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Abstract Background Available data about the effects of circulating polyunsaturated fatty acids (PUFAs) on ischemic stroke (IS) and its main risk factors remains limited and conflicting. Therefore, we conducted Mendelian randomization (MR) to assess whether genetically predicted PUFA affected IS, lipids and blood pressure (BP). Methods Genetic instruments associated with IS were derived from ISGC Consortium (n = 29,633), with lipids were derived from GLGC(n = 188,577), with BP were derived from Neale Lab(n = 337,000). The inverse-variance weighted method was the main analysis to estimate the effect of exposure on outcome. Sensitivity analyses included principal components analysis, MR-Egger, weighted median, and weighted mode. Results Per SD increases in serum α-linolenic acid (ALA) were associated with lower IS risk, with odd ratio (OR) of 0.867(0.782,0.961), arachidonic acid (AA) were associated with higher IS risk (OR: 1.053(1.014,1.094)). Likewise, Per SD increases in ALA were associated with the lower-level low-density lipoprotein cholesterol(LDL-C), high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC) (β:-0.122(− 0.144, − 0.101), − 0.159(− 0.182, − 0.135), − 0.148(− 0.171, − 0.126), respectively), AA were associated with the higher-level of LDL-C, HDL-C and TC (β:0.045(0.034,0.056), 0.059(0.050,0.067), 0.055(0.046,0.063), respectively). Linoleic acid (LA), eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA) and docosapentaenoic acid (DPA) had little or no association with IS, lipids or BP at Bonferroni-corrected significance. Different analytic methods supported these findings. The intercept test of MR-Egger implied no pleiotropy. Conclusions High-level plasma ALA was protective for IS but AA was the opposite. LA, EPA, DHA, and DPA had no effects on IS.

Abstract Background Prevention and control of cardiometabolic conditions and cardiovascular disease (CVD) in China may contribute to sustainable CVD reduction globally, given the fact that one-fifth of the worldwide population is in China. Knowing the distribution of behavioral risk factors (e.g., smoking and physical inactivity), especially at a national level in China, would be extremely relevant to the field of public health and CVD prevention. The objectives of this study were to investigate the nationwide prevalence of obesity, smoking, heavy drinking, and physical inactivity in Chinese adults, and further explore whether cardiometabolic conditions would modify the distribution of behavioral risk factors. Methods This population-based study is based on the China Health and Retirement Longitudinal Study (2011–2012), including 17,302 adults (≥45 years, mean age 59.67 years, female 51.66%) from 25 provinces in China. Data on demographics, lifestyle factors, health status and history of diseases were collected via structured interviews and laboratory tests. Smoking, heavy drinking, obesity, and physical inactivity were defined following standard guidelines. We performed descriptive analysis and logistic regressions in this study. Results The overall prevalence of heavy drinking, obesity, current smoking, and physical inactivity among middle-aged and older adults was 7.23% (95% confidence interval 6.53—7.29%), 11.53% (10.43—12.62%), 27.46% (26.30—28.62%), and 44.06% (41.19—46.92%), respectively. The prevalence varied between rural and urban areas as well as among geographic areas, with higher prevalence in the Northern and Northeastern regions. Heavy drinking and obesity were significantly associated with incident hypertension, diabetes, and high cholesterol; while current smoking was significantly associated with incident hypertension. Compared with healthy individuals, participants who self-reported a diagnosis of hypertension, high cholesterol, or diabetes were less likely to smoke currently and drink alcohol heavily, but more likely to be physically inactive and obese. Conclusions Among Chinese middle-aged and older adults, the prevalence of behavioral risk factors varies by geographic region. Further effort is required to improve physical activity and fitness for Chinese adults, especially those with cardiometabolic conditions.

Abstract Background Limited studies have compared the association between various physical measurements and the risk of cancer or cardiovascular disease (CVD). We aim to explore the best‐individualized indicators of cancer and CVD risk assessment. Methods From May 2004 to December 2017, a community‐based cohort in China involving 100 280 participants were enrolled. BMI, height, body surface area (BSA), and body fat percentage (BFP) were compared in parallel about cancer and CVD risk with the multivariable‐adjusted Cox proportional hazard regression model. Results Within the follow‐up period, 3107 (3.10%) were diagnosed with cancer and 3721 (3.71%) had CVD. Per‐level increased (in tertile: T1, T2, and T3 level) BSA, height, and BFP was positively associated with the risk of overall cancer [HR (95% CI): 1.10 (1.05‐1.15), 1.12 (1.07‐1.18), and 1.10 (1.03‐1.16), respectively], whereas BMI was insignificant. Compared with the reference group (T2), the highest BSA level (T3) was positively associated with overall cancer incidence for both male [HR (95% CI): 1.28 (1.13‐1.45)] and female [HR (95% CI): 1.13 (1.00‐1.28)]. The BSA, height, and BFP also significantly associated with some site‐specific cancers including thyroid, stomach, breast, urinary system, and skin cancer. Meanwhile, BFP presented a strong positive association with overall CVD [HR (95% CI): 1.22 (1.15‐1.30) in trend] in both gender and associated with nearly all CVD subtypes especially the myocardial infarction and heart failure. Conclusion BSA, height, and BFP have more sensitivity in assessing cancer risk and BFP shows the largest hazard ratios for CVD incident. We provided valuable evidence for the application of height, BSA, and BFP in routine healthcare practice. These encouraging findings should be tested in more well‐defined studies for risk prediction.

Abstract 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.

Background This longitudinal study aims to characterize longitudinal body mass index (BMI) trajectories during young adulthood (20–40 years) and examine the impact of level‐independent BMI trajectories on hypertension risk. Methods and Results The cohort consisted of 3271 participants (1712 males and 1559 females) who had BMI and blood pressure (BP) repeatedly measured 4 to 11 times during 2004 to 2015 and information on incident hypertension. Four distinct trajectory groups were identified using latent class growth mixture model: low‐stable (n=1497), medium‐increasing (n=1421), high‐increasing (n=291), sharp‐increasing (n=62). Model‐estimated levels and linear slopes of BMI at each age point between ages 20 and 40 were calculated in 1‐year intervals using the latent class growth mixture model parameters and their first derivatives, respectively. Compared with the low‐stable group, the hazard ratios and 95% CI were 2.42 (1.88, 3.11), 4.25 (3.08, 5.87), 11.17 (7.60, 16.41) for the 3 increasing groups, respectively. After adjusting for covariates, the standardized odds ratios and 95% CI of model‐estimated BMI level for incident hypertension increased in 20 to 35 years, ranging from 0.80 (0.72–0.90) to 1.59 (1.44–1.75); then decreased gradually to 1.54 (1.42–1.68). The standardized odds ratios of level‐adjusted linear slopes increased from 1.22 (1.09–1.37) to 1.79 (1.59–2.01) at 20 to 24 years; then decreased rapidly to 1.12 (0.95–1.32). Conclusions These results indicate that the level‐independent BMI trajectories during young adulthood have significant impact on hypertension risk. Age between 20 and 30 years is a crucial period for incident hypertension, which has implications for early prevention.

Objectives: The aim of this study was to quantify the relationship between meteorological factors and the occurrence of hand, foot, and mouth disease (HFMD) among children in Shandong Province, China, at a county level, using spatial panel data models. Methods: Descriptive analysis was applied to describe the epidemic characteristics of HFMD from January 2008 to December 2012, and then a global autocorrelation statistic (Moran's I) was used to detect the spatial autocorrelation of HFMD in each year. Finally, spatial panel data models were performed to explore the association between the incidence of HFMD and meteorological factors. Results: Moran's I at the county level were high, from 0.30 to 0.45 (p

Background: Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease caused by a novel bunyavirus. The spatial distribution has continued to expand, while the areas at potential high risk of SFTS have, to date, remained unclear. Methods: Using ecological factors as predictors, the MaxEnt model was first trained based on the locations of human SFTS occurrence in Shandong Province. The risk prediction map of China was then created by projecting the training model onto the whole country. The performance of the model was assessed using the known locations of disease occurrence in China. Results: The key environmental factors affecting SFTS occurrence were temperature, precipitation, land cover, normalized difference vegetation index (NDVI), and duration of sunshine. The risk prediction maps suggested that central, southwestern, northeastern, and the eastern coast of China are potential areas at high risk of SFTS. Conclusions: The potential high risk SFTS areas are distributed widely in China. The epidemiological surveillance system should be enhanced in these high risk regions.

BACKGROUND:Multidrug-resistant tuberculosis (MDR-TB) resulting from various factors has raised serious public health concerns worldwide. Identifying the ecological risk factors associated with MDR-TB is critical to its prevention and control. This study aimed to explore the association between the development of MDR-TB and the risk factors at the group-level (ecological risk factors) in China. METHODS:Data on MDR-TB in 120 counties were obtained from the National Tuberculosis Information Management System, and data on risk-factor variables were extracted from the Health Statistical Yearbook, provincial databases, and the meteorological bureau of each province (municipality). Partial Least Square Path Modeling was used to detect the associations. RESULTS:The median proportion of MDR-TB in new TB cases was 3.96% (range, 0-39.39%). Six latent factors were extracted from the ecological risk factors, which explained 27.60% of the total variance overall in the prevalence of MDR-TB. Based on the results of PLS-PM, TB prevention, health resources, health services, TB treatment, TB detection, geography and climate factors were all associated with the risk of MDR-TB, but socioeconomic factors were not significant. CONCLUSIONS:The development of MDR-TB was influenced by TB prevention, health resources, health services, TB treatment, TB detection, geography and climate factors. Such information may help us to establish appropriate public health intervention strategies to prevent and control MDR-TB and yield benefits to the entire public health system in China.

ObjectivesTo explore the relationship between non-alcoholic fatty liver disease (NAFLD) and the metabolic syndrome (MetS), and evaluate the value of NAFLD as a marker for predicting the risk of MetS in a large scale prospective cohort from northern urban Han Chinese population.Materials and methodsA total of 17,920 MetS-free at baseline cohort members was included in the current study between 2005 and 2011. The baseline characteristics of the cohort were compared by NAFLD status at baseline, MetS status after follow-up. Cox proportional hazards models were used to estimate the unadjusted or adjusted hazard ratios (HRs) for NAFLD at baseline predicting the risk of MetS.Results2,183 (12.18%) new cases of MetS occurred between 2005 and 2011. In unadjusted model, HRs (95% CIs) for NAFLD predicting MetS was 3.65 (3.35, 3.97). After adjusting the confounding factors of age, gender, the metabolic factors, smoke and exercise, the HRs (95% CIs) was 1.70 (1.55, 1.87). Gender difference was observed, adjusted HRs (95% CIs) of NAFLD for predicting MetS were 2.06(1.72, 2.46) and 1.55(1.39, 1.72) in female and male population, respectively. Moreover, 163 participants developed MetS among participants without any MetS component at baseline, and its adjusted HRs was still significant, 1.87 (1.12, 3.13).ConclusionThe present study indicates that NAFLD is an independent risk factor for predicting the risk of MetS in northern urban Han Chinese population, and the people with NAFLD should initiate weight and dietary control to prevent the occurrence of MetS.

For genome-wide association data analysis, two genes in any pathway, two SNPs in the two linked gene regions respectively or in the two linked exons respectively within one gene are often correlated with each other. We therefore proposed the concept of gene-gene co-association, which refers to the effects not only due to the traditional interaction under nearly independent condition but the correlation between two genes. Furthermore, we constructed a novel statistic for detecting gene-gene co-association based on Partial Least Squares Path Modeling (PLSPM). Through simulation, the relationship between traditional interaction and co-association was highlighted under three different types of co-association. Both simulation and real data analysis demonstrated that the proposed PLSPM-based statistic has better performance than single SNP-based logistic model, PCA-based logistic model, and other gene-based methods.

BACKGROUND: Metabolic syndrome (MetS) is proposed as a predictor for cardiovascular disease (CVD). It involves the mechanisms of insulin resistance, obesity, inflammation process of atherosclerosis, and their complex relationship in the metabolic network. Therefore, more cardiovascular risk-related biomarkers within this network should be considered as components of MetS in order to improve the prediction of CVD. METHODS: Factor analysis was performed in 5311 (4574 males and 737 females) Han Chinese subjects with MetS to extract CVD-related factors with specific clinical significance from 16 biomarkers tested in routine health check-up. Logistic regression model, based on an extreme case-control design with 445 coronary heart disease (CHD) patients and 890 controls, was performed to evaluate the extracted factors used to identify CHD. Then, Cox model, based on a cohort design with 1923 subjects followed up for 5 years, was conducted to validate their predictive effects. Finally, a synthetic predictor (SP) was created by weighting each factor with their risks for CHD to develop a risk matrix to predicting CHD. RESULTS: Eight factors were obtained from both males and females with a similar pattern. The AUC to classify CHD under the extreme case-control suggested that SP might serve as a useful tool in identifying CHD with 0.994 (95%CI 0.984-0.998) for males and 0.998 (95%CI 0.982-1.000) for females respectively. In the cohort study, the AUC to predict CHD was 0.871 (95%CI 0.851-0.889) for males and 0.899 (95%CI 0.873-0.921) for females, highlighting that SP was a powerful predictor for CHD. The SP-based 5-year CHD risk matrix provided as convenient tool for CHD risk appraisal. CONCLUSIONS: Eight factors were extracted from sixteen biomarkers in subjects with MetS and the SP adds to new insights into studies of prediction of CHD risk using data from routine health check-up.

BACKGROUND: Hand, foot, and mouth disease (HFMD) has caused major public health concerns worldwide, and has become one of the leading causes of children death. China is the most serious epidemic area with a total of 3,419,149 reported cases just from 2008 to 2010, and its different geographic areas might have different spatial epidemiology characteristics at different spatial-temporal scale levels. We conducted spatial and spatial-temporal epidemiology analysis to HFMD at county level in Shandong Province, China. METHODS: Based on the China National Disease Surveillance Reporting and Management System, the spatial-temporal database of HFMD from 2007 to 2011 was built. The global autocorrelation statistic (Moran's I) was first used to detect the spatial autocorrelation of HFMD cases in each year. Purely Spatial scan statistics combined with Space-time scan statistic were used to detect epidemic clusters. RESULTS: The annual average incidence rate was 93.70 per 100,000 in Shandong Province. Most HFMD cases (93.94%) were aged within 0-5 years old with an average male-to-female sex ratio 1.71, and the incidence seasonal peak was between April and July. The dominant pathogen was EV71 (47.35%), and CoxA16 (26.59%). HFMD had positive spatial autocorrelation at medium spatial scale level (county level) with higher Moran's I from 0.31 to 0.62 (P

BackgroundAlthough 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).MethodsA 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.ResultsA 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], pConclusionTotal 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.

Objectives: The white blood cell (WBC) count is a simple and convenient marker of inflammation for use in medical practice; however, its association with nonalcoholic fatty liver disease (NAFLD) has not been determined. We examined the relationship between WBC and NAFLD to provide a convenient and useful marker for the prediction of NAFLD. Setting: A longitudinal cohort participating in a large health check-up programme for the Chinese population was selected and followed up from 2005 to 2011. Participants: A total of 21 307 male and female participants without NAFLD who underwent health check-ups at least twice between 2005 and 2011 were included in this study. 15 201 participants (7286 men and 7915 women) were eligible for inclusion. Results: The baseline distribution of age, WBC, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting plasma glucose (FPG), total cholesterol (TC), triglyceride (TG), highdensity lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), serum total protein (TP), albumin (ALB) and globin (GLO) and the prevalence of males, hypertension, hyperglycaemia, smoking and regular exercise were significantly different between the incident NAFLD and non-NAFLD groups (p<0.05). Cox proportional hazards regression analysis was performed to estimate the HRs and 95% CIs of WBC, which predicted the occurrence of NAFLD. Compared with the lowest WBC quartile (Q1), the HRs and 95% CIs of the other WBC quartiles (Q2, Q3 and Q4) for incident NAFLD were 1.090 (0.978 to 1.215), 1.174 (1.055 to 1.305) and 1.152 (1.035 to 1.281), respectively, after adjusting for age, gender, smoking, regular exercise, BMI, hypertension, hyperglycaemia, TC, TG, HDL-C, LDL-C, ALB and GLO. Conclusions: Our study clearly showed that WBC count was a significant factor associated with incident NAFLD in Han Chinese. [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 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: 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: 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]

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]