Journal of Preventive Medicine and Public Health

Original Article

Statistical Algorithm in Genetic Linkage Based on Haplotypes.: Jinheum Kim, Dae Ryong Kang, Yun Kyung Lee, Sun Mi Shin, Il Suh, Chung Mo Nam; J Prev Med Public Health. 2004;37(4):366-372. Published online November 30, 2004

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Abstract PDF: OBJECTIVES
This study was conducted to propose a new transmission/disequilibrium test (TDT) to test the linkage between genetic markers and diseasesusceptibility genes based on haplotypes. Simulation studies were performed to compare the proposed method with that of Zhao et al. in terms of type I error probability and powers. METHODS: We estimated the haplotype frequencies using the expectation-maximization (EM) algorithm with parents' genotypes taken from a trio dataset, and then constructed a two-way contingency table containing estimated frequencies to all possible pairs of parents' haplotypes. We proposed a score test based on differences between column marginals and their corresponding row marginals. The test also involved a covariance structure of marginal differences and their variances. In simulation, we considered a coalescent model with three genetic markers of biallele to investigate the performance of the proposed test under six different configurations. RESULTS: The haplotype-based TDT statistics, our test and Zhao et al.'s test satisfied a type I error probability, but the TDT test based on single locus showed a conservative trend. As expected, the tests based on haplotypes also had better powers than those based on single locus. Our test and that of Zhao et al. were comparable in powers. CONCLUSION: We proposed a TDT statistic based on haplotypes and showed through simulations that our test was more powerful than the single locus-based test. We will extend our method to multiplex data with affected and/or unaffected sibling (s) or simplex data having only one parent's genotype.; Summary

Evaluation Studies

An Evaluation of Sampling Design for Estimating an Epidemiologic Volume of Diabetes and for Assessing Present Status of Its Control in Korea.: Ji Sung Lee, Jaiyong Kim, Sei Hyun Baik, Ie Byung Park, Juneyoung Lee; J Prev Med Public Health. 2009;42(2):135-142.; DOI: https://doi.org/10.3961/jpmph.2009.42.2.135

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OBJECTIVES
An appropriate sampling strategy for estimating an epidemiologic volume of diabetes has been evaluated through a simulation. METHODS: We analyzed about 250 million medical insurance claims data submitted to the Health Insurance Review & Assessment Service with diabetes as principal or subsequent diagnoses, more than or equal to once per year, in 2003. The database was re-constructed to a 'patient-hospital profile' that had 3,676,164 cases, and then to a 'patient profile' that consisted of 2,412,082 observations. The patient profile data was then used to test the validity of a proposed sampling frame and methods of sampling to develop diabetic-related epidemiologic indices. RESULTS: Simulation study showed that a use of a stratified two-stage cluster sampling design with a total sample size of 4,000 will provide an estimate of 57.04% (95% prediction range, 49.83 - 64.24%) for a treatment prescription rate of diabetes. The proposed sampling design consists, at first, stratifying the area of the nation into "metropolitan/city/county" and the types of hospital into "tertiary/secondary/primary/clinic" with a proportion of 5:10:10:75. Hospitals were then randomly selected within the strata as a primary sampling unit, followed by a random selection of patients within the hospitals as a secondly sampling unit. The difference between the estimate and the parameter value was projected to be less than 0.3%. CONCLUSIONS: The sampling scheme proposed will be applied to a subsequent nationwide field survey not only for estimating the epidemiologic volume of diabetes but also for assessing the present status of nationwide diabetes control.

Summary

Citations

Citations to this article as recorded by

Diabetes Epidemics in Korea: Reappraise Nationwide Survey of Diabetes "Diabetes in Korea 2007"
Ie Byung Park, Jaiyong Kim, Dae Jung Kim, Choon Hee Chung, Jee-Young Oh, Seok Won Park, Juneyoung Lee, Kyung Mook Choi, Kyung Wan Min, Jeong Hyun Park, Hyun Shik Son, Chul Woo Ahn, Hwayoung Kim, Sunhee Lee, Im Bong Lee, Injeoung Choi, Sei Hyun Baik
Diabetes & Metabolism Journal.2013; 37(4): 233. CrossRef
Development of a Sampling Strategy and Sample Size Calculation to Estimate the Distribution of Mammographic Breast Density in Korean Women
Jae Kwan Jun, Mi Jin Kim, Kui Son Choi, Mina Suh, Kyu-Won Jung
Asian Pacific Journal of Cancer Prevention.2012; 13(9): 4661. CrossRef

Original Articles

The Study of Prescription Behaviors of Practicing Pharmacists with Simulated Patients of Arthritis.: Hong Jun Cho, Kwang Su Uh, Jin Wook Choi; Korean J Prev Med. 1999;32(3):343-346.

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Abstract PDF: OBJECTIVES
In Korea, pharmacists can dispense medicines without doctor's prescription. This causes the high proportion of pharmaceutical expenditures. The study shows the prescribing behaviors of practicing pharmacists with the simulated patient of arthritis. We select the arthritis as a subject of simulation, because the arthritis is one of the major health problems and the abuse of cortico-steroids is usual in treatment of arthritis patients. METHODS: Twenty drug stores among the 320 drug stores in a district, Seoul, Korea were randomly selected. One of the researchers visited the drug stores and received the medicines from the pharmacists after explaining standardized scenario of arthritis. The simulated patient recorded the practice behaviors of pharmacists. RESULTS: The mean number of prescribed drugs are four and half. Among the twenty pharmacists, the nineteen prescribed non-steroidal anti-inflammatory drugs and the seven(35%) prescribed the cortico-steroids. The antacids were prescribed by the fourteen(70%) pharmacists. The five(25%) pharmacists only recommended the simulated patients to visit the medical doctors, and the three(15%) performed physical examination to the simulated patients. The three pharmacists(15%) asked the past history of the drug adverse effects and no pharmacist explained the adverse effects of prescribed medicines. CONCLUSIONS: The research shows that the cortico-steroids are frequently prescribed and the pharmacists commonly do not give the explanations of the prescribed medicines to the arthritis patients.; Summary

Health Risk Assessment and Analysis on the Volatile Organic Compounds in Some Workplace.: Hyo Min Lee, Myung Soo Kim, Shin Ai Choi, Eun Kyung Yoo, Jong Sei Park; Korean J Prev Med. 1997;30(3):530-539.

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Abstract PDF: This study was conducted to assess the health risk on the volatile organic compounds such as toluene, xylene, and styrene in painting workplace. It was monitored through personal air sampling during working time in selected 5 workplaces and analysed using gas chromatography. For the settlement of exposure situation, there were regarded working conditions such as working hours, yearly working days, and working years. Also, Monte-Carlo simulation was used for the induction of hazard index using toxicity value from IRIS(Integrated risk information system) database. The results of risk assessment were summarized as follows : 1. The air concentration of toluene was 7.096+/-15.6 ppm, 2.586+/-4.2 ppm for xylene, 1.914+/-5.3 ppm for styrene in blast painting workplaces. The level of toluene was different significantly compared with the level of xylene and styrene. 2. Computated chronic daily intake value of 95th percentile on toluene, xylene and styrene treated by Monte-Carlo simulation were 9.616, 3.567, 2.782 mg/kg/day, respectively. 3. Computated hazard index value of 75th percentile on toluene, xylene and styrene treated by Monte-Carlo simulation were 3.5, 1.0 and 1.6, respectively. Adverse health effects on the toluene, xylene and styrene would be expected by working exposure in blast painting workplace since the hazard indices of three compounds were exceeded 1 in the surroundings of percenitile 75 through having the low emerged frequency; Summary

A Study on the Efficient Management of Long-term Inpatient Flow in a General Hospital.: Chun Bae Kim, Young Moon Chae, Seung Hum Yu, Hee Chul Oh; Korean J Prev Med. 1990;23(1):11-21.

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Abstract PDF: This study refers to the problem of long-term inpatient flow in a general hospital. In this study, a queueing simulation model was developed for the two departments in the hospital with a homogenous case mix and relatively many long-term inpatients in order to increase the tumover rate and hospital charges. Before the simulation run, the model was verified by the Kolmogorov-Smirmov test. The following results were generated by three alternative models of the special bed policies. 1. Alternative I: When long term inpatients were admitted to the wards belonging to departments A and B without transfer to other departments and special beds, the average turn-over rate decreased by 2-4% and the average hospital charges decreased by 70 million won. 2. Alternative II: When long-term inpatients were transferred to department C but the transfer of wards was determined by department C in order of clinical need, the average turnover rate increased by 4-13% but the average hospital charges decreased by 30 million won. This result was not greatly different from the present state. 3. Alternative III: When long-term inpatients were transferred to the special wards and department C simultaneously, the increase in the average turnover rate and hospital charges was equivalent to the increase of two beds in the special wards. When the special wards were allocated 16 beds, the average turnover rate of departments A and B increased by about 55% and 20% respectively. Also, the hospital charges increased by about 0.44 billion won. As a result, trasfer to department C and the use of 16 beds in the special wards for long-term inpatients of departments A and B is expected to maximize the hospital revenue. However, as the above special bed policy can not increase the turnover rate above 60%, there is a need for a more comprehensive policy to further increase the rate. The development of an elaborate model should include the number of long-term inpatients in all clinical departments, the special wards system or an increase of hospital beds to handle admission needs, and the resources of the hospital by department. When the alternative are evaluated, a cost-benefit analysis in addition to the turnover rate and the hospital charges should be considered.; Summary

English Abstract

Modelling the Impact of Pandemic Influenza.: Byung Chul Chun; J Prev Med Public Health. 2005;38(4):379-385.

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Abstract PDF: The impact of the next influenza pandemic is difficult to predict. It is dependent on how virulent the virus is, how rapidly it spreads from population to population, and the effectiveness of prevention and response efforts. Despite the uncertainty about the magnitude of the next pandemic, estimates of the health and economic impact remain important to aid public health policy decisions and guide pandemic planning for health and emergency sectors. Planning ahead in preparation for an influenza pandemic, with its potentially very high morbidity and mortality rates, is essential for hospital administrators and public health officials. The estimation of pandemic impact is based on the previous pandemics- we had experienced at least 3 pandemics in 20th century. But the epidemiological characteristics - ie, start season, the impact of 1st wave, pathogenicity and virulence of the viruses and the primary victims of population were quite different from one another. I reviewed methodology for estimation and modelling of pandemic impact and described some nations's results using them in their national preparedness plans. And then I showed the estimates of pandemic influenza impact in Korea with FluSurge and FluAid. And, I described the results of pandemic modelling with parameters of 1918 pandemic for the shake of education and training of the first-line responder health officials to the epidemics. In preparing influenza pandemics, the simulation and modelling are the keys to reduce the uncertainty of the future and to make proper policies to manage and control the pandemics.; Summary

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