colon and rectal cancer with statistical significance is shown as follows. However, the P values did not reach statistical significance. This study found a significant association between SUCLG2-rs35494829 and colon cancer. A significant interaction between SDHC-rs17395595 and obesity in colon cancer was also shown. This study evaluated the citric acid cycle SNPs, which were nonsynonymous SNPs or SNPs at a splicing site, as a functional candidate locus of the citric acid cycle in colorectal cancer. The findings in this study suggest that obesity could alter the association between variants in the citric acid cycle and colorectal cancer and may provide new insights into the genetic susceptibility and molecular mechanisms of obesity and the citric acid cycle on colorectal cancer.λŒ€μž₯암은 μ„Έκ³„μ μœΌλ‘œ ν”ν•œ 암쒅이닀. λŒ€μž₯μ•” λ°œμƒμ˜ μœ„ν—˜μš”μΈμœΌλ‘œλŠ” λΉ„λ§Œ, μ‹ μ²΄ν™œλ™ κ°μ†Œ 등이 있고, 이듀은 μ—λ„ˆμ§€ κ· ν˜•μ— 크게 κΈ°μ—¬ν•˜λŠ” μš”μΈμ΄κΈ°λ„ ν•˜λ‹€. λ³Έ μ—°κ΅¬λŠ” 세포 μˆ˜μ€€μ—μ„œ μ—λ„ˆμ§€ λŒ€μ‚¬μ— 쀑심적인 역할을 ν•˜λŠ” λ―Έν† μ½˜λ“œλ¦¬μ•„μ˜ μœ μ „μ  λ‹€ν˜•μ„±μœΌλ‘œμ„œ μ—λ„ˆμ§€ λŒ€μ‚¬μ˜ κ°œλ³„ 차이에 λŒ€ν•œ μ„€λͺ…을 κ°•ν™”ν•˜κΈ° μœ„ν•΄ λ―Έν† μ½˜λ“œλ¦¬μ•„ μ‹œνŠΈλ₯΄μ‚° μ‚¬μ΄ν΄μ˜ μœ μ „μ  변이와 λŒ€μž₯μ•” μ‚¬μ΄μ˜ 연관성을 ν‰κ°€ν•˜λŠ” 것을 λͺ©ν‘œλ‘œ ν•œλ‹€. λŒ€μž₯μ•” λ°œμƒ μœ„ν—˜μ— λŒ€ν•œ μ‹œνŠΈλ₯΄μ‚° μ‚¬μ΄ν΄μ˜ μœ μ „μžμ— μžˆλŠ” 단일 μ—ΌκΈ° λ‹€ν˜•μ„±(single nucleotide polymorphism, SNP)와 λΉ„λ§Œ, 신체 ν™œλ™, μ—λ„ˆμ§€ μ„­μ·¨ κ°„ μƒν˜Έμž‘μš©λ„ ν‰κ°€ν•˜μ˜€λ‹€. λ˜ν•œ, μ‹œνŠΈλ₯΄μ‚° μ‚¬μ΄ν΄μ˜ SNP-SNP κ°„ μƒν˜Έμž‘μš©λ„ ν‰κ°€ν•˜μ˜€λ‹€. λ³Έ μ—°κ΅¬λŠ” UK Biobank μ—°κ΅¬μ˜ 데이터λ₯Ό μ‚¬μš©ν•˜μ˜€λ‹€. 연ꡬ μ°Έμ—¬μžλ“€μ€ 3,523λͺ…μ˜ λŒ€μž₯μ•” ν™˜μžμ™€, ν™˜μžκ΅°μ— λŒ€ν•΄ λ§€μΉ­ν•œ 10,522λͺ…μ˜ λŒ€μ‘°κ΅°μ„ ν¬ν•¨ν•œλ‹€. λΉ„λ§Œμ€ μ²΄μ§ˆλŸ‰μ§€μˆ˜(body mass index, BMI)와 ν—ˆλ¦¬ λŒ€ 엉덩이 λ‘˜λ ˆ λΉ„(waist to hip ratio, WHR)λ₯Ό μ‚¬μš©ν•˜μ—¬ μ •μ˜λ˜μ—ˆλ‹€. μ°Έκ°€μžλ“€μ˜ BMIκ°€ 30보닀 ν¬κ±°λ‚˜ κ°™μœΌλ©΄ λΉ„λ§ŒμœΌλ‘œ, BMIκ°€ 40보닀 크면 쀑증 λΉ„λ§ŒμœΌλ‘œ λΆ„λ₯˜λλ‹€. λ³΅λΆ€λΉ„λ§Œμ€ WHR이 λ‚¨μ„±μ—μ„œ 0.9 이상, μ—¬μ„±μ—μ„œ 0.85 μ΄μƒμœΌλ‘œ μ •μ˜ν•˜μ˜€λ‹€. μ—λ„ˆμ§€ μ„­μ·¨λŸ‰μ΄ ꢌ고된 양보닀 초과된 μ°Έκ°€μžλŠ” μ—¬μ„±μ˜ 경우 ν•˜λ£¨ μ—λ„ˆμ§€ μ†ŒλΉ„λŸ‰μ΄ 2,000 kcal 이상, 남성은 2,500 kcal 이상인 κ²ƒμœΌλ‘œ μ •μ˜ν–ˆλ‹€. 150λΆ„ μ΄μƒμ˜ μ λ‹Ήν•œ μ‹ μ²΄ν™œλ™ λ˜λŠ” 75λΆ„ μ΄μƒμ˜ ν™œλ°œν•œ μ‹ μ²΄ν™œλ™μ„ 일주일 λ‚΄λ‚΄ μˆ˜ν–‰ν•œ μ°Έκ°€μžλŠ” 일반적인 건강상 이읡을 μœ„ν•΄ μ‹ μ²΄ν™œλ™μ„ λ‹¬μ„±ν•œ μ°Έκ°€μžλ‘œ λΆ„λ₯˜λ˜μ—ˆλ‹€. λŒ€μž₯암에 λŒ€ν•œ μ‹œνŠΈλ₯΄μ‚° 사이클 SNP의 effect sizeλŠ” codominant, dominant 및 additive model을 κ°€μ •ν•˜μ—¬ ν‰κ°€ν•˜μ˜€λ‹€. λŒ€μž₯μ•”κ³Ό 직μž₯암에 λŒ€ν•œ μ˜€μ¦ˆλΉ„(odds ratio, OR)와 95% μ‹ λ’° ꡬ간(95% confidence intervals, 95% CIs)은 쑰건뢀 λ‘œμ§€μŠ€ν‹± νšŒκ·€ λͺ¨ν˜•μ„ μ‚¬μš©ν•˜μ—¬ μΆ”μ •ν•˜μ˜€λ‹€. 닀쀑 비ꡐλ₯Ό λ³΄μ •ν•˜κΈ° μœ„ν•΄ false discovery rateλ₯Ό μ‚¬μš©ν•˜λ‹€. SUCLG2-rs35494829λŠ” dominant model (OR [95% CI]: 0.82 [0.74–0.92]) 및 additive model(0.82 [0.74–0.92)μ—μ„œ λŒ€μž₯μ•”μ˜ μœ„ν—˜ κ°μ†Œμ™€ 관련이 μžˆμ—ˆλ‹€. 닀쀑 비ꡐ에 λŒ€ν•œ 보정을 ν•œ 후에도 SUCLG2-rs35494829와 λŒ€μž₯μ•” μ‚¬μ΄μ˜ 연관성은 ν†΅κ³„μ μœΌλ‘œ μœ μ˜ν–ˆλ‹€(p=0.0206). SDHC-rs17395595와 λŒ€μž₯암에 λŒ€ν•œ λΉ„λ§Œ μ‚¬μ΄μ˜ κ΅ν˜Έμž‘μš©μ΄ λ°œκ²¬λ˜μ—ˆμœΌλ©°(p for interaction =0.0023), 닀쀑 비ꡐλ₯Ό κ΅μ •ν•œ 후에도 이 κ΅ν˜Έμž‘μš©μ˜ μœ μ˜μ„±μ€ 남아 μžˆμ—ˆλ‹€(p for interaction=0.047). pairwise SNP-SNP κ΅ν˜Έμž‘μš©μ€ κ΅ν˜Έμž‘μš©μœΌλ‘œ μΈν•œ κΈ°μ—¬ λΆ„μœ¨ (attributable proportion of disease due to interaction with both exposures, AP)을 μ‚¬μš©ν•˜μ—¬ ν‰κ°€ν–ˆλ‹€. ν†΅κ³„μ μœΌλ‘œ μœ μ˜ν•œ λŒ€μž₯μ•”κ³Ό 직μž₯암에 λŒ€ν•œ μ‹œνŠΈλ₯΄μ‚° μ£ΌκΈ° SNP μ‚¬μ΄μ˜ 음의 APλ₯Ό κ΄€μ°°ν•  수 μžˆμ—ˆμ§€λ§Œ, ν†΅κ³„μ μœΌλ‘œ μœ μ˜ν•˜μ§€ μ•Šμ•˜λ‹€. λ³Έ μ—°κ΅¬μ—μ„œ SUCLG2-rs35494829와 λŒ€μž₯μ•” μ‚¬μ΄μ˜ μœ μ˜λ―Έν•œ 연관성을 λ°œκ²¬ν•  수 μžˆμ—ˆλ‹€. λ˜ν•œ, SDHC-rs17395595와 λŒ€μž₯μ•”μ˜ λΉ„λ§Œ μ‚¬μ΄μ˜ μœ μ˜ν•œ μƒν˜Έμž‘μš©λ„ κ΄€μ°°ν•  수 μžˆμ—ˆλ‹€. 이 μ—°κ΅¬μ˜ κ²°κ³Όλ₯Ό 톡해, λŒ€μž₯μ•” λ°œμƒμ— λŒ€ν•œ λΉ„λ§Œκ³Ό μ‹œνŠΈλ₯΄μ‚° 회둜의 λΆ„μž λ©”μ»€λ‹ˆμ¦˜μ— λŒ€ν•œ μƒˆλ‘œμš΄ κ·Όκ±°λ₯Ό μ œμ‹œν•˜κ³ μž ν•œλ‹€.Abstract i Contents v List of Tables viii List of Figures xi 1. Introduction 1 1.1. Colorectal cancer epidemiology 1 1.2. Well-known risk factors for colorectal cancer 4 1.2.1. Obesity 4 1.2.2. Physical inactivity 4 1.2.3. Energy intake 5 1.3. Cell metabolism as a contributor to energy balance 7 1.4. The mitochondria play a major role in energy metabolism 8 1.5. Mitochondrial citric acid cycle as a biomarker for cancer 10 1.6. Previous studies on the interaction of obesity, physical activity, and energy intake with genetic factors on cancer risk and SNP-SNP interaction in colorectal cancer 11 1.6.1. Previous studies on the interaction of obesity, physical activity, and energy intake with genetic factors in cancer 12 1.6.2. Previous studies on SNP-SNP interactions in colorectal cancer 17 2. Research objectives 27 3. Materials and methods 28 3.1. Study population 28 3.2. Data collection and measurements 29 3.3. Outcome ascertainment 33 3.4. Case and control selection 34 3.5. Genotyping 36 3.6. Marker selection 37 3.7. Statistical analysis 43 4. Results 46 4.1. Characteristics of participants 46 4.2. Citric acid cycle polymorphisms involved in the risk for colon and rectal cancer development 52 4.3. Interaction of the citric acid cycle polymorphisms with obesity, physical activity, and energy intake on the risk of colorectal cancer development 61 4.4. Pairwise SNP-SNP interactions of SNPs within the Citric acid cycle on the risk of colorectal cancer 66 5. Discussion 73 5.1. Previous studies on polymorphisms of the citric acid cycle 77 5.2. Mechanisms of the citric acid cycle for colorectal cancer 84 6. Conclusions 87 7. References 89Docto

    λŒ€μ‚¬μ μœΌλ‘œ κ±΄κ°•ν•œ λΉ„λ§Œκ³Ό λ§Œμ„± μ‹ κΈ°λŠ₯ μ €ν•˜ λ°œμƒ μœ„ν—˜ κ°„μ˜ μ—°κ΄€μ„±

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    ν•™μœ„λ…Όλ¬Έ (석사)-- μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› : λ³΄κ±΄λŒ€ν•™μ› 보건학과(보건학전곡), 2018. 8. 쑰성일.Introduction: Chronic kidney disease (CKD), known as a global public health problem, has also become important issues threatening public health in Korea. Many epidemiological studies have investigated the association between obesity and kidney disease, supporting that obesity increases the risk of kidney disease. It has been known that most of the increased risk of CKD in obese individuals is primarily due to cardiometabolic factors associated with excess adiposity. However, not all the obese people have metabolic abnormality, and obese people with no metabolic dysfunction have been existed. They have been reported as metabolically healthy obesity (MHO) phenotype. The association between MHO and kidney dysfunction is well unknown, and it is yet to be determined whether MHO is associated with kidney dysfunction. The objective of this study is to investigate the association between MHO and the risk of incident chronic kidney dysfunction for general population of Korea. Methods: From the Ansung and Ansan community cohort of the Korean Genome and Epidemiology Study (KoGES) data, 8,608 participants were analyzed. The main exposure of this study is MHO. This concept is a combination of metabolic phenotype and the presence or absence of obesity. The participants were divided into four groups based on the body mass index (β‰₯28kg/㎑ as obesity) and the metabolic healthy status by using Adult Treatment Panel-β…’ (ATP-β…’): Metabolically healthy non-obesity (MHNO), Metabolically healthy obesity (MHO), Metabolically unhealthy non-obesity (MUNO), and metabolically unhealthy obesity (MUO). The outcome of the present study is kidney dysfunction defined as eGFR <60ml/min/1.73㎑. To control the potential confounding, socio-demographic variables, behavioral factors, and biochemical factors were adjusted. Cox proportional hazard regression was used to calculate the hazard ratio (HR) with 95% confidence interval (CI) and MHNO is used as the reference. All statistical analyzes are done by using R 3.4.3. Results: The MHO phenotype represented 4.1% (n=351) of the total analytic sample and 29.9% of the obese population. After adjusting for all covariates, the HR of MHO individuals for incident kidney dysfunction was 1.59 (95% CI, 1.24-2.04), the HR of MUNO individuals was 1.69 (95% CI, 1.51-1.89), and the HR of MUO individuals was 2.03 (95% CI, 1.73-2.38). The HRs of all groups were statistically significant higher, compared MHNO individuals, and presented a linear trend, in order of linearity: MHO, MUNO, MUO. Conclusion: This study indicated that metabolically healthy obesity may increase the risk of incident kidney dysfunction in Korean adults. We suggest that different obese phenotype have different effect on the risk of incident kidney dysfunction and MHO is not a benign condition. Therefore, it is crucial to identify obesity-metabolic status phenotype in predicting kidney dysfunction incidence risk. Moreover, the proper prevention and treatment of chronic disease including CKD according to the obesity subtype are needed.Chapter 1. INTRODUCTION 1 1.1 Background 1 1.2 Literature Review 4 1.3 Objective 7 Chapter 2. METHODS 8 2.1 Study population 8 2.2 Measurement 10 2.3 Study design 16 2.4 Statistical analysis 17 Chapter 3. RESULTS 18 3.1 Descriptive analysis of the study participants 18 3.2 Association between metabolically healthy obesity and kidney dysfunction 28 3.3 Association between metabolically healthy obesity and kidney dysfunction stratified by sex 32 3.4 Association between metabolically healthy obesity and kidney dysfunction stratified by age group 35 3.5 Association between metabolically healthy obesity and kidney dysfunction stratified by hypertension 39 Chapter 4. DISCUSSION AND CONCLUSION 42 4.1 Discussion 42 4.2 Conclusion 47 REFERENCES 48 ABSTRACT IN KOREAN 53Maste

    μ€‘μ†ŒκΈ°μ—… S-OJTν›ˆλ ¨κ°€μ˜ ν—Œμ‹ κ³Ό μ—…λ¬΄λΆ€ν•˜, 보상 및 자율적 μ§λ¬΄λ™κΈ°μ˜ 관계

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    ν•™μœ„λ…Όλ¬Έ (석사)-- μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› : λ†μ‚°μ—…κ΅μœ‘κ³Ό, 2015. 2. λ‚˜μŠΉμΌ.이 μ—°κ΅¬μ˜ λͺ©μ μ€ μ€‘μ†ŒκΈ°μ—… S-OJTν›ˆλ ¨κ°€μ˜ ν—Œμ‹ κ³Ό μ—…λ¬΄λΆ€ν•˜, 보상(물질적, μ‚¬νšŒκ΄€κ³„μ , 직무적), 자율적 μ§λ¬΄λ™κΈ°μ˜ 관계λ₯Ό ꡬλͺ…ν•˜λŠ”λ° μžˆμ—ˆλ‹€. 이λ₯Ό μœ„ν•œ ꡬ체적인 연ꡬ λ¬Έμ œλŠ” 첫째, μ€‘μ†ŒκΈ°μ—… S-OJTν›ˆλ ¨κ°€μ˜ ν—Œμ‹ μ— λ―ΈμΉ˜λŠ” μ—…λ¬΄λΆ€ν•˜, 보상(물질적, μ‚¬νšŒκ΄€κ³„μ , 직무적), 자율적 μ§λ¬΄λ™κΈ°μ˜ 영ν–₯을 ꡬλͺ…ν•˜κ³ , λ‘˜μ§Έ, μ€‘μ†ŒκΈ°μ—… S-OJTν›ˆλ ¨κ°€μ˜ ν—Œμ‹ κ³Ό μ—…λ¬΄λΆ€ν•˜μ˜ κ΄€κ³„μ—μ„œ 보상(물질적, μ‚¬νšŒκ΄€κ³„μ , 직무적)이 ν—Œμ‹ μ— λŒ€ν•œ μ—…λ¬΄λΆ€ν•˜μ˜ λΆ€μ μ˜ν–₯을 μ™„ν™”ν•˜λŠ” 쑰절효과λ₯Ό κ°€μ§€λŠ”μ§€ ꡬλͺ…ν•˜λ©°, μ…‹μ§Έ, μ€‘μ†ŒκΈ°μ—… S-OJTν›ˆλ ¨κ°€μ˜ ν—Œμ‹ κ³Ό 보상(물질적, μ‚¬νšŒκ΄€κ³„μ , 직무적)의 κ΄€κ³„μ—μ„œ 자율적 직무동기가 쑰절효과λ₯Ό κ°€μ§€λŠ”μ§€λ₯Ό ꡬλͺ…ν•˜λŠ” κ²ƒμ΄μ—ˆλ‹€. μ—°κ΅¬μ˜ λͺ¨μ§‘단은 ν•œκ΅­μ‚°μ—…μΈλ ₯κ³΅λ‹¨μ—μ„œ μ§€μ›ν•˜κ³  μžˆλŠ” 체계적 ν˜„μž₯ν›ˆλ ¨ μ‹€μ‹œ μ€‘μ†ŒκΈ°μ—…μ—μ„œ ν›ˆλ ¨μ„ λ‹΄λ‹Ήν•˜κ³  μžˆλŠ” S-OJTν›ˆλ ¨κ°€ 565λͺ…이며, λͺ¨μ§‘λ‹¨μ˜ 크기에 λ”°λ₯Έ 적정 ν‘œμ§‘μˆ˜λŠ” 226λͺ…μ΄μ—ˆλ‹€. λ¬΄μ„ ν‘œμ§‘μ„ ν™œμš©ν•˜μ—¬ 350λͺ…을 ν‘œμ§‘, 온라인 섀문지가 링크된 이메일을 λ°œμ†‘ν•˜λŠ” 온라인 섀문쑰사λ₯Ό μ‹€μ‹œν•˜μ˜€λ‹€. μ‘°μ‚¬λ„κ΅¬λ‘œ ν›ˆλ ¨κ°€ ν—Œμ‹ , μ—…λ¬΄λΆ€ν•˜, 보상(물질적, μ‚¬νšŒκ΄€κ³„μ , 직무적), 자율적 직무동기, μ‘λ‹΅μž μΌλ°˜μ‚¬ν•­μœΌλ‘œ κ΅¬μ„±λœ 섀문지λ₯Ό μ‚¬μš©ν•˜μ˜€λ‹€. μžλ£Œμˆ˜μ§‘μ€ 2014λ…„ 11μ›” 17일뢀터 21μΌκΉŒμ§€ μ΄λ£¨μ–΄μ‘ŒμœΌλ©°, 총 350λͺ…μ—κ²Œ 이메일을 ν™œμš©ν•œ 섀문이 λ°°ν¬λ˜μ—ˆκ³ , 이 쀑 260개(회수율 74.2%)의 섀문지가 νšŒμˆ˜λ˜μ—ˆλ‹€. νšŒμˆ˜ν•œ 섀문지 쀑 λΆˆμ„±μ‹€ 응닡 18λΆ€λ₯Ό μ œμ™Έν•œ 242λΆ€κ°€ μ΅œμ’…μ μœΌλ‘œ 뢄석에 μ‚¬μš©λ˜μ—ˆλ‹€(유효자료율 69.1%) μžλ£ŒλŠ” λΉˆλ„λΆ„μ„, 평균 및 ν‘œμ€€νŽΈμ°¨, λ°±λΆ„μœ¨, t검증, μΌμ›λ³€λŸ‰λΆ„μ„, μœ„κ³„μ  νšŒκ·€λΆ„μ„ λ“±μ˜ 톡계기법을 μ‚¬μš©ν•˜μ—¬ λΆ„μ„ν•˜μ˜€μœΌλ©°, 톡계적 μœ μ˜λ―Έμ„±μ€ 0.05λ₯Ό κΈ°μ€€μœΌλ‘œ νŒλ‹¨ν•˜μ˜€λ‹€. 이 μ—°κ΅¬μ˜ κ²°κ³Όλ₯Ό μš”μ•½ν•˜λ©΄, 첫째, μ—…λ¬΄λΆ€ν•˜λŠ” ν›ˆλ ¨κ°€μ˜ ν—Œμ‹ μ— 뢀적(-)인 영ν–₯을 μ£ΌλŠ” κ²ƒμœΌλ‘œ λ‚˜νƒ€λ‚¬κ³ , 물질적 보상, μ‚¬νšŒκ΄€κ³„μ  보상, 직무적 보상, 자율적 μ§λ¬΄λ™κΈ°λŠ” ν—Œμ‹ μ— 정적(+)인 영ν–₯을 μ£ΌλŠ” κ²ƒμœΌλ‘œ λ‚˜νƒ€λ‚¬λ‹€. 특히, 자율적 직무동기 쀑 λ™μΌμ‹œ 동기가 λ‚΄μž¬μ  동기보닀 더 큰 영ν–₯을 μ£ΌλŠ” κ²ƒμœΌλ‘œ λ‚˜νƒ€λ‚¬κ³ , 보상 μœ ν˜• μ€‘μ—μ„œλŠ” 직무적 λ³΄μƒμ˜ 영ν–₯이 κ°€μž₯ 크고, 물질적 보상, μ‚¬νšŒκ΄€κ³„μ  λ³΄μƒμ˜ 순으둜 영ν–₯λ ₯이 큰 κ²ƒμœΌλ‘œ λ‚˜νƒ€λ‚¬λ‹€. ν•œνŽΈ, λͺ¨λ“  변인이 μ’…ν•©μ μœΌλ‘œ μž‘μš©ν•  경우 μ—…λ¬΄λΆ€ν•˜μ™€ 자율적 μ§λ¬΄λ™κΈ°λŠ” ν›ˆλ ¨κ°€μ˜ ν—Œμ‹ μ— 영ν–₯을 주지 μ•ŠμœΌλ©°, 직무적 보상, 물질적 보상, μ‚¬νšŒκ΄€κ³„μ  λ³΄μƒλ§Œμ΄ ν—Œμ‹ μ— 긍정적인 영ν–₯을 μ£ΌλŠ” κ²ƒμœΌλ‘œ λ‚˜νƒ€λ‚¬λ‹€. λ‘˜μ§Έ, ν›ˆλ ¨κ°€μ˜ ν—Œμ‹ κ³Ό μ—…λ¬΄λΆ€ν•˜μ˜ κ΄€κ³„μ—μ„œ 물질적 보상, μ‚¬νšŒκ΄€κ³„μ  보상, 직무적 보상은 μ—…λ¬΄λΆ€ν•˜μ˜ 뢀정적인 영ν–₯을 μ™„ν™”ν•˜λŠ” μ‘°μ ˆνš¨κ³Όκ°€ μžˆλŠ” κ²ƒμœΌλ‘œ λ‚˜νƒ€λ‚¬λ‹€. 쑰절효과의 ν¬κΈ°λŠ” 직무적 보상이 κ°€μž₯ 크고, 물질적 보상, μ‚¬νšŒκ΄€κ³„μ  λ³΄μƒμ˜ 순으둜 λ‚˜νƒ€λ‚¬λ‹€. μ…‹μ§Έ, ν›ˆλ ¨κ°€μ˜ ν—Œμ‹ κ³Ό 물질적 보상, 직무적 λ³΄μƒμ˜ κ΄€κ³„μ—μ„œ 자율적 μ§λ¬΄λ™κΈ°μ˜ μ‘°μ ˆνš¨κ³Όκ°€ λ‚˜νƒ€λ‚¬κ³ , μ‚¬νšŒκ΄€κ³„μ  λ³΄μƒκ³Όμ˜ κ΄€κ³„μ—μ„œλŠ” μ‘°μ ˆνš¨κ³Όκ°€ λ‚˜νƒ€λ‚˜μ§€ μ•Šμ•˜λ‹€. 즉, 자율적 μ§λ¬΄λ™κΈ°μ˜ 영ν–₯으둜 물질적 보상과 직무적 보상이 ν—Œμ‹ μ— λ―ΈμΉ˜λŠ” 영ν–₯λ ₯이 μ€„μ–΄λ“€μ—ˆκ³ , 특히 자율적 직무동기와 직무적 λ³΄μƒμ˜ μƒν˜Έμž‘μš©μœΌλ‘œ 자율적 μ§λ¬΄λ™κΈ°μ˜ 영ν–₯λ ₯이 크게 μ¦κ°€ν•˜λŠ” μƒν˜Έμž‘μš© νš¨κ³Όκ°€ λ‚˜νƒ€λ‚¬λ‹€. 이 μ—°κ΅¬μ˜ 결둠은, 첫째, ν›ˆλ ¨κ°€μ˜ ν—Œμ‹ μ„ μ¦κ°€μ‹œν‚€κΈ° μœ„ν•΄μ„œλŠ” ν›ˆλ ¨κ°€μ˜ 업무뢀담을 쀄여주고, ν›ˆλ ¨μ„ μœ„ν•œ μ€€λΉ„μ‹œκ°„μ„ μ—…λ¬΄μ‹œκ°„μœΌλ‘œ μΈμ •ν•˜μ—¬ λͺ…μ‹œν•˜λŠ” λ“± νšŒμ‚¬μ˜ 적극적인 배렀와 지원이 ν•„μš”ν•˜λ‹€. λ‘˜μ§Έ, 물질적 보상을 κ°•ν™”ν•  ν•„μš”κ°€ μžˆλ‹€. 물질적 보상은 ν›ˆλ ¨κ°€μ˜ ν—Œμ‹ μ„ μ¦κ°€μ‹œν‚€κ³  ν—Œμ‹ μ— λŒ€ν•œ μ—…λ¬΄λΆ€ν•˜μ˜ 뢀정적인 영ν–₯을 μ™„ν™”ν•˜μ§€λ§Œ, ν˜„μž¬ 물질적 λ³΄μƒμ˜ μˆ˜μ€€μ΄ 보톡 μ΄ν•˜λ‘œ λ‚˜νƒ€λ‚¨μ— 따라 물질적 보상을 κ°•ν™”ν•˜λ €λŠ” λ…Έλ ₯이 ν•„μš”ν•˜λ‹€. 특히 ν›ˆλ ¨κ°€μ˜ 직무λ₯Ό 독립적인 λ‹¨μΌμ§λ¬΄λ‘œ μ„€κ³„ν•˜κ³  그에 ν•©λ‹Ήν•œ μž„κΈˆμ„ 보μž₯ν•˜κ±°λ‚˜ μŠΉμ§„μ— ν•„μˆ˜μ μΈ 경둜둜 μ„€μ •ν•  ν•„μš”κ°€ μžˆλ‹€. μ…‹μ§Έ, μ‚¬νšŒκ΄€κ³„μ  보상을 κ°•ν™”ν•˜κΈ° μœ„ν•˜μ—¬ ν›ˆλ ¨κ°€μ— λŒ€ν•œ 상사와 λ™λ£Œμ˜ 지원과 ν˜‘μ‘°λ₯Ό κ°•μ‘°ν•  ν•„μš”κ°€ 있으며, 이λ₯Ό μœ„ν•΄ κΈ°μ—…κ³Ό μ‚¬νšŒμ—μ„œ ν›ˆλ ¨κ°€λ₯Ό μ‘΄κ²½ν•˜κ³  λ°°λ €ν•˜λŠ” λΆ„μœ„κΈ°λ₯Ό μ‘°μ„±ν•  ν•„μš”κ°€ μžˆλ‹€. λ„·μ§Έ, 직무적 보상은 ν—Œμ‹ μ„ μ¦κ°€μ‹œν‚€λŠ” κ°€μž₯ 효과적인 λ°©λ²•μœΌλ‘œ λ³΄μƒλ°©μ•ˆ μ„€κ³„μ‹œ κ°€μž₯ μ€‘μš”ν•˜κ²Œ κ³ λ €ν•˜μ—¬μ•Ό ν•œλ‹€. 즉, ν›ˆλ ¨κ°€κ°€ μžμ‹ μ˜ 직무에 λŒ€ν•΄ μ€‘μš”μ„±μ„ μΈμ§€ν•˜κ³  μ±…μž„κ°μ„ 느끼며, 슀슀둜 μ„±μž₯ν•˜κ³  μžˆλ‹€κ³  λŠλ‚„ 수 μžˆλ„λ‘ ν›ˆλ ¨κ°€μ˜ 직무 κΆŒν•œκ³Ό μžμœ¨μ„±μ„ ν™•λŒ€ν•˜λŠ” λ°©ν–₯으둜 직무λ₯Ό μ„€κ³„ν•˜κ³  μš΄μ˜ν•˜λŠ” 것이 ν•„μš”ν•˜λ‹€. λ‹€μ„―μ§Έ, 자율적 μ§λ¬΄λ™κΈ°λŠ” ν›ˆλ ¨κ°€μ˜ ν—Œμ‹ μ— 긍정적인 영ν–₯을 μ£Όλ©°, 자율적 직무동기가 높을 경우 비둝 물질적 보상이 적더라도 높은 ν—Œμ‹ μ„ μœ μ§€ν•  수 μžˆλ‹€. 특히 μˆ™λ ¨κ°€κ°€ κ΅μœ‘ν›ˆλ ¨ 업무에 λŒ€ν•œ ν₯미와 μžκΈ°μ„±μž₯ κΈ°λŒ€λ₯Ό 더 많이 κ°€μ§ˆ 수 μžˆλ„λ‘ ν›ˆλ ¨κ°€μ— λŒ€ν•΄ 더 λ§Žμ€ ꡐ윑기회λ₯Ό μ œκ³΅ν•˜κ³ , ν›ˆλ ¨κ°€λ‘œ ν™œλ™ν•˜λŠ” 것을 μžμ‹ μ˜ μ—­λŸ‰κ°œλ°œ 및 μ§μ—…μ β€€μ‚¬νšŒμ  μ„±μž₯기회둜 인식할 수 μžˆλ„λ‘ λ‹€μ–‘ν•œ κ²½λ ₯경둜 μ œμ‹œ, ꡐ윑기회 λΆ€μ—¬, μžκ²©μ œλ„λ₯Ό λ§ˆλ ¨ν•˜λŠ” λ“±μ˜ μ œλ„μ μΈ 섀계가 ν•„μš”ν•˜λ‹€. λ˜ν•œ ν›ˆλ ¨κ°€λ₯Ό μ„ λ°œν•˜λŠ” 단계뢀터 ν›ˆλ ¨ 업무에 λŒ€ν•œ κΈ°λŒ€λ₯Ό 가진 μ‚¬λžŒμ„ μ„ λ°œν•˜λŠ” 것도 μ€‘μš”ν•˜λ‹€. 이 μ—°κ΅¬μ˜ κ²°κ³Όλ₯Ό ν† λŒ€λ‘œ 후속 연ꡬλ₯Ό μœ„ν•œ μ œμ–Έμ„ ν•˜κ³ μž ν•œλ‹€. 첫째, ν›ˆλ ¨κ°€μ˜ ν—Œμ‹ μ— 영ν–₯을 μ£ΌλŠ” λ‹€μ–‘ν•œ 변인에 λŒ€ν•œ 연ꡬ가 ν•„μš”ν•˜λ‹€. λ‘˜μ§Έ, ν›ˆλ ¨κ°€μ˜ μ—…λ¬΄λΆ€ν•˜, μ†Œμ§„, μ΄μ§μ˜λ„μ™€μ˜ 관계λ₯Ό 연ꡬ할 ν•„μš”κ°€ μžˆλ‹€. μ…‹μ§Έ, ν›ˆλ ¨κ°€ ν—Œμ‹ μ˜ ν•˜μœ„μš”μΈ, 즉, ν—Œμ‹ μ˜ λŒ€μƒμ— λŒ€ν•œ ꡬ뢄, λŒ€μƒλ³„ κ΄€λ ¨ λ³€μΈμ˜ 영ν–₯관계 등이 보닀 깊이 있게 연ꡬ될 ν•„μš”κ°€ μžˆλ‹€.I. μ„œλ‘  1 1. μ—°κ΅¬μ˜ ν•„μš”μ„± 1 2. μ—°κ΅¬μ˜ λͺ©μ  4 3. μ—°κ΅¬μ˜ κ°€μ„€ 4 4. μš©μ–΄μ˜ μ •μ˜ 6 5. μ—°κ΅¬μ˜ μ œν•œ 7 II. 이둠적 λ°°κ²½ 8 1. μ€‘μ†ŒκΈ°μ—…κ³Ό S-OJT(체계적 ν˜„μž₯μ§λ¬΄κ΅μœ‘ν›ˆλ ¨) 8 2. μ€‘μ†ŒκΈ°μ—… S-OJTν›ˆλ ¨κ°€μ˜ μ—­ν• κ³Ό μ—­λŸ‰ 14 3. ν›ˆλ ¨κ°€ ν—Œμ‹ μ˜ κ°œλ…κ³Ό μΈ‘μ • 18 4. ν›ˆλ ¨κ°€μ˜ ν—Œμ‹ κ³Ό μ—…λ¬΄λΆ€ν•˜, 자율적 직무동기 및 λ³΄μƒμ˜ 관계 26 III. 연ꡬ 방법 45 1. 연ꡬ λͺ¨ν˜• 45 2. 연ꡬ λŒ€μƒ 46 3. 쑰사 도ꡬ 46 4. 자료 μˆ˜μ§‘ 57 5. 자료 뢄석 58 IV. 연ꡬ κ²°κ³Ό 및 λ…Όμ˜ 61 1. μ‘λ‹΅μžμ˜ 일반적 νŠΉμ„± 61 2. μ‘λ‹΅μžμ˜ 일반적 νŠΉμ„±μ— λ”°λ₯Έ ν—Œμ‹ μ˜ 차이 뢄석 63 3. μ€‘μ†ŒκΈ°μ—… S-OJTν›ˆλ ¨κ°€μ˜ ν—Œμ‹ μ— λŒ€ν•œ μ—…λ¬΄λΆ€ν•˜, 보상 및 자율적 μ§λ¬΄λ™κΈ°μ˜ 영ν–₯관계 65 4. μ€‘μ†ŒκΈ°μ—… S-OJTν›ˆλ ¨κ°€μ˜ ν—Œμ‹ κ³Ό μ—…λ¬΄λΆ€ν•˜μ˜ κ΄€κ³„μ—μ„œ λ³΄μƒμ˜ 쑰절효과 76 5. μ€‘μ†ŒκΈ°μ—… S-OJTν›ˆλ ¨κ°€μ˜ ν—Œμ‹ κ³Ό λ³΄μƒμ˜ κ΄€κ³„μ—μ„œ 자율적 μ§λ¬΄λ™κΈ°μ˜ 쑰절효과 79 6. λ…Όμ˜ 83 V. μš”μ•½, κ²°λ‘  및 μ œμ–Έ 92 1. μš”μ•½ 92 2. κ²°λ‘  94 3. μ œμ–Έ 97 μ°Έκ³ λ¬Έν—Œ 100 뢀둝 107 [뢀둝 1] μ˜ˆλΉ„μ‘°μ‚¬μš© μ§ˆλ¬Έμ§€ 107 [뢀둝 2] μ˜ˆλΉ„μ‘°μ‚¬ κ²°κ³Ό 112 [뢀둝 3] λ³Έμ‘°μ‚¬μš© μ§ˆλ¬Έμ§€ 114 Abstract 119Maste

    ν•œκ΅­μ—μ„œ λŒ€μž₯μ•” μ£Όμš” μœ„ν—˜μš”μΈμ— λŒ€ν•œ λŒ€μž₯μ•” κΈ°μ—¬μœ„ν—˜λ„ μΆ”μ •

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    ν•™μœ„λ…Όλ¬Έ (석사)-- μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› : μ˜ν•™κ³Ό μ˜ˆλ°©μ˜ν•™μ „κ³΅, 2016. 8. μ‹ μ• μ„ .Background: Colorectal cancer incidence has increased in Korea in accordance with westernization. We estimated the population attributable fraction (PAF) of well-established risk factors for colorectal cancer, using both nationwide and worldwide risk estimates. Materials and methods: We estimated the PAFs attributable to tobacco smoking, alcohol consumption, obesity, physical inactivity, and meat intake. Relative risks (RRs) were estimated from the meta-analyses of the studies conducted in both Korean and worldwide populations. Worldwide RRs were obtained from previous studies that reported summary effect sizes of associations between colorectal cancer and each risk factor and included the largest number of studies or colorectal cancer cases. The prevalence of each exposure was calculated by using data from the 2001 Korean National Health Examination Survey. National cancer incidence data from the Korea Central Cancer Registry were used to estimate the number of colorectal cancer cases attributable to each risk factor. Results: When using RRs estimated in the Korean population, the PAFs of all selected risk factors considered in this study were 44.5% for men and 22.7% for women. The most important risk factor for colorectal cancer among men was alcohol consumption (24.3%) and among women was meat intake (14.2%). When using RRs estimated in worldwide populations, the PAFs were 54.7% for men and 37.3% for women. The most important risk factor among both men and women was red meat intake (men, 23.1%women, 23.0%). When global estimated RRs were applied to the risk factors from the limited numbers of Korean studies (n > 3), the PAFs for all selected risk factors were 55.8% for men and 38.3% for women. Conclusions: Appropriate lifestyle modifications could decrease risk for colorectal cancer in the Korean population by 55.8% for men and 38.3% for women.INTRODUCTION 1 Epidemiology of colorectal cancer 1 Established risk factors for colorectal cancer 1 Previous studies on attributable fraction of risk for colorectal cancer risk factors 4 Burden of colorectal cancer in Korea 8 Population attributable fraction of risk 8 Objectives 8 MATERIALS AND METHODS 9 Data selection 9 Literature search 9 Inclusion criteria 14 Relative risks for colorectal cancer used to calculate population attributable fractions of risk 14 Estimation of exposure prevalence 15 Cancer incidence in 2013 16 Statistical analysis 16 Calculation of population attributable fractions of risk 17 RESULTS 18 Identification of Korean studies 18 Relative risk estimates in the Korean population 52 Global relative risk estimates population 78 Estimated prevalence of exposure 81 Estimated population attributable fractions (PAFs) of risk 86 DISCUSSION 98 REFERENCES 100 μš”μ•½ 111Maste

    적응적 κ°€μ€‘μΉ˜λ₯Ό μ‚¬μš©ν•œ Multi Scale Retinex

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