Inaccuracy of Self-reported Low Sodium Diet among Chinese: Findings from Baseline Survey for Shandong & Ministry of Health Action on Salt and Hypertension (SMASH) Project / 生物医学与环境科学（英文）

This study was aimed to evaluate the agreement between the self-reported sodium intake level and 24-h urine sodium excretion level in Chinese. The 24-h urine collection was conducted among 2112 adults aged 18-69 years randomly selected in Shandong Province, China. The subjects were asked whether their sodium intake was low, moderate, or high. The weighted kappa statistics was calculated to assess the agreement between 24-h urine sodium excretion level and self-reported sodium intake level. One third of the subjects reported low sodium intake level. About 70% of the subjects had mean 24-h sodium excretion>9 g/d, but reported low or moderate sodium intake. The agreement between self-reported sodium intake level and 24-h urine sodium excretion level was low in both normotensive subjects and hypertensive subjects. These findings suggested that many subjects who reported low sodium intake had actual urine sodium excretion>9 g/d. Sodium intake is often underestimated in both hypertensive and normotensive participants in China.

Statistical methodologies used in genome-wide association studies / 中华流行病学杂志

In lieu of large samples of cases and/or controls with hundreds of markers spreading throughout the human genome, researchers started to notice the dramatic increase of genome-wide association study (GWAS) for complex disorders, in the last 5 years. This paper highlights the statistical challenges in such huge-scale genetic studies, and introduces the analytical strategies and steps for handling GWAS data. Such issues as quality control of data, population stratification, methods available to data analysis and results presentation, replication, as well as the limitations of GWAS studies and the challenges presenting for statistics, are addressed.

Analysis on the risk factors of maternal weight for fetal macrosomia / 中华流行病学杂志

Objective To investigate the relationship between maternal weight gain and the increasing speed of weight in different pregnant terms and macrosomia.In order to reasonably manage pregnancy and decrease the morbidity of maerosomia.Methods 106 newborns whose birth weights were equal to or greater than 4000 g were specified as macrosomia,while 106 newborn with birth weights lying in 2500-3999 g were under the control group.A case-control study was conducted to compare the corresponding factors such as maternal BMI.weight before pregnancy and the change of weight during pregnancy respectively.Results Indicated by both simple and multiple unconditional logistic regression analysis,the cause of fetal macrosomia Was mainly associated with the factors including the maternal weight before pregnancy(OR=2.204,95％CI:1.377-3.529),matemal weight gain in 12-pregnant weeks(kgper week)(OR=1.961,95％CI:1.204-3.194),maternal weight gain in 20-gestation weeks(kg perweek)(OR=1.811,95％CI:1.078-3.041),maternal weight gain in 30-pregnant weeks(kg per week)(OR=1.858,95％CJ:1.095-3.153)and virile newborn(OR=2.630,95％CJ:1.420.4.850.When in 30-pregnant weeks.the pregnant women with 0.5-1.0 kg weight gain per week had 1.13 fold risks comparing to those whose weight gains were lexq than 0.5 kg per week.Conclusion Maternal weight before pregnancy,weight gain during pregnancy and fetal sex appeared a closer relation to macrosomia.It is necessary to monitor the change of maternal weight during different pregnancy periods,especially for the 30th-pregnant weeks.

Estimation of gene-environment interaction regarding partial case-control study with missing data on gene information of the controls / 中华流行病学杂志

<p><b>OBJECTIVE</b>To discuss the estimation on gene-environment interaction in partial case-control studies when gene information of the controls was partly missing.</p><p><b>METHODS</b>The results of hot deck multiple imputation and listwise deletion analysis were compared when missing data was generated using Monte Carlo method in Stata 9.0.</p><p><b>RESULTS</b>Coefficients of environment effect, gene effect and gene-environment interaction were respectively estimated by means of hot deck multiple imputation and listwise deletion when approaching to those complete data with missing part less than 50 percent. Both estimated variances of the two methods were increasing with the increased proportion of missing data, but the estimated variance of hot deck multiple imputation was smaller than the one with listwise deletion in each proportion.</p><p><b>CONCLUSION</b>Hot deck imputation could be adopted to make full use of existing information to estimate gene-environment interaction in the partial case-control study when missing proportion of gene data of controls was less than 50 percent so as to increase the precision of the estimation.</p>

Estimation on gene-environment interaction in the partial case-control study / 中华流行病学杂志

<p><b>OBJECTIVE</b>To introduce the approaches for estimating gene-environment interaction based on partial case-control studies.</p><p><b>METHODS</b>The effects of logistic model and log-linear model for estimating the main effects and gene-environment interaction effect were estimated by means of maximum likelihood methods in traditional case-control studies, case-only studies and partial case-control studies, respectively. An example was also illustrated.</p><p><b>RESULTS</b>In traditional case-control study with complete data, the results of logistic model and log-linear model were equivalent. In case-only study without any information about controls, the logistic model can also efficiently estimate gene-environment interaction. In partial case-control study, environmental information was collected from all of the cases and controls, while genetic information was only collected from cases. For this case-control study with incomplete data, a suitable parameterized log-linear model could simultaneously and efficiently estimate the main effect of environment and gene-environment interaction, whereas the logistic model could not.</p><p><b>CONCLUSION</b>For a partial case-control study, log-linear model could estimate not only the main effect of environment but also gene-environment interaction. If genotype and exposure were independent, estimators from partial case-control were as precisely as those from complete-data case-control studies.</p>

Analysis on potential years of life lost of automobile drivers in Jiangsu in 1990 - 1999 / 中华流行病学杂志

<p><b>OBJECTIVE</b>To describe the health status of automobile drivers and to define their potential years of life lost (PYLL) resulting from main death causes in Jiangsu in 1990 - 1999.</p><p><b>METHODS</b>The Reed-Merrell method and Makham-Gompertz equation were used to compile the abridged truncate life tables. PYLL and rate of PYLL was used to analyse death causes in 1990 - 1999.</p><p><b>RESULTS</b>(1) The life expectancy of drivers at age 20 was 55.36, which was 0.70 year less than that of non-drivers. (2) Rate of PYLL was 35.07 per thousand in drivers, and 42.65 per thousand in non-drivers, and the corresponding standard rates of PYLL were 42.45 per thousand and 41.14 per thousand, respectively. (3) Damage and toxicosis ranked number 4 in terms of proportionate mortality ratio, but ranked first with the rate of PYLL.</p><p><b>CONCLUSION</b>Special attention should be paid to the health status of automobile drivers, especially to those who are middle aged. Diseases that made the greatest contributions to drivers' "earlier death" were damage and toxicosis.</p>