Exploring the causal relationship between hip circumference and type 2 diabetes based on mendelian randomization / 中华疾病控制杂志

Objective To investigate the causal association between hip circumference (HC) and type 2 diabetes mellitus (T2DM) based on Mendelian randomization. Methods The genetic variants data of the HC and T2DM from the Genetic Investigation of Anthropometric Traits (GIANT) and DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) database were matched according to the single nucleotide polymorphism (SNP) rsID. Genetic loci strongly related to the HC were used as instrumental variables; and the inverse-variance weighting, MR-Egger regression model and weighting median method were carried out to analyze the causal effect of HC on T2DM. Results Fifty-two, nine and fifteen SNPs were matched in the total cohort, female cohort and male cohort, respectively. Heterogeneity test suggested the SNPs were homogeneous. We found HC to be positively associated with T2DM risk (OR=1.065, 95% CI: 1.030-1.100, OR=1.103, 95% CI: 1.057-1.150 and OR=1.583, 95% CI: 1.273-1.968, respectively) in above three cohorts, respectively. Sensitivity analysis showed the results were robust. Conclusions There is a relationship between HC and T2DM of people, and HC may be the risk factor of T2DM.

Lifespan Risk Exposure Measurement Instrument: a Feasible and Effective Tool for Life Course Epidemiology Research / 生物医学与环境科学（英文）

Life course epidemiology should practically illustrate how risk exposures and their dynamic changes influence the occurrence, development and prognosis of chronic diseases from early life to the elderly. This paper develops the lifespan risk exposure measurement instrument (LREMI) in the framework of retrospective study to collect lifestyle, diet, physical activity information across subjects'life courses from 18-years-old to current age. Through a pilot study, the result of the test-retest analysis demonstrated the reliability of LREMI. In Shandong Multicenter Cohort, the LREMI showed its feasibility, for it could measure the exposure spectrum on both individuals and population with different life experiences. Moreover, it had good differentiation ability for identifying cases versus controls in population-based case-control study. However, further studies should be conducted in an already available prospective cohort to ascertain that our results could match prospective data.

Spatio-temporal evolution on geographic boundaries of HFRS endemic areas in Shandong Province, China / 生物医学与环境科学（英文）

<p><b>OBJECTIVE</b>To take effective strategies and measures for the prevention and control of hemorrhagic fever with renal syndrome (HFRS) endemic areas by investigating its dynamic geographical boundaries in Shandong Province, China.</p><p><b>METHODS</b>The incidence of HFRS from 1982 to 2008 in Shandong Prvince, China, was detected with inverse distance weighting (IDW) interpolation based on geographical information system (GIS). Dynamic geographical boundaries of HFRS endemic areas in Shandong Province, China, were analyzed by geographical boundary analysis.</p><p><b>RESULTS</b>The HTN-type endemic areas of HFRS were located in Linyi City in phase 1 (1982-1986), the SEO-type endemic areas of HFRS were located in Jining City in phase 2 (1987-2003), and the endemic areas of HFRS in Jining City gradually disappeared and the endemic areas of HFRS with mixed-types of reservoir rodents were located in Linyi City in phase 3 (2004-2008). Meanwhile, new endemic areas emerged in the northwestern Shandong province, China.</p><p><b>CONCLUSION</b>The SEO-type endemic areas of HFRS are located in western Shandong Province, China, and the HTN-type endemic areas of HFRS are located eastern Shandong Province, Chin, indicating that the endemic areas of HFRS should be vaccinated and rodents should be controlled.</p>

Genetic polymorphisms of 15 X-STR loci in Shandong Han population / 法医学杂志

OBJECTIVE@#To investigate the genetic polymorphisms of 15 X-STR loci in Shandong Han population in order to establish the forensic application database.@*METHODS@#The multi-PCR primers of these loci were designed by Primer Premier 5.0 software and labeled by 4 fluoresceins (FAM, VIC, NED and TET). The developed multi-PCR was used to investigate 15 X-STR loci (DXS10011, DXS101, GATA 165B12, DXS6795, DXS6800, DXS6801, DXS6803, DXS7132, DXS7133, DXS7423, DXS7424, DXS8377, DXS8378, DXS9898 and HPRTB) selected from the X chromosome of 481 unrelated individuals (295 females and 186 males) in Shandong Han population.@*RESULTS@#Among the 15 X-STR loci, GATA 165B12, DXS6800, DXS6803, DXS7133 and DXS7423 showed moderate polymorphisms, while the rest 10 X-STR loci showed high polymorphisms (PIC > 0.5 and H > 0.5). No shared haplotype was detected among the males in Shandong Han population.@*CONCLUSION@#The developed multi-PCR system with fluorescence detection provides an effective way to establish X-STR loci database of population genetics in Shandong Han population and shows its forensic application.

Path analysis of lifestyle habits to the metabolic syndrome / 中华预防医学杂志

<p><b>OBJECTIVE</b>To evaluate the relationship between lifestyle habits and the components of metabolic syndrome (MS).</p><p><b>METHODS</b>Based on the routine health check-up system in a certain Center for Health Management of Shandong Province, a longitudinal surveillance health check-up cohort from 2005 to 2010 was set up. There were 13 225 urban workers in Jinan included in the analysis. The content of the survey included demographic information, medical history, lifestyle habits, body mass index (BMI) and the level of blood pressure, fasting blood-glucose, and blood lipid, etc. The distribution of BMI, blood pressure, fasting blood-glucose, blood lipid and lifestyle habits between MS patients and non-MS population was compared, latent variables were extracted by exploratory factor analysis to determine the structure model, and then a partial least squares path model was constructed between lifestyle habits and the components of MS.</p><p><b>RESULTS</b>Participants'age was (46.62 ± 12.16) years old. The overall prevalence of the MS was 22.43% (2967/13 225), 26.49% (2535/9570) in males and 11.82% (432/3655) in females. The prevalence of the MS was statistically different between males and females (χ(2) = 327.08, P < 0.01). Between MS patients and non-MS population, the difference of dietary habits was statistically significant (χ(2) = 166.31, P < 0.01) in MS patients, the rate of vegetarian, mixed and animal food was 23.39% (694/2967), 42.50% (1261/2967) and 34.11% (1012/2967) respectively, while in non-MS population was 30.80% (3159/10 258), 46.37% (4757/10 258), 22.83% (2342/10 258) respectively. Their alcohol consumption has statistical difference (χ(2) = 374.22, P < 0.01) in MS patients, the rate of never or past, occasional and regular drinking was 27.37% (812/2967), 24.71% (733/2967), 47.93% (1422/2967) respectively, and in non-MS population was 39.60% (4062/10 258), 31.36% (3217/10 258), 29.04% (2979/10 258) respectively. The difference of their smoking status was statistically significant (χ(2) = 115.86, P < 0.01) in MS patients, the rate of never or past, occasional and regular smoking was 59.72% (1772/2967), 6.24% (185/2967), 34.04% (1010/2967) respectively, while in non-MS population was 70.03% (7184/10 258), 5.35% (549/10 258), 24.61% (2525/10 258) respectively. Both lifestyle habits and the components of MS were attributable to only one latent variable. After adjustment for age and gender, the path coefficient between the latent component of lifestyle habits and the latent component of MS was 0.22 with statistical significance (t = 6.46, P < 0.01) through bootstrap test. Reliability and validity of the model:the lifestyle latent variable: average variance extracted was 0.53, composite reliability was 0.77 and Cronbach's a was 0.57. The MS latent variable: average variance extracted was 0.45, composite reliability was 0.76 and Cronbach's a was 0.59.</p><p><b>CONCLUSION</b>Unhealthy lifestyle habits are closely related to MS. Meat diet, excessive drinking and smoking are risk factors for MS.</p>

Spatial clustering analysis of Budd-Chiari syndrome in Heze City of Shandong Province / 中国地方病学杂志

Objective To investigate the spatial distribution and clustering areas of Budd-Chiari syndrome in Heze City,Shandong Province,and to provide epidemiological information for further exploring the etiology and related risk factors of the disease.Methods Detailed residential addresses of 342 cases of patients (residents of Heze City) with diaphragm type Budd-Chiari syndrome diagnosed between 1995 and 2004 in Heze Municipal Hospital,Heze Shan County Central Hospital,Affiliated Hospital of Xuzhou Medical College,Shandong Provincial Hospital and Beijing Xuanwu Hospital were collected.Geographic information system (GIS) was used as a platform for data management and display.The nearest neighbor index,Ripley's K(d) function,Ripley's L(d) function and the nearest neighbor clustering method were applied to detect the spatial characters of Budd-Chiari syndrome in Heze City,Shandong Province.Crimestat 3.0 was used for spatial analysis.Results The nearest neighbor distance analysis showed that the nearest neighbor index was 0.6767 (Z =-11.4387,P ＜ 0.01).That was an aggregation at the first-order spatial scale.Within the study area,the first clustering radius of Budd-Chiari syndrome was 6.66 km,and the first clustering strength was 5.40; the average radius of the strongest clustering area was 126.61 km,and the clustering strength was 12.52,while the biggest clustering radius was larger than 222 km.After corrected by population,the gathering strength was slightly higher than that before the correction.Ten first-order hot spots were formed,and 95％ confidence interval aggregation number was 7,which meant the results were statistically significant(P ＜ 0.05),main clustering areas are in Mudan District,Shan County and Juancheng.One secondorder hot spot was gathered based on the first-order hot spot.Conclusions Spatial distribution of Budd-Chiari syndrome in Heze City,Shandong Province has showed spatial aggregation and heterogeneity.This study has a great epidemiological significance for further exploring the cause of Budd-Chiari syndrome.

Spatial structure of rodent populations and infection patterns of hantavirus in seven villages of Shandong Province from February 2006 to January 2007 / 中华医学杂志(英文版)

<p><b>BACKGROUND</b>Hemorrhagic fever with renal syndrome (HFRS) is endemic in Junan county, Shandong Province, China. We conducted geographic information system (GIS)-based spatial analysis with the objective of estimating the spatial distribution of rodent populations and their hantavirus infection patterns, to describe the spatial relationships of hantavirus strains in small ecological areas and to identify key areas in endemic areas of HFRS for future public health planning and resource allocation.</p><p><b>METHODS</b>Rodent sampling was conducted in seven villages in Junan county from February 2006 to January 2007 using field epidemiological surveillance. Dynamics of hantavirus infection and population densities in rodents were investigated. Spatial statistical techniques including Ripley' L index and nearest neighbour hierarchical (NNH) clustering analysis were conducted to reveal the spatial structure of rodent populations in seven villages. Phylogenetic analysis and two-dimensional minimal spanning tree (2-D MST) models were employed to describe the spatial relationship of hantavirus strains.</p><p><b>RESULTS</b>Data showed that Mus musculus was the most common species in our study area, followed by Rattus norvegicus. Ripley's L index and NNH analysis showed that the spatial distribution of all captured rodents, Mus musculus and Rattus norvegicus in seven villages were clustered and there were hotspot areas of rodent distribution. The branches of 2-D MSTs had similar topologies to those of corresponding phylogenetic trees, and hantavirus strains exhibited obvious connective traces in seven villages.</p><p><b>CONCLUSIONS</b>These results contribute to the understanding of the spatial distribution of rodent populations and hantavirus infection patterns in small areas, and identify priority areas within the epidemic areas for the development of a better prevention strategy against hemorrhagic fever with renal syndrome in a small ecological area.</p>

Study on the incidence and spatiotemporal dynamic variation of hemorrhagic fever with renal syndrome in Shandong province / 中华流行病学杂志

<p><b>OBJECTIVE</b>To study the incidence and spatiotemporal dynamic variation of hemorrhagic fever with renal syndrome (HFRS) in Shandong province.</p><p><b>METHODS</b>According to surveillance data on HFRS epidemics and host animals, a 'contour area multifractal model' was estimated on the HFRS' incidence and multi-analysis model was applied to study spatiotemporal dynamic variation.</p><p><b>RESULTS</b>The process could be classified into 5 periods: 1st period (1974-1981) when HFRS was in completely natural focal state in Shandong, and the nature of focus was typical Apodemus type. 2nd period (1982-1986) indicated the process of expanding and merging of the Apodemus type focus in the southeastern part of Linyi district and the Rattus type focus was in the southern part of Jining city. 3rd period (1987-1990) indicated that through the expanding and merging of the two epidemic focuses,one mixed focus dominated by the Apodemus type had been formed in the hilly area of the southern and middle part of Shandong while another one dominated by the Rattus type in the Yellow River valley of the northwestern part of Shandong. 4th period (1991-1993) showed that the process of the spatial pattern of the mixed focus dominated by the Rattus type in Shandong. 5th period (1994-2004) referred to the spatial pattern of the mixed focus dominated by the Rattus became stabilized.</p><p><b>CONCLUSION</b>Evolution of the characteristics of HFRS focus in Shandong province experienced the following three processes: the simple Apodemus type and the simple Rattus type were seen separately to the mixed foci with the Apodemus type dominant and the Rattus dominant type coexisted and merged to the stable state of the mixed focus with Rattus as the dominant one.</p>

Spatial genetic structure of two HIV-I-resistant polymorphisms (CCR2-64 I and SDF1-3'A) alleles in population of Shandong Province, China / 生物医学与环境科学（英文）

<p><b>OBJECTIVE</b>To explore the spatial genetic structure of two HIV-I-resistant polymorphisms (CCR2-64 I and SDF1-3'A) alleles in the population of Shandong Province, China.</p><p><b>METHODS</b>Using the techniques of spatial stratified sampling and spatial statistics, the spatial genetic structure of the locus (CCR2-64 I and SDF1-3'A), which was shown to be important co-receptor for HIV infection, was quantified from the populations of 36 sampled counties of Shandong Province, and a total of 3147 and 3172 samples were taken for testing CCR2-64I and SDF1-3'A respectively from individuals without known history of HIV-I infection and AIDS symptoms.</p><p><b>RESULTS</b>There were significantly spatial genetic structures of the two alleles at different spatial distance classes on the scale of populations, but on the scale of individuals, no spatial structure was found in either the whole area of Shandong Province or the area of each sampled county. Although the change of frequencies of the two alleles with geographic locations in Shandong Province both showed gradual increase trends, their changing directions were inverse. The frequency of CCR2-64I allele gradually increased from the southwest to the northeast, while the frequency of SDF1-3'A allele gradually increased from the northeast to the southwest. However the RH to AIDS of combined types of their different genotypes did not represent obvious geographic diversity on the whole area of the Province.</p><p><b>CONCLUSION</b>The frequency of allele usually has some spatial genetic structures or spatial autocorrelation with different spatial distance classes, but the genotypes of individuals have random distribution in the same geographic area. Evaluating spatial distribution of the genetic susceptibility of HIV (AIDS) to CCR2-64I and SDF1-3'A alleles, should focus on the frequencies of combined genotypes of CCR2 and SDF1 based on the two-locus genotypes of each individual rather than the frequencies of CCR2-64I and SDF1-3'A alleles.</p>