Yanxun Liu

Detecting Spatial-Temporal Clusters of HFMD from 2007 to 2011 in Shandong Province, China

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<0.001). Seven spatial-temporal clusters were detected from 2007 to 2011 in the landscape of the whole Shandong, with EV71 or CoxA16 as the dominant pathogen for most hotspots areas. Conclusions The spatial-temporal clusters of HFMD wandered around the whole Shandong Province during 2007 to 2011, with EV71 or CoxA16 as the dominant pathogen. These findings suggested that a real-time spatial-temporal surveillance system should be established for identifying high incidence region and conducting prevention to HFMD timely.

The spatial epidemiology of tuberculosis in Linyi City, China, 2005-2010.

BackgroundTuberculosis (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.MethodsThe 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.ResultsSpatial 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.ConclusionsThere 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.

Metabolic syndrome and its components as predictors of nonalcoholic fatty liver disease in a northern urban Han Chinese population: A prospective cohort study

OBJECTIVES To explore the longitudinal effect of metabolic syndrome (MetS) and its components on the development of non-alcoholic fatty liver disease (NAFLD) and to evaluate the significance of MetS and its components as early markers of NAFLD risk in a northern urban Han Chinese population. MATERIALS AND METHODS A total of 15,791 cohort members without NAFLD at baseline were included in the current study between 2005 and 2011. The baseline characteristics of the cohort were compared by MetS status at baseline and NAFLD status after follow-up. Cox proportional hazards models were used to estimate the unadjusted or adjusted hazard ratios (HRs) for development of NAFLD among individuals with MetS compared with individuals without MetS at baseline. RESULTS During 51,652 person-years of follow-up, 3913 (24.78%) new cases of NAFLD occurred between 2005 and 2011. In the unadjusted model, the HR (95% confidence interval [CI]) for NAFLD was 2.51 (2.30, 2.73). After adjusting for gender, age, diet, smoking status, and regular exercise, the HR was 1.94 (1.78, 2.13). Gender differences were observed, with adjusted HRs (95% CIs) of 1.89 (1.71, 2.09) and 1.72 (1.43, 2.07) among males and females, respectively. Compared with individuals without MetS components, the HRs were 1.92 (1.76, 2.09), 2.64 (2.40, 2.90) and 3.51 (3.15, 3.91) for individuals with one, two, or three or more MetS components, respectively. Moreover, participants with obesity or hyperlipidemia had a higher risk of NAFLD than patients with hypertension or hyperglycemia, with HRs of 2.03 (1.83, 2.25) for obesity, 1.94 (1.72, 2.19) for hyperlipidemia, and 3.01 (2.68, 3.37) for these factors in combination. CONCLUSION The present study indicates that MetS and its components independently predict the risk of NAFLD in a northern urban Han Chinese population and suggests that people with MetS or its component should initiate lifestyle changes to prevent the development of NAFLD.

Detecting the association between meteorological factors and hand, foot, and mouth disease using spatial panel data models

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 (Morans 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 Morans I at the county level were high, from 0.30 to 0.45 (p < 0.001), indicating the existence of a high spatial autocorrelation on HFMD. Spatial panel data models are more appropriate to describe the data. Results showed that the incidences of HFMD in Shandong Province, China were significantly associated with average temperature, relative humidity, vapor pressure, and wind speed. CONCLUSIONS Spatial panel data models are useful when longitudinal data with multiple units are available and spatial autocorrelation exists. The association found between HFMD and meteorological factors makes a contribution towards advancing knowledge with respect to the causality of HFMD and has policy implications for HFMD prevention and control.

Identification of reciprocal causality between non-alcoholic fatty liver disease and metabolic syndrome by a simplified Bayesian network in a Chinese population

Objectives It remains unclear whether non-alcoholic fatty liver disease (NAFLD) is a cause or a consequence of metabolic syndrome (MetS). We proposed a simplified Bayesian network (BN) and attempted to confirm their reciprocal causality. Setting Bidirectional longitudinal cohorts (subcohorts A and B) were designed and followed up from 2005 to 2011 based on a large-scale health check-up in a Chinese population. Participants Subcohort A (from NAFLD to MetS, n=8426) included the participants with or without NAFLD at baseline to follow-up the incidence of MetS, while subcohort B (from MetS to NAFLD, n=16 110) included the participants with or without MetS at baseline to follow-up the incidence of NAFLD. Results Incidence densities were 2.47 and 17.39 per 100 person-years in subcohorts A and B, respectively. Generalised estimating equation analyses demonstrated that NAFLD was a potential causal factor for MetS (relative risk, RR, 95% CI 5.23, 3.50 to 7.81), while MetS was also a factor for NAFLD (2.55, 2.23 to 2.92). A BN with 5 simplification strategies was used for the reciprocal causal inference. The BNs causal inference illustrated that the total effect of NAFLD on MetS (attributable risks, AR%) was 2.49%, while it was 19.92% for MetS on NAFLD. The total effect of NAFLD on MetS components was different, with dyslipidemia having the greatest (AR%, 10.15%), followed by obesity (7.63%), diabetes (3.90%) and hypertension (3.51%). Similar patterns were inferred for MetS components on NAFLD, with obesity having the greatest (16.37%) effect, followed by diabetes (10.85%), dyslipidemia (10.74%) and hypertension (7.36%). Furthermore, the most important causal pathway from NAFLD to MetS was that NAFLD led to elevated GGT, then to MetS components, while the dominant causal pathway from MetS to NAFLD began with dyslipidaemia. Conclusions The findings suggest a reciprocal causality between NAFLD and MetS, and the effect of MetS on NAFLD is significantly greater than that of NAFLD on MetS.

Ecological niche modeling for predicting the potential risk areas of severe fever with thrombocytopenia syndrome.

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.

Prediction of metabolic syndrome by non-alcoholic fatty liver disease in northern urban Han Chinese population: a prospective cohort study.

Objectives To 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 Methods A 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. Results 2,183 (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). Conclusion The 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.

Association between erythrocyte parameters and metabolic syndrome in urban Han Chinese: a longitudinal cohort study

BackgroundAlthough 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.MethodsA 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).Results287 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.ConclusionsElevated 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.

Association between leukocyte and metabolic syndrome in urban Han Chinese: a longitudinal cohort study.

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.

The Impact of Ambient Temperature on Childhood HFMD Incidence in Inland and Coastal Area: A Two-City Study in Shandong Province, China.

Hand, foot and mouth disease (HFMD) has been a substantial burden throughout the Asia-Pacific countries over the past decades. For the purposes of disease prevention and climate change health impact assessment, it is important to understand the temperature–disease association for HFMD in different geographical locations. This study aims to assess the impact of temperature on HFMD incidence in an inland city and a coastal city and investigate the heterogeneity of temperature–disease associations. Daily morbidity data and meteorological variables of the study areas were collected for the period from 2007 to 2012. A total of 108,377 HFMD cases were included in this study. A distributed lag non-linear model (DLNM) with Poisson distribution was used to examine the nonlinear lagged effects of daily mean temperature on HFMD incidence. After controlling potential confounders, temperature showed significant association with HFMD incidence and the two cities demonstrated different impact modes (I2 = 96.1%; p < 0.01). The results highlight the effect of temperature on HFMD incidence and the impact pattern may be modified by geographical localities. Our findings can be a practical reference for the early warning and intervention strategies of HFMD.