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Background Obesity is a major independent risk factor for chronic diseases such as hypertension and coronary diseases, it might not be only related to the amount of body fat but its distribution. The single body mass index (BMI), waist circumference (WC), waist to hip ratio (WHR) or waist to stature ratio (WSR) provides limited information on fat distribution, and the debate about which one is the best remained. On the other hand, the current classification of body shape is qualitative rather than quantitative, and only crudely measure fat distribution. Therefore, a synthetical index is highly desirable to quantify body shape. Methods Based on the China Health and Nutrition Survey (CHNS) data, using Lohmäller PLSPM algorithm, six Partial Least Squares Path Models (PLSPMs) between the different obesity measurements and hypertension as well as two synthetical body shape scores (BSS1 by BMI/WC/Hip circumference, BSS2 by BMI/WC/WHR/WSR) were created. Simulation and real data analysis were conducted to assess their performance. Results Statistical simulation showed the proposed model was stable and powerful. Totally 15,172 (6,939 male and 8,233 female) participants aged from 18 to 87 years old were included. It indicated that age, height, weight, WC, WHR, WSR, SBP, DBP, the prevalence of hypertension and obesity were significantly sex-different. BMI, WC, WHR, WSR, Hip, BSS1 and BSS2 between hypertension and normotensive group are significantly different (p < 0.05). PLSPM method illustrated the biggest path coefficients (95% confidence interval, CI) were 0.220(0.196, 0.244) for male and 0.205(0.182, 0.228) for female in model of BSS1. The area under receiver-operating characteristic curve (AUC(95%CI)) of BSS1(0.839(0.831,0.847)) was significantly larger than that of BSS2(0.834(0.825,0.842)) as well as the four single indices for female, and similar trend can be found for male. Conclusions BSS1 was an excellent measurement for quantifying body shape and detecting the association between body shape and hypertension. [ABSTRACT FROM AUTHOR]

Background and Objectives: Chinese women in rural areas who are currently >=55 years old have experienced extreme undernutrition during their childbearing age. Their specific experiences provided us with a natural quasiexperimental field for assessing the effects of consuming eggs to obtain nutrients during the childbearing period on preventing nonfatal coronary events (NCE) during the postmenopausal period in the framework of life course epidemiology.Methods and Study Design: A population-based matched case-control design for NCE was conducted in Yiyuan County, Shandong Province, China. In this study, 462 women with NCE (cases; onset age >=55 years) were included from the Active Surveillance System for Chronic Diseases, and 462 age-matched women without NCE and stroke (controls) from the same village were included. Conditional logistic model analysis was used to determine the association between egg intake and NCE during the postmenopausal period in 3 specific life-periods, namely age 18 to 49 years (childbearing period), age 50 years to NCE onset (perimenopausal and postmenopausal period), and age 18 years to NCE onset (total period).Results: We found that >=12 eggs vs. 0 egg intake per month under extreme undernutrition status during childbearing period exhibited a strong preventive effect against NCE during the postmenopausal period (OR=0.588, 95% CI=0.358-0.964). The window of protective effect was in the age 28 to 49 years, suggesting a critical period model of life course epidemiology.Conclusions: Egg intake under extreme undernutrition status during the childbearing period plays a critical role in preventing NCE during the postmenopausal period. [ABSTRACT FROM AUTHOR]

Background: Confounders can produce spurious associations between exposure and outcome in observational studies. For majority of epidemiologists, adjusting for confounders using logistic regression model is their habitual method, though it has some problems in accuracy and precision. It is, therefore, important to highlight the problems of logistic regression and search the alternative method. Methods: Four causal diagram models were defined to summarize confounding equivalence. Both theoretical proofs and simulation studies were performed to verify whether conditioning on different confounding equivalence sets had the same bias-reducing potential and then to select the optimum adjusting strategy, in which logistic regression model and inverse probability weighting based marginal structural model (IPW-based-MSM) were compared. The "do-calculus" was used to calculate the true causal effect of exposure on outcome, then the bias and standard error were used to evaluate the performances of different strategies. Results: Adjusting for different sets of confounding equivalence, as judged by identical Markov boundaries, produced different bias-reducing potential in the logistic regression model. For the sets satisfied G-admissibility, adjusting for the set including all the confounders reduced the equivalent bias to the one containing the parent nodes of the outcome, while the bias after adjusting for the parent nodes of exposure was not equivalent to them. In addition, all causal effect estimations through logistic regression were biased, although the estimation after adjusting for the parent nodes of exposure was nearest to the true causal effect. However, conditioning on different confounding equivalence sets had the same bias-reducing potential under IPW-based-MSM. Compared with logistic regression, the IPW-based-MSM could obtain unbiased causal effect estimation when the adjusted confounders satisfied G-admissibility and the optimal strategy was to adjust for the parent nodes of outcome, which obtained the highest precision. Conclusions: All adjustment strategies through logistic regression were biased for causal effect estimation, while IPW-based-MSM could always obtain unbiased estimation when the adjusted set satisfied G-admissibility. Thus, IPW-based-MSM was recommended to adjust for confounders set. [ABSTRACT FROM AUTHOR]

Background: The genetic variants identified by Genome-wide association study (GWAS) can only account for a small proportion of the total heritability for complex disease. The existence of gene-gene joint effects which contains the main effects and their co-association is one of the possible explanations for the "missing heritability" problems. Gene-gene co-association refers to the extent to which the joint effects of two genes differ from the main effects, not only due to the traditional interaction under nearly independent condition but the correlation between genes. Generally, genes tend to work collaboratively within specific pathway or network contributing to the disease and the specific disease-associated locus will often be highly correlated (e.g. single nucleotide polymorphisms (SNPs) in linkage disequilibrium). Therefore, we proposed a novel score-based statistic (SBS) as a gene-based method for detecting gene-gene co-association. Results: Various simulations illustrate that, under different sample sizes, marginal effects of causal SNPs and co-association levels, the proposed SBS has the better performance than other existed methods including single SNP-based and principle component analysis (PCA)-based logistic regression model, the statistics based on canonical correlations (CCU), kernel canonical correlation analysis (KCCU), partial least squares path modeling (PLSPM) and delta-square (δ2) statistic. The real data analysis of rheumatoid arthritis (RA) further confirmed its advantages in practice. Conclusions: SBS is a powerful and efficient gene-based method for detecting gene-gene co-association. [ABSTRACT FROM AUTHOR]

Background: Whether non-alcoholic fatty liver disease (NAFLD) is a risk factor for gallstones remains uncertain. Few longitudinal or cohort studies have been used to identify this relationship. The aim of this study was to confirm the association between NAFLD and gallstones in a longitudinal cohort of urban dwellers in China. Methods: To elucidate the association between NAFLD and gallstones, we fitted a generalized estimating equation (GEE) model in a large-scale longitudinal cohort over 6 years, which included 11,200 participants with at least three regular health check-ups. Results: A total of 498 cases of gallstones occurred during the 6-year follow-up, which resulted in a total incidence density of 12.73 per 1000 person-years (498/39, 135.5 person-years). The GEE analyses confirmed and clarified the association between NAFLD and gallstones (relative risk (RR) = 1.2381, 95% confidence interval (CI) = 1.003-1.528, P = 0.047) after adjusting for other potential confounding factors, especially in females (RR = 1.707, 95% CI = 1.245-2.341, P = 0.001). Conclusions: NAFLD is associated with gallstones in an urban Chinese population from the middle to upper socioeconomic strata. Moreover, this association is more strongly apparent in females than in males. Further cohort studies must be conducted to confirm this association in the general population. [ABSTRACT FROM AUTHOR]

Background: Smoking prevalence is high in China and even higher among rural residents. The aims of this study were: 1) to gain insights into the motivations of tobacco use and barriers to smoking cessation among rural village residents; 2) to understand the current tobacco control measures in the rural villages and barriers encountered or perceived for implementation. Methods: Qualitative semi-structured face-to-face interviews and focus group discussions were conducted of 59 rural villagers including 37 village residents, 10 village leaders and 12 village doctors in three counties in Shandong Province, China. Results: Smoking initiation was most often out of curiosity when seeing others smoke, but pressure from cigarette sharing and gifting custom was the major barrier to smoking cessation. The most important reason for quitting successfully was a detrimental health problem. Although many attempted to quit at the advice of other family members, relapses were common and few were able to quit completely and for long-term unless accompanied by significant health issues. Although doctor's advice to quit is effective, many doctors do not offer advice to all patients. There is a lack of true understanding of the harm of smoking and second-hand smoking among the villagers and a lack of access to and knowledge of effective smoking cessation tools among both smokers and village doctors. Tobacco control activities at villages were rare and infrequent. Conclusions: This study highlighted the need to develop tobacco control measures that reflect the unique culture in rural China. Smoking cessation measures are not likely to achieve large scale effect unless the prevailing cigarette sharing and gifting custom is drastically changed. More educations of the hazards of smoking and second-hand smoking to village residents and educations of effective smoking cessation treatment to both village residents and healthcare providers are needed. [ABSTRACT FROM AUTHOR]

Background Although various cross-sectional studies have shown that erythrocyte parameters, including red blood cell (RBC), hemoglobin (Hb) and hematocrit (HCT), were linked with metabolic syndrome (MetS), few longitudinal studies have been used to confirm their relationship. The study, therefore, constructed a large-scale longitudinal cohort in urban Chinese population to highlight and confirm the association between erythrocyte parameters and MetS/its components. Methods A longitudinal cohort with 6,453 participants was established based on the routine health check-up systems to follow up MetS, and Generalized Estimating Equation (GEE) model was used to detect the association between erythrocyte parameters and MetS/its components (obesity, hyperglycemia, dyslipidemia, and hypertension). Results 287 MetS occurred over the four-year follow-up, leading to a total incidence density of 14.19 per 1,000 person-years (287/20218 person-years). Both RBC and Hb were strongly associated with MetS (RR/95%CI, P value; 3.016/1.525-5.967, 0.002 for RBC; 3.008/1.481- 6.109, 0.002 for Hb), with their dose--response trends detected. All three erythrocyte parameters (RBC, Hb and HCT) were found to be associated with obesity, hypertension and dyslipidemia with similar dose--response trends respectively, while only Hb showed a significant association with hyperglycemia. Conclusions Elevated erythrocyte parameters were confirmed to be associated with MetS/its components in urban Chinese population, suggesting that erythrocyte parameters might be served as a potential predictor for risk of MetS. [ABSTRACT FROM AUTHOR]

Background: Although cross-sectional studies have shown that leukocyte is linked with metabolic syndrome (MetS), few longitudinal or cohort studies have been used to confirm this relationship. We therefore conducted a large-scale health check-up longitudinal cohort in urban Chinese population from middle to upper socioeconomic strata to investigate and prove the association between the total leukocyte/its subtypes and MetS/its components (obesity, hyperglycemia, dyslipidemia, and hypertension). Methods: A longitudinal cohort study was established in 2005 on individuals who were middle-to-upper class urban Chinese. Data used in this investigation was based on 6,513 participants who had at least three routine health check-ups over a period of six-year follow-up. Data analysis was conducted through generalized estimating equation (GEE) model. Results: A total of 255 cases of MetS occurred over the six-year follow-up, leading to a total incidence density of 11.45 per 1,000 person-years (255/22279 person-years). The total leukocyte was markedly associated with MetS (RR = 2.66, 95%CI = 1.81-3.90], p<0.0001) and a dose-response existed. Similar trends can be found in monocytes, lymphocytes, and neutrophils compared with the total leukocyte. The total leukocyte, neutrophil, monocyte and eosinophil levels were strong and independent risk factors to obesity, total leukocyte and neutrophil to dyslipidemia and hyperglycemia, while neither total leukocyte nor its subtypes to hypertension. Conclusion: Total leukocyte/its subtype were associated with MetS/its components (obesity, dyslipidemia and hyperglycemia), they might provide convenient and useful markers for further risk appraisal of MetS, and be the earlier biomarkers for predicting cardiovascular disease than the components of MetS. [ABSTRACT FROM AUTHOR]

Background: Tuberculosis (TB) remains a major public health burden in many developing countries. China alone accounted for an estimated 12% of all incident TB cases worldwide in 2010. Several studies showed that the spatial distribution of TB was nonrandom and clustered. Thus, a spatial analysis was conducted with the aim to explore the spatial epidemiology of TB in Linyi City, which can provide guidance for formulating regional prevention and control strategies. Methods: The study was based on the reported cases of TB, between 2005 and 2010. 35,308 TB cases were geo-coded at the town level (n = 180). The spatial empirical Bayes smoothing, spatial autocorrelation and space-time scan statistic were used in this analysis. Results: Spatial distribution of TB in Linyi City from 2005 to 2010 was mapped at town level in the aspects of crude incidence, excess hazard and spatial smoothed incidence. The spatial distribution of TB was nonrandom and clustered with the significant Moran's I for each year. Local Gi* detected five significant spatial clusters for high incidence of TB. The space-time analysis identified one most likely cluster and nine secondary clusters for high incidence of TB. Conclusions: There is evidence for the existence of statistically significant TB clusters in Linyi City, China. The result of this study may assist health departments to develop a better preventive strategy and increase the public health intervention's effectiveness. [ABSTRACT FROM AUTHOR]