Long-Term Exposure to Fine Particulate Matter and Fasting Blood Glucose and Diabetes in 20 Million Chinese Women of Reproductive Age.

OBJECTIVE: Evidence of the associations between fine particulate matter (PM2.5) and diabetes risk from women of reproductive age, in whom diabetes may have adverse long-term health effects for both themselves and future generations, remains scarce. We therefore examined the associations of long-term PM2.5 exposure with fasting blood glucose (FBG) level and diabetes risk in women of reproductive age in China. RESEARCH DESIGN AND METHODS: This study included 20,076,032 women age 20-49 years participating in the National Free Preconception Health Examination Project in China between 2010 and 2015. PM2.5 was estimated using a satellite-based model. Multivariate linear and logistic regression models were used to examine the associations of PM2.5 exposure with FBG level and diabetes risk, respectively. Diabetes burden attributable to PM2.5 was estimated using attributable fraction (AF) and attributable number. RESULTS: PM2.5 showed monotonic relationships with elevated FBG level and diabetes risk. Each interquartile range (27 µg/m3) increase in 3-year average PM2.5 concentration was associated with a 0.078-mmol/L (95% CI 0.077, 0.079) increase in FBG and 18% (95% CI 16%, 19%) higher risk of diabetes. The AF attributed to PM2.5 exposure exceeding 5 µg/m3 was 29.0% (95% CI 27.5%, 30.5%), corresponding to an additional 78.6 thousand (95% CI 74.5, 82.6) diabetes cases. Subgroup analyses showed more pronounced diabetes risks in those who were overweight or obese, age >35 years, less educated, of minority ethnicity, registered as a rural household, and residing in western China. CONCLUSIONS: We found long-term PM2.5 exposure was associated with higher diabetes risk in women of reproductive age in China.

Association between plasma metal exposure and health span in very elderly adults: a prospective cohort study with mixture statistical approach.

BACKGROUND: Metals have been linked to a diverse spectrum of age-related diseases; however, the effects of metal exposure on health span remains largely unknown. This cohort study aims to determine the association between plasma metal and health span in elder adults aged ≥ 90 years. METHODS: The plasma concentrations of seven metals were measured at baseline in 300 elder adults. The end of the health span (EHS) was identified as the occurrence of one of eight major morbidities or mortality events. We used Cox regression to assess hazard ratios (HR). The combined effects of multiple metal mixtures were estimated using grouped-weighted quantile sum (GWQS), quantile g-computation (Q-gcomp), and Bayesian kernel machine regression (BKMR) methods. RESULTS: The estimated HR for EHS with an inter-quartile range (IQR) increment for selenium (Se) was 0.826 (95% confidence interval [CI]: 0.737-0.926); magnesium (Mg), 0.806 (95% CI: 0.691-0.941); iron (Fe), 0.756 (95% CI: 0.623-0.917), and copper (Cu), 0.856 (95% CI: 0.750-0.976). The P for trend of Se, Mg, and Fe were all < 0.05. In the mixture analyses, Q-gcomp showed a negative correlation with EHS (P = 0.904), with the sum of the negative coefficients being -0.211. CONCLUSION: Higher plasma Se, Mg, and Fe reduced the risk of premature end of health span, suggesting that essential metal elements played a role in health maintenance in elder adults.

Metabolomic landscape of overall and common cancers in the UK Biobank: A prospective cohort study.

Information about the NMR metabolomics landscape of overall, and common cancers is still limited. Based on a cohort of 83,290 participants from the UK Biobank, we used multivariate Cox regression to assess the associations between each of the 168 metabolites with the risks of overall cancer and 20 specific types of cancer. Then, we applied LASSO to identify important metabolites for overall cancer risk and obtained their associations using multivariate cox regression. We further conducted mediation analysis to evaluate the mediated role of metabolites in the effects of traditional factors on overall cancer risk. Finally, we included the 13 identified metabolites as predictors in prediction models, and compared the accuracies of our traditional models. We found that there were commonalities among the metabolic profiles of overall and specific types of cancer: the top 20 frequently identified metabolites for 20 specific types of cancer were all associated with overall cancer; most of the specific types of cancer had common identified metabolites. Meanwhile, the associations between the same metabolite with different types of cancer can vary based on the site of origin. We identified 13 metabolic biomarkers associated with overall cancer, and found that they mediated the effects of traditional factors. The accuracies of prediction models improved when we added 13 identified metabolites in models. This study is helpful to understand the metabolic mechanisms of overall and a wide range of cancers, and our results also indicate that NMR metabolites are potential biomarkers in cancer diagnosis and prevention.

Association and mediation between educational attainment and respiratory diseases: a Mendelian randomization study.

BACKGROUND: Respiratory diseases are a major health burden, and educational inequalities may influence disease prevalence. We aim to evaluate the causal link between educational attainment and respiratory disease, and to determine the mediating influence of several known modifiable risk factors. METHODS: We conducted a two-step, two-sample Mendelian randomization (MR) analysis using summary statistics from genome-wide association studies (GWAS) and single nucleotide polymorphisms (SNPs) as instrumental variables for educational attainment and respiratory diseases. Additionally, we performed a multivariable MR analysis to estimate the direct causal effect of each exposure variable included in the analysis on the outcome, conditional on the other exposure variables included in the model. The mediating roles of body mass index (BMI), physical activity, and smoking were also assessed. FINDINGS: MR analyses provide evidence of genetically predicted educational attainment on the risk of FEV1 (ß = 0.10, 95% CI 0.06, 0.14), FVC (ß = 0.12, 95% CI 0.07, 0.16), FEV1/FVC (ß = - 0.005, 95% CI - 0.05, 0.04), lung cancer (OR = 0.54, 95% CI 0.45, 0.65) and asthma (OR = 0.86, 95% CI 0.78, 0.94). Multivariable MR dicated the effect of educational attainment on FEV1 (ß = 0.10, 95% CI 0.04, 0.16), FVC (ß = 0.07, 95% CI 0.01, 0.12), FEV1/FVC (ß = 0.07, 95% CI 0.01, 0.01), lung cancer (OR = 0.55, 95% CI 0.42, 0.71) and asthma (OR = 0.88, 95% CI 0.78, 0.99) persisted after adjusting BMI and cigarettes per day. Of the 23 potential risk factors, BMI, smoking may partially mediate the relationship between education and lung disease. CONCLUSION: High levels of educational attainment have a potential causal protective effect on respiratory diseases. Reducing smoking and adiposity may be a target for the prevention of respiratory diseases attributable to low educational attainment.

Association between longitudinal dietary patterns and changes in obesity: a population-based cohort study.

Introduction: Research on the trajectory of dietary patterns and changes in obesity has been inconclusive. Methods: This study described the dietary intake and adiposity trajectories of Chinese adults and assessed the association between dietary trajectories and changes in body mass index (BMI) and waist-to-hip ratio (WHR). We used data from 3, 643 adults who participated in the China Health and Nutrition Survey from 1997 to 2015. Detailed dietary data were collected by conducting three consecutive 24-h recalls. Multitrajectories of diet scores were identified by a group-based multitrajectory method. We described the change in BMI and WHR using group-based trajectory modeling. We assessed the associations between dietary trajectories and changes in people with obesity using a logistic regression model. Results: Our study revealed four trajectories of low-carbohydrate (LCD) and low-fat diet (LFD) scores. Three adiposity trajectories were identified according to the baseline level and developmental trend of BMI and WHR. Compared with the reference group, which was characterized by sustained healthy dietary habits with healthy diet scores at baseline and sustained maintenance of healthy diet scores, the other three diet trajectories had a higher risk of falling into the adverse adiposity trajectory. Discussion: Maintaining a healthy LCD and LFD can markedly decrease the risk of adiposity.

Association of ambient PM10 and PM2.5 with coronary stenosis measured using selective coronary angiography.

BACKGROUND: Long-term ambient particulate matter (PM) exposure exerts detrimental effects on cardiovascular health. Evidence on the relation of chronically exposed ambient PM10 and PM2.5 with coronary stenosis remains lacking. Our aim was to investigate the association of PM10 and PM2.5 with coronary stenosis in patients undergoing coronary angiography. METHODS: We performed a retrospective cohort study consisting of 7513 individuals who underwent coronary angiography in Fujian Province, China, from January 2019 to December 2021. We calculated a modified Gensini score (GS) to represent the degree of stenosis in coronary arteries by selective coronary angiography. We fitted linear regressions and logistic models to assess the association of PM10 and PM2.5 with coronary stenosis. We employed restricted cubic splines to describe the exposure-response curves. We performed mediation analyses to assess the potential mediators. RESULTS: Long-term ambient PM10 and PM2.5 (prior three years average) exposure was significantly associated with the GS, with a breakpoint concentration of 47.5 µg/m3 and 25.8 µg/m3 for PM10 and PM2.5, respectively, above which we found a linear positive exposure-response relationship of ambient PM with GS. Each 10 µg /m3 increase in PM10 exposure (ß: 4.81, 95 % CI: 0.44-9.19) and PM2.5 exposure [ß: 10.50, 95 % CI: 3.14-17.86] were positively related to the GS. The adjusted odds ratio (OR) for each 10 µg/m3 increment in PM10 exposure on severe coronary stenosis was 1.33 (95 % CI: 1.04-1.76). Correspondingly, the adjusted OR for PM2.5 was 1.87 (95 % CI: 1.24-2.99). The mediation analysis indicated that the effect of PM10 on coronary stenosis may be partially mediated through total cholesterol, low-density lipoprotein cholesterol, apolipoprotein B, serum creatinine and blood urea nitrogen, and the effect of PM2.5 may be mediated in part by hemoglobin A1c. CONCLUSION: Our study provides the first evidence that chronic ambient PM10 and PM2.5 exposure was associated with coronary stenosis assessed by GS in patients with suspected coronary artery disease and reveals its potential mediators.

Hyperuricemia and coronary heart disease: The mediating role of blood pressure and thrombospondin 3.

BACKGROUND & AIMS: Although hyperuricemia is a known risk factor for coronary heart disease (CHD), little is known about the role of blood pressure in mediating this association. The purpose of this study is to investigate the role of blood pressure-related indicators and Thrombospondin 3 (THBS3) in the association between hyperuricemia and CHD. METHODS AND RESULTS: Our observational epidemiology study included 593 CHD cases and 760 controls from a residential stable sample. We also chose 43 new CHD patients and 43 controls to test the expression levels of THBS3 using ELISA kits. We used logistic regression models and mediating effect analysis to investigate the relationships between hyperuricemia and CHD, as well as the mediating role of blood pressure-related indicators and THBS3. In the general population (OR: 2.001 [95% CI: 1.528-2.622]), male population (OR: 1.591 [95% CI: 1.119-2.262]), and female population (OR: 2.813 [95% CI: 1.836-4.310]), hyperuricemia is an independent risk factor for CHD. In general, average systolic blood pressure (SBP) and average pulse pressure difference (PPD) mediated 3.35% and 4.59%, respectively, of the association between hyperuricemia and CHD, and 6.60% and 6.60% in women. However, in the male population, we have not yet found that blood pressure-related indicators had a significant mediating effect. Meanwhile, we found that THBS3 mediated 19.23% of the association between hyperuricemia and CHD. CONCLUSIONS: Average SBP, PPD, and THBS3 all play a role in the association of hyperuricemia and CHD. In the female population, similar mediating results in blood pressure-related indicators were observed.

Association of longitudinal patterns of nighttime sleep duration and daytime napping duration with risk of multimorbidity.

OBJECTIVES: To determine whether longitudinal trajectories of nighttime sleep duration and daytime napping duration are related to subsequent multimorbidity risk. To explore whether daytime napping can compensate for negative effects of short nighttime sleep. METHODS: The current study included 5262 participants from China Health and Retirement Longitudinal Study. Self-reported nighttime sleep duration and daytime napping duration were collected from 2011 to 2015. The 4-year sleep duration trajectories were conducted by group-based trajectory modeling. The 14 medical conditions were defined by self-reported physician diagnoses. Multimorbidity was diagnosed as participants with 2 or more of the 14 chronic diseases after 2015. Associations between sleep trajectories and multimorbidity were assessed by Cox regression models. RESULTS: During 6.69 years of follow-up, we observed multimorbidity in 785 participants. Three nighttime sleep duration trajectories and three daytime napping duration trajectories were identified. Participants with persistent short nighttime sleep duration trajectory had the higher risk of multimorbidity (hazard ratio = 1.37, 95% confidence interval: 1.06-1.77), compared with those with persistent recommended nighttime sleep duration trajectory. Participants with persistent short nighttime sleep duration and persistent seldom daytime napping duration had the highest risk of multimorbidity (hazard ratio = 1.69, 95% confidence interval: 1.16-2.46). CONCLUSIONS: In this study, persistent short nighttime sleep duration trajectory was associated with subsequent multimorbidity risk. Daytime napping could compensate for the risk of insufficient night sleep.

Association between polyfluoroalkyl substances exposure and sex steroids in adolescents: The mediating role of serum albumin.

BACKGROUND: Polyfluoroalkyl substances (PFASs) are an emerging class of contaminants with endocrine disrupting hazards. The impact of PFASs exposure on sex steroids remain inconclusive. METHODS: This study used data from the 2013-2016 National Health and Nutrition Examination Survey (NHANES), including 525 adolescents aged 12-19. We explored the association between serum PFASs and sex steroids using multiple linear regression, weighted quantified sum (WQS) regression, and Bayesian kernel machine regression (BKMR). Mediation analyses were performed to assess whether serum albumin mediates the effects of PFASs on sex steroids. RESULTS: Single exposure to perfluorohexane sulfonic acid (PFHxS) or n-perfluorooctanoic acid (n-PFOA) was found to be inversely associated with sex hormone binding protein (SHBG) after adjustment for confounders. Results from both the WQS and BKMR models showed that mixed exposure to the five PFASs was negatively associated with SHBG and testosterone (TT) in all adolescents, while only in the WQS model, the mixed exposure to PFASs was negatively correlated with E2 and FAI in boys and negatively correlated with TT and SHBG in girls. Serum albumin was found to possibly mediate 9.7 % of the association between mixed PFAS exposure and TT, and 9.7 % of the association between mixed PFAS exposure and SHBG. CONCLUSION: Our study demonstrates a negative association between mixed exposure to PFASs and adolescent TT and SHBG levels, and suggests that albumin may merit further study as a potential target for PFAS harm reduction.

Association between solid cooking fuel and cognitive decline: Three nationwide cohort studies in middle-aged and older population.

BACKGROUND: Household solid-fuel burning contributes to indoor air pollution and is linked to poor cognitive function, but how solid cooking fuel use leads to cognitive decline over time is not well elaborated. OBJECTIVE: We examine the associations of solid cooking fuel with cognitive function among three nationally representative cohorts. METHODS: This study uses data from the 2010-2018 China Family Panel Studies (CFPS), the 2011-2018 China Health and Retirement Longitudinal Study (CHARLS) and the 2003-2015 Mexican Health and Aging Study (MHAS) in adults over the age of 50. Time varying Cox model was conducted to measure the association between cooking fuel types and cognitive decline. Mediation analysis was used to estimate the potential mediation effects on the associations of cooking fuel types with cognitive decline risk. RESULTS: Respondents in CFPS, CHARLS, and MHAS relied on solid cooking fuel at baseline approximately 56 %, 51 %, and 12 %, respectively. Using solid fuel was consistently associated with higher risk of cognitive decline in three cohorts (CFPS: HR = 1.300 [95 % CI: 1.201, 1.407], CHARLS: HR = 1.179 [95 % CI: 1.059, 1.312], MHAS: HR = 1.237 [95 % CI: 1.123, 1.362]). Compared to those with persistent solid fuel, persistent clean fuel and change from solid fuel to clean fuel were associated with a lower risk of cognitive decline. Hypertension, diabetes, physical activity, dyslipidemia and high-density lipoprotein cholesterol (HDL-C) may partially mediate the cognitive decline caused by solid fuel use. Of the cognitive decline burden, 18.23 % (95 % CI: 12.21 %, 24.73 %) in CFPS, 8.90 % (95 % CI: 2.93 %, 15.52 %) in CHARLS and 2.92 % (95 % CI: 1.52 %, 4.46 %) in MHAS of cognitive decline cases attributable to solid cooking fuel use. CONCLUSION: The use of solid cooking fuel is associated with a higher risk of cognitive decline. It is essential to promote the expanded use of clean fuel to protect cognitive health.

Changes in Mobile Health Apps Usage Before and After the COVID-19 Outbreak in China: Semilongitudinal Survey.

BACKGROUND: Mobile health (mHealth) apps are rapidly emerging technologies in China due to strictly controlled medical needs during the COVID-19 pandemic while continuing essential services for chronic diseases. However, there have been no large-scale, systematic efforts to evaluate relevant apps. OBJECTIVE: We aim to provide a landscape of mHealth apps in China by describing and comparing digital health concerns before and after the COVID-19 outbreak, including mHealth app data flow and user experience, and analyze the impact of COVID-19 on mHealth apps. METHODS: We conducted a semilongitudinal survey of 1593 mHealth apps to study the app data flow and clarify usage changes and influencing factors. We selected mHealth apps in app markets, web pages from the Baidu search engine, the 2018 top 100 hospitals with internet hospitals, and online shopping sites with apps that connect to smart devices. For user experience, we recruited residents from a community in southeastern China from October 2019 to November 2019 (before the outbreak) and from June 2020 to August 2020 (after the outbreak) comparing the attention of the population to apps. We also examined associations between app characteristics, functions, and outcomes at specific quantiles of distribution in download changes using quantile regression models. RESULTS: Rehabilitation medical support was the top-ranked functionality, with a median 1.44 million downloads per app prepandemic and a median 2.74 million downloads per app postpandemic. Among the top 10 functions postpandemic, 4 were related to maternal and child health: pregnancy preparation (ranked second; fold change 4.13), women's health (ranked fifth; fold change 5.16), pregnancy (ranked sixth; fold change 5.78), and parenting (ranked tenth; fold change 4.03). Quantile regression models showed that rehabilitation (P75, P90), pregnancy preparation (P90), bodybuilding (P50, P90), and vaccination (P75) were positively associated with an increase in downloads after the outbreak. In the user experience survey, the attention given to health information (prepandemic: 249/375, 66.4%; postpandemic: 146/178, 82.0%; P=.006) steadily increased after the outbreak. CONCLUSIONS: mHealth apps are an effective health care approach gaining in popularity among the Chinese population following the COVID-19 outbreak. This research provides direction for subsequent mHealth app development and promotion in the postepidemic era, supporting medical model reformation in China as a reference, which may provide new avenues for designing and evaluating indirect public health interventions such as health education and health promotion.

Association of greenness exposure with coronary artery stenosis and biomarkers of myocardial injury in patients with myocardial infarction.

BACKGROUND: Greenness has been linked to cardiovascular health; however, limited evidence is available regarding its association with coronary artery stenosis and biomarkers of myocardial injury. We aimed to assess these associations and examine their modification and mediation effects in patients with myocardial infarction (MI). METHODS: This study included 2030 patients with MI. The normalized difference vegetation index (NDVI) was used to characterize greenness exposure. We used a logistic regression model to explore the relationship between coronary artery stenosis and residential greenness, and applied linear regression models to assess the association of greenness with biomarkers of myocardial injury. The bootstrap method was used to explore whether potential variables mediated the associations. To further investigate the exposure-response curve describing these relationships, we developed restricted cubic spline models. RESULT: Compared to the lowest quartile of NDVI, the odds ratio (OR) (95 % confidence interval [CI]) for severe stenosis (≥75 % stenosis) was 0.68 (95 % CI: 0.47 to 0.98) for the third quartile. Participants in the highest greenness exposure quartile had lower levels of cardiac troponin I (cTnI), creatine kinase (CK), and creatine kinase isoenzyme (CKMB) than those in the lowest quartile (ß = -0.22, 95 % CI: -0.40 to -0.05; ß = -0.13, 95 % CI: -0.22 to -0.04; ß = -0.07, 95 % CI: -0.14 to -0.003). The association between residential greenness and myocardial injury biomarkers was stronger in men and older participants. Mediation analyses revealed that the effects of greenness on coronary stenosis, cTnI, CK, and CKMB were mediated by systolic blood pressure (SBP) and diastolic blood pressure (DBP). CONCLUSION: Higher greenness exposure was associated with coronary artery stenosis and reduced levels of myocardial injury biomarkers, including cTnI, CK, and CKMB. These associations may be partially mediated by SBP and DBP levels.

Physical Changes of Preschool Children during COVID-19 School Closures in Fujian, China.

The COVID-19 pandemic may constitute an "obesogenic lifestyle" that results in exacerbating childhood obesity. However, studies investigating regional sociodemographic factors including different age groups or sexes in children with obesity are lacking. We aimed to clarify the high obesity prevalence populations of preschool children to provide a regional basis for children's health policy during the COVID-19 school closures. From May to September 2019, a total of 29,518 preschool children were included in a large sample, multicenter cross-sectional study to explore physical status in Fujian Province by stratified cluster random sampling. In October 2019 and October 2020, we also conducted a cross-sectional study exploring physical development including changes in height, weight, and BMI of 1688 preschool children in Fuzhou before and after the COVID-19 school closures. Student' s t-test, Mann-Whitney U test, or chi-square test was used to assess differences in physical development and overweight and obesity rates among preschool children before and after school closures. For regional factors, the weight of urban preschool children of all ages became higher after the outbreak (p (age 3-4) = 0.009; p (age 4-5) < 0.001; p (age 5-6) = 0.002). For sex factors, overweight and obesity in boys had a greater prevalence than in girls before and after the outbreak. In four age groups, overweight and obesity rates in the 5-year-old group (15.5% and 9.9%) were higher than before (11.4% and 6.0%). The weight and BMI of 4- to 5-year-old children also increased faster than before (p < 0.001). The COVID-19 pandemic has promoted the epidemic of childhood obesity. Living in urban/coastal (economically developed) areas, boys, and aged 4-6 years old may be a susceptible population to obesity development after the outbreak.

Effects of Weak Bedding Plane, Fault, and Extreme Rainfall on the Landslide Event of a High Cut-Slope.

High cut-slopes are widespread in engineering constructions and often converted into landslides. Some extreme circumstances facilitate the landslide process, such as the weak bedding plane, rainfall, and faults. Therefore, this paper intends to offer insights into the influence of the weak bedding plane, extreme rainfall as well as faults on the landslide process of the high cut-slope. In this paper, the Anling landslide in Anhui Province, China, is selected as an example. Geological surveys, displacement monitoring, data analysis, as well as numerical simulation are carried out. The entire excavation construction and landslide deformation process are simulated to reveal the formation mechanism of the landslide using the finite difference code, FLAC3D. The effects of the fault on the landslide and the effectiveness of adjusting protection measures by adding piles are investigated on the basis of the finite difference analysis. According to monitoring data and numerical simulation, the weak bedding plane and extreme rainfall are considered the main factors leading to the Anling landslide. Field investigation and numerical experiments indicate that the fault shall facilitate and accelerate the landslide process. The construction of piles in a suitable position for the landslide is a reasonable and economical measure to stabilize the landslide.

Association between fine particulate matter and coronary heart disease: A miRNA microarray analysis.

Several studies have reported an association between residential surrounding particulate matter with an aerodynamic diameter ≤2.5 µm (PM2.5) and coronary heart disease (CHD). However, the underlying biological mechanism remains unclear. To fill this research gap, this study enrolled a residentially stable sample of 942 patients with CHD and 1723 controls. PM2.5 concentration was obtained from satellite-based annual global PM2.5 estimates for the period 1998-2019. MicroRNA microarray and pathway analysis of target genes was performed to elucidate the potential biological mechanism by which PM2.5 increases CHD risk. The results showed that individuals exposed to high PM2.5 concentrations had higher risks of CHD than those exposed to low PM2.5 concentrations (odds ratio = 1.22, 95% confidence interval: 1.00, 1.47 per 10 µg/m3 increase in PM2.5). Systolic blood pressure mediated 6.6% of the association between PM2.5 and CHD. PM2.5 and miR-4726-5p had an interaction effect on CHD development. Bioinformatic analysis demonstrated that miR-4726-5p may affect the occurrence of CHD by regulating the function of RhoA. Therefore, individuals in areas with high PM2.5 exposure and relative miR-4726-5p expression have a higher risk of CHD than their counterparts because of the interaction effect of PM2.5 and miR-4726-5p on blood pressure.

The spatiotemporal correlation of PM2.5 concentration on esophageal cancer hospitalization rate in Fujian province of China.

This paper aimed to explore the correlation between PM2.5 concentration and hospitalization rate of esophageal cancer in Fujian province, and tried to find out the accurate lag effect between PM2.5 and hospitalization rate in 70 counties from the linear and nonlinear aspects. We extracted inpatients data of esophageal cancer from the New Rural Cooperative Medical Scheme (NRCMS) database and air pollutant PM2.5 grid data published by the atmospheric composition analysis group. The study showed that the hospitalization rate of esophageal cancer presented spatial aggregation in 70 counties of Fujian province. Southeast urban agglomerations had high hospitalization rates, while central and western regions had low hospitalization rates. The study found that the spatial distribution of the hospitalization rate of esophageal cancer in 2016 was not consistent with that of the PM2.5 concentration in the same year. The concentration of PM2.5 in 2003 and 2004 had the strongest correlation with the hospitalization rate of esophageal cancer in 2016, with Pearson correlation coefficient r value of - 0.365 and Geodetector q-statistic value of 0.148 (p < 0.05). Our findings showed that there existed a 13-year lag period of air pollutant PM2.5 on the esophageal cancer hospitalization rate, which can provide helpful guidance in the early screening strategy of esophageal cancer in Fujian. The research progress of this paper will help to understand the lag period of the impact of air pollutants on the hospitalization rate of esophageal cancer, provide valuable information for the prevention and treatment strategy of esophageal cancer in Fujian province, and provide relevant experience for alike regions.

Effect of apparent temperature on hospitalization from a spectrum of cardiovascular diseases in rural residents in Fujian, China.

Cardiovascular disease (CVD) is a leading threat to global public health. Although associations between temperature and CVD hospitalization have been suggested for developed countries, limited evidence is available for developing countries or rural residents. Moreover, the effect of apparent temperature (AT) on the spectrum of cause-specific CVDs remains unknown. Based on 2,024,147 CVD hospitalizations for rural residents from eight regions in Fujian Province, China, during 2010-2016, a quasi-Poisson regression with distributed lag non-linear model was fitted to estimate the AT effect on daily CVD hospitalization for each region, and then pooled in a meta-regression that included regional indicators related to rural residents. Stratified analyses were performed according to the cause of hospitalization, sex and age groups. Finally, we calculated the fraction of CVD hospitalizations attributable to AT, as a reflection of the burden associated with AT. The heat effect appeared at lag 0-1 days, with 19% (95% CI, 11-26%) increased risk of CVD hospitalization, which was worse for ischemic heart disease, heart failure, arrhythmias and ischemic stroke. The decreased AT was associated with increase of hemorrhagic stroke at lag 0-28 days. People aged 65 and above suffered more from the heat effect on cardiovascular and cerebrovascular diseases. Regions with a lower gross value of agricultural production, rural residents' per capita net income, number of air conditioners and water heaters were more susceptible. A large number of hospitalizations were attributable to heat for most subcategories. High AT level increased CVD hospitalization, and the subcategories had different susceptibilities. The effects were modified by individual and regional characteristics. These findings have important implications for the development of targeted interventions and for hospital service planning.

Data Mining and Deep Learning for Predicting the Displacement of "Step-like" Landslides.

Landslide displacement prediction is one of the unsolved challenges in the field of geological hazards, especially in reservoir areas. Affected by rainfall and cyclic fluctuations in reservoir water levels, a large number of landslide disasters have developed in the Three Gorges Reservoir Area. In this article, the Baishuihe landslide was taken as the research object. Firstly, based on time series theory, the landslide displacement was decomposed into three parts (trend term, periodic term, and random term) by Variational Mode Decomposition (VMD). Next, the landslide was divided into three deformation states according to the deformation rate. A data mining algorithm was introduced for selecting the triggering factors of periodic displacement, and the Fruit Fly Optimization Algorithm-Back Propagation Neural Network (FOA-BPNN) was applied to the training and prediction of periodic and random displacements. The results show that the displacement monitoring curve of the Baishuihe landslide has a "step-like" trend. Using VMD to decompose the displacement of a landslide can indicate the triggering factors, which has clear physical significance. In the proposed model, the R2 values between the measured and predicted displacements of ZG118 and XD01 were 0.977 and 0.978 respectively. Compared with previous studies, the prediction model proposed in this article not only ensures the calculation efficiency but also further improves the accuracy of the prediction results, which could provide guidance for the prediction and prevention of geological disasters.