Cho, Eun;Kang, Moon Hae;Choi, Kui Son;Suh, MiNa;Jun, Jae Kwan;Park, Eun-Cheol
Asian Pacific Journal of Cancer Prevention
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v.14
no.4
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pp.2533-2540
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2013
Background: Although screening is necessary where gastric cancer is particularly common in Asia, the performance outcomes of mass screening programs have remained unclear. This study was conducted to evaluate cost-effectiveness outcomes of the national cancer screening program (NCSP) for gastric cancer in South Korea. Materials and Methods: People aged 40 years or over during 2002-2003 (baseline) were the target population. Screening recipients and patients diagnosed with gastric cancers were identified using the NCSP and Korea Central Cancer Registry databases. Clinical outcomes were measured in terms of mortality and life-years saved (LYS) of gastric cancer patients during 7 years based on merged data from the Korean National Health Insurance Corporation and National Statistical Office. We considered direct, indirect, and productivity-loss costs associated with screening attendance. Incremental cost-effectiveness ratio (ICER) estimates were produced according to screening method, sex, and age group compared to non-screening. Results: The age-adjusted ICER for survival was 260,201,000-371,011,000 Korean Won (KW; 1USD=1,088 KW) for the upper-gastrointestinal (UGI) tract over non-screening. Endoscopy ICERs were lower (119,099,000-178,700,000 KW/survival) than UGI. To increase 1 life-year, additional costs of approximately 14,466,000-15,014,000 KW and 8,817,000-9,755,000 KW were required for UGI and endoscopy, respectively. Endoscopy was the most cost-effective strategy for males and females. With regard to sensitivity analyses varying based on the upper age limit, endoscopy NCSP was dominant for both males and females. For males, an upper limit of age 75 or 80 years could be considered. ICER estimates for LYS indicate that the gastric cancer screening program in Korea is cost-effective. Conclusion: Endoscopy should be recommended as a first-line method in Korea because it is beneficial among the Korean population.
Objective: To determine the effects of genomic breeding values (GBV) and single nucleotide polymorphisms (SNP) on the total number of piglets born (TNB) in 3 pig breeds (Berkshire, Landrace, and Yorkshire). Methods: After collecting genomic information (Porcine SNP BeadChip) and phenotypic TNB records for each breed, the effects of GBV and SNP were estimated by using single step best linear unbiased prediction (ssBLUP) method. Results: The heritability estimates for TNB in Berkshire, Landrace, and Yorkshire breeds were 0.078, 0.107, and 0.121, respectively. The breeding value estimates for TNB in Berkshire, Landrace, and Yorkshire breeds were in the range of -1.34 to 1.47 heads, -1.79 to 1.87 heads, and -2.60 to 2.94 heads, respectively. Of sows having records for TNB, the reliability of breeding value for individuals with SNP information was higher than that for individuals without SNP information. Distributions of the SNP effects on TNB did not follow gamma distribution. Most SNP effects were near zero. Only a few SNPs had large effects. The numbers of SNPs with absolute value of more than 4 standard deviations in Berkshire, Landrace, and Yorkshire breeds were 11, 8, and 19, respectively. There was no SNP with absolute value of more than 5 standard deviations in Berkshire or Landrace. However, in Yorkshire, four SNPs (ASGA 0089457, ASGA0103374, ALGA0111816, and ALGA0098882) had absolute values of more than 5 standard deviations. Conclusion: There was no common SNP with large effect among breeds. This might be due to the large genetic composition differences and the small size of reference population. For the precise evaluation of genetic performance of individuals using a genomic selection method, it may be necessary to establish the appropriate size of reference population.
Objective: The objective of this study was to estimate genetic parameters of milk, fat, and protein yields within and across lactations in Tunisian Holsteins using a random regression test-day (TD) model. Methods: A random regression multiple trait multiple lactation TD model was used to estimate genetic parameters in the Tunisian dairy cattle population. Data were TD yields of milk, fat, and protein from the first three lactations. Random regressions were modeled with third-order Legendre polynomials for the additive genetic, and permanent environment effects. Heritabilities, and genetic correlations were estimated by Bayesian techniques using the Gibbs sampler. Results: All variance components tended to be high in the beginning and the end of lactations. Additive genetic variances for milk, fat, and protein yields were the lowest and were the least variable compared to permanent variances. Heritability values tended to increase with parity. Estimates of heritabilities for 305-d yield-traits were low to moderate, 0.14 to 0.2, 0.12 to 0.17, and 0.13 to 0.18 for milk, fat, and protein yields, respectively. Within-parity, genetic correlations among traits were up to 0.74. Genetic correlations among lactations for the yield traits were relatively high and ranged from $0.78{\pm}0.01$ to $0.82{\pm}0.03$, between the first and second parities, from $0.73{\pm}0.03$ to $0.8{\pm}0.04$ between the first and third parities, and from $0.82{\pm}0.02$ to $0.84{\pm}0.04$ between the second and third parities. Conclusion: These results are comparable to previously reported estimates on the same population, indicating that the adoption of a random regression TD model as the official genetic evaluation for production traits in Tunisia, as developed by most Interbull countries, is possible in the Tunisian Holsteins.
Large-scale copy number variants (CNVs) in the human provide the raw material for delineating population differences, as natural selection may have affected at least some of the CNVs thus far discovered. Although the examination of relatively large numbers of specific ethnic groups has recently started in regard to inter-ethnic group differences in CNVs, identifying and understanding particular instances of natural selection have not been performed. The traditional $F_{ST}$ measure, obtained from differences in allele frequencies between populations, has been used to identify CNVs loci subject to geographically varying selection. Here, we review advances and the application of multinomial-Dirichlet likelihood methods of inference for identifying genome regions that have been subject to natural selection with the $F_{ST}$ estimates. The contents of presentation are not new; however, this review clarifies how the application of the methods to CNV data, which remains largely unexplored, is possible. A hierarchical Bayesian method, which is implemented via Markov Chain Monte Carlo, estimates locus-specific $F_{ST}$ and can identify outlying CNVs loci with large values of FST. By applying this Bayesian method to the publicly available CNV data, we identified the CNV loci that show signals of natural selection, which may elucidate the genetic basis of human disease and diversity.
This study deals with the decision problem of sample size by the relative standard error of estimates derived from survey results in successive occasions. The population of the construction in business survey results is used to calculate quartile of the relative standard error of the 1,000 sample obtained from simple or stratified random sampling. The sample size at time t with a relative standard error of the point (t-1) in the successive occasions were calculated according to the sampling method. As a result, in terms of the sample size according to the size of the relative standard error of the (t-1), simple random sampling differs significantly from stratified sampling. In addition, we could see differences in sample size (depending on how the population is stratified) and that careful attention is required in the problem of sample size by the relative standard error of estimates derived from survey results in successive occasions.
Follow-up surveys with 700 smoking male adults and 300 nonsmoking male adults were performed before 20-days and after one month, three months and six months since government's price increase enforcement. 572 smokers among 700 and 198 non-smokers among 300 were remained and followed up till the end of the surveys. The cessation rate of smokers are 6.6%(after one month), 10.3%(after three months) and 11.0%(after six months). Smoking cessation ratio of new smoking quilters who considered that price increase as a motive of their giving-up smoking are 76.3%, 81.3% and 65.1%. The smokers estimates of short-run price elasticities from follow-up surveys are -0.6853, -0.6230 and -0.5482 at each survey period. Including non-smokers, estimates of short-run price elasticities from follow-up surveys are -0.3920, -0.3739 and -0.3481 at each survey period. The effect of demand decrease caused by KR\500 price increase stayed with little difference for six months because price elasticities between each survey period showed no much change. Effectiveness and validity of tobacco control by price increase was confirmed through the survey results. Therefore if the government want to attain long term strategic goal to decrease general smoking rate among male adult smokers by 30%, the strong smoking prohibition policy, just like the price increase of December 2004, should be continuously driven.
Rajkumar, Ullengala;Gupta, B. Ramesh;Reddy, A. Rajasekhara
Asian-Australasian Journal of Animal Sciences
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v.21
no.12
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pp.1710-1720
/
2008
A comprehensive genome profiling study was undertaken based on automated genotyping and analysis of 20 microsatellite markers that involved 155 birds representing eight different populations. The distribution of microsatellite markers in each of these breeds helped us to decipher genetic heterogeneity, population genetic structure and evolutionary relationships of the present day chicken populations in India. All the microsatellite loci utilized for the analysis were polymorphic and reasonably informative. A total of 285 alleles were documented at 20 loci with a mean of 14.25 alleles/locus. A total of 103 alleles were found to be population/strain specific of which, only 30 per cent had a frequency of more than 10. The mean PIC values ranged from 0.39 for the locus ADL158 to 0.71 for loci MCW005 or ADL267 across the genomes and 0.55 in Dahlem Red to 0.71 in Desi (non-descript), among the populations. The overall mean expected and observed heterozygosity estimates for our populations were 0.68 and 0.64, respectively. The overall mean inbreeding coefficients (FIS) varied between -0.05 (Babcock) and 0.16 (Rhode Island Red). The pairwise FST estimates ranged from 0.06 between Aseel and Desi (non-descript) to 0.14 between Dahlem Red and Babcock. The Nei's genetic distance varied from 0.30 (WLH-IWD and WLH-IWF) to 0.80 (Dahlem Red and Babcock. Phylogenetic analysis grouped all the populations into two main clusters, representing i) the pure breeds, Dahlem Red and Rhode Island Red, and ii) the remaining six populations/strains. All the chicken populations studied were in the state of mild to moderate inbreeding except for commercial birds. A planned breeding is advised for purebreds to revive their genetic potential. High genetic diversity exists in Desi (non-descript), local birds, which can be exploited to genetically improve the birds suitable for backyard poultry.
Purpose: This study assessed the accuracy of age estimates produced by a regression equation derived from lower third molar development in a Thai population. Materials and Methods: The first part of this study relied on measurements taken from panoramic radiographs of 614 Thai patients aged from 9 to 20. The stage of lower left and right third molar development was observed in each radiograph and a modified Gat score was assigned. Linear regression on this data produced the following equation: Y=9.309+1.673 mG+0.303S (Y=age; mG=modified Gat score; S=sex). In the second part of this study, the predictive accuracy of this equation was evaluated using data from a second set of panoramic radiographs (539 Thai subjects, 9 to 24 years old). Each subject's age was estimated using the above equation and compared against age calculated from a provided date of birth. Estimated and known age data were analyzed using the Pearson correlation coefficient and descriptive statistics. Results: Ages estimated from lower left and lower right third molar development stage were significantly correlated with the known ages (r=0.818, 0.808, respectively, $P{\leq}0.01$). 50% of age estimates in the second part of the study fell within a range of error of ${\pm}1year$, while 75% fell within a range of error of ${\pm}2years$. The study found that the equation tends to estimate age accurately when individuals are 9 to 20 years of age. Conclusion: The equation can be used for age estimation for Thai populations when the individuals are 9 to 20 years of age.
Journal of the Korean Association of Geographic Information Studies
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v.19
no.4
/
pp.118-129
/
2016
Many epidemiological studies, relying on administrative air pollution monitoring data, have reported the association between particulate matter ($PM_{10}$) air pollution and human health. These monitoring data were collected at a limited number of fixed sites, whereas government-generated health data are aggregated at the area level. To link these two data types for assessing health effects, it is necessary to estimate area-level concentrations of $PM_{10}$. In this study, we estimated district (Gu)-level $PM_{10}$ concentrations using a previously developed pointwise exposure prediction model for $PM_{10}$ and three types of point locations in Seoul, Korea. These points included 16,230 centroids of the largest census output residential areas, 422 community service centers, and 610 centroids on the 1km grid. After creating three types of points, we predicted $PM_{10}$ annual average concentrations at all locations and calculated Gu averages of predicted $PM_{10}$ concentrations as representative Gu-estimates. Then, we compared estimates to each other and to measurements. Prediction-based Gu-level estimates showed higher correlations with measurement-based estimates as prediction locations became more population representative ($R^2=0.06-0.59$). Among the three estimates, grid-based estimates gave lowest correlations compared to the other two(0.35-0.47). This study provides an approach for estimating area-level air pollution concentrations and assesses air pollution health effects using national-scale administrative health data.
Choi, Jae Gwan;Cho, Chung Il;Choi, Im Soo;Lee, Seung Soo;Choi, Tae Jeong;Cho, Kwang Hyun;Park, Byoung Ho;Choy, Yun Ho
Asian-Australasian Journal of Animal Sciences
/
v.26
no.4
/
pp.470-475
/
2013
The objective of this study was to estimate genetic parameters that are to be used for across-herd genetic evaluations of seed stock pigs at GGP level. Performance data with pedigree information collected from swine breeder farms in Korea were provided by Korea Animal Improvement Association (AIAK). Performance data were composed of final body weights at test days and ultrasound measures of back fat thickness (BF), rib eye area (EMA) and retail cut percentage (RCP). Breeds of swine tested were Landrace, Yorkshire and Duroc. Days to 90 kg body weight (DAYS90) were estimated with linear function of age and ADG calculated from body weights at test days. Ultrasound measures were taken with A-mode ultrasound scanners by trained technicians. Number of performance records after censoring outliers and keeping records pigs only born from year 2000 were of 78,068 Duroc pigs, 101,821 Landrace pigs and 281,421 Yorkshire pigs. Models included contemporary groups defined by the same herd and the same seasons of births of the same year, which was regarded as fixed along with the effect of sex for all traits and body weight at test day as a linear covariate for ultrasound measures. REML estimation was processed with REMLF90 program. Heritability estimates were 0.40, 0.32, 0.21 0.39 for DAYS90, ADG, BF, EMA, RCP, respectively for Duroc population. Respective heritability estimates for Landrace population were 0.43, 0.41, 0.22, and 0.43 and for Yorkshire population were 0.36, 0.38, 0.22, and 0.42. Genetic correlation coefficients of DAYS90 with BF, EMA, or RCP were estimated to be 0.00 to 0.09, -0.15 to -0.25, 0.22 to 0.28, respectively for three breeds populations. Genetic correlation coefficients estimated between BF and EMA was -0.33 to -0.39. Genetic correlation coefficient estimated between BF and RCP was high and negative (-0.78 to -0.85) but the environmental correlation coefficients between these two traits was medium and negative (near -0.35), which describes a highly correlated genetic response to selection on one or the other of these traits. Genetic Trends of all three breeds tend to be towards bigger EMA or greater RCP and shorter DAYS90 especially from generations born after year 2000.
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