A high body mass index strengthens the association between the time of eye rubbing and keratoconus in a Chinese population: a case control study.

BACKGROUND: Although body mass index (BMI) and eye rubbing are linked to an increased risk of keratoconus (KC), the interactive effect of eye rubbing and BMI on KC is largely unknown. This study aimed to evaluate the independent and interactive effects of BMI and eye rubbing on KC and to further explore the role of environmental factors on the occurrence of KC. METHODS: A total of 621 individuals (291 KC patients and 330 control individuals) were enrolled in this hospital­based study on KC patients in Central China after individuals missing BMI data were excluded. BMI was calculated as weight in kilograms divided by the square of height in meters. Data on eye rubbing was recorded through face-to-face interviews. Generalized linear regression models were used to analyze associations among BMI, eye rubbing and KC. Interaction plots were used to describe the interactive effects of BMI and eye rubbing on KC. RESULTS: The ß and 95% confidence interval (CI) were 0.923 (0.112, 1.733) (p = 0.026) and 3.356 (1.953, 4.759) (p < 0.001), respectively, for the effect of each 10 kg/m2 increase in BMI and each 1 min increase in eye rubbing on KC. The interaction of BMI and eye rubbing were positively correlated with KC (p < 0.001). CONCLUSION: These findings suggested that a high BMI aggravated the negative effect of eye rubbing on KC, implying that individuals with a high BMI may be more susceptible to exposure to eye rubbing, which is related to an increased risk of KC.

Mendelian Randomization Analysis of the Association of SOCS3 Methylation with Abdominal Obesity.

This study was conducted to evaluate the potential causality association of SOCS3 methylation with abdominal obesity using Mendelian randomization. A case-control study, including 1064 participants, was carried out on Chinese subjects aged 18 to 79. MethylTargetTM was used to detect the methylation level for each CpG site of SOCS3, and SNPscan® was applied to measure the single-nucleotide polymorphism (SNP) genotyping. The logistic regression was used to assess the relationship of SOCS3 methylation level and SNP genotyping with abdominal obesity. Three types of Mendelian randomization methods were implemented to examine the potential causality between SOCS3 methylation and obesity based on the SNP of SOCS3 as instrumental variables. SOCS3 methylation levels were inversely associated with abdominal obesity in five CpG sites (effect estimates ranged from 0.786 (Chr17:76356054) to 0.851 (Chr17:76356084)), and demonstrated positively association in 18 CpG sites (effect estimates ranged from 1.243 (Chr17:76354990) to 1.325 (Chr17:76355061)). The causal relationship between SOCS3 methylation and abdominal obesity was found using the maximum-likelihood method and Mendelian randomization method of penalized inverse variance weighted (MR-IVW), and the ß values (95% CI) were 5.342 (0.215, 10.469) and 4.911 (0.259, 9.564), respectively. The causality was found between the SOCS3 methylation level and abdominal obesity in the Chinese population.

Snoring and napping independently increased the serum uric acid levels and hyperuricemia risk: The Henan Rural Cohort Study.

BACKGROUND AND AIMS: Evidence on the association of snoring, daily sleep duration (daytime napping and night sleep duration) with hyperuricemia (HUA) was limited, especially in the resources-poor areas. This study aimed to investigate the independent effect of snoring frequency and daily sleep duration on HUA prevalence in rural Chinese adults. METHODS AND RESULTS: 29,643 participants aged 18-79 years were included in the final cross-sectional analysis from the Henan Rural Cohort Study. Multivariate logistic regression and linear regression models with HUA and serum uric acid (SUA) levels as dependent variables were conducted, respectively. Of the 29,643 included adults, 3498 suffered from HUA. Compared to never snoring, the adjusted odds ratio (OR) and 95% confidence interval (CI) of HUA for rare snoring, occasional snoring, and habitual snoring were 1.35 (1.17, 1.56), 1.30 (1.14, 1.47), and 1.59 (1.47, 1.73), respectively (P for trend <0.001). Compared with no napping, participants who had daytime napping of 61-90 and > 91 min were associated with a 29% and 30% increase in the prevalence of HUA, respectively (P for trend <0.001). But in night sleep duration groups, no significant associations were observed. The positive associations between snoring and HUA were attenuated in people aged ≥65 and people with type 2 diabetes mellitus (both P for interaction <0.05). CONCLUSION: Habitual snoring or longer daytime napping was independently associated with increased HUA prevalence and SUA levels in rural Chinese adults, which indicates the significance of early intervention and treatment of snoring and longer daytime napping to prevent hyperuricemia.

Adverse associations of different obesity measures and the interactions with long-term exposure to air pollutants with prevalent type 2 diabetes mellitus: The Henan Rural Cohort study.

BACKGROUND: Obesity and ambient air pollution are independent risk factors of type 2 diabetes mellitus (T2DM), however, the evidence regarding their joint associations on T2DM was sparsely studied in low-middle income countries. METHODS: A total of 38,841 participants were selected from Henan Rural Cohort study which was carried out during 2015-2017. Obesity was identified by body mass index (BMI), WC (waist circumstance), WHR (waist-to-hip ratio), WHtR (waist-to-height ratio), BFP (body fat percent), and VFI (visceral fat index). Three-year averaged-concentrations of NO2, PM1, PM2.5, and PM10 were assessed by using the method of spatiotemporal model incorporated into the satellites data. The independent associations of obesity indicators and exposure to air pollutants on fasting blood glucose (FBG) and T2DM were assessed by generalized linear and logistic regression model, respectively, and their interaction associations on T2DM were quantified by using relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP), and synergy index (S). RESULTS: Positive associations of six obesity measures and four air pollutants with FBG levels and prevalent T2DM were observed. Obese participants measured by BMI plus high exposure to NO2, PM1, PM2.5 and PM10 were related to a 2.96-fold (2.66-3.29), 2.87-fold (2.58-3.20), 2.98-fold (2.67-3.32) and 3.01-fold (2.70-3.35) increased risk for prevalent T2DM, respectively; similarity of joint associations of the other obesity measures and air pollutants on T2DM were observed. The additive associations of different obesity measures and air pollutants with prevalent T2DM were further found. CONCLUSIONS: The synergistic associations of obesity and air pollutants on FBG levels and prevalent T2DM were observed, indicating that obese participants were at high risk for prevalent T2DM in highly polluted rural regions.

Residential greenness attenuated associations of long-term exposure to air pollution with biomarkers of advanced fibrosis.

Long-term exposure to air pollutants and residential greenness related to advanced fibrosis have been sparsely studied in low- and middle-income countries. A total of 29883 participants were selected from a cross-sectional survey of the Henan Rural Cohort. Concentrations of air pollutants (particulate matter with an aerodynamic diameter ≤ 1.0 µm (PM1), ≤ 2.5 µm (PM2.5), ≤ 10 µm (PM10) and nitrogen dioxide (NO2)) for participants were predicted by using a spatiotemporal model. Residential greenness of each participant was indicated by Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI). Independent and joint associations of air pollutants and residential greenness indices with prevalent advanced fibrosis reflected by fibrosis-4 score (FIB4), aspartate-to-platelet-ratio index (APRI) and ALT/AST ratio were analyzed by generalized linear mixed models and their interactive effect on prevalent advanced fibrosis were visualized by using the interplot method. Long-term exposure to PM1, PM2.5, PM10 and NO2 were positively related to FIB4 or APRI as well as prevalent intermediate-high advanced fibrosis; EVI was negatively related to FIB4 or APRI as well as prevalent intermediate-high advanced fibrosis. Negative associations of residential greenness indices (EVI or NDVI) with prevalent advanced fibrosis were decreased as increased air pollutants (PM1, PM2.5, PM10 or NO2) (P < 0.05 for all). This study indicated that residential greenness may partially attenuate negative effect of long-term exposure to air pollutants related to increased prevalent intermediate-high advanced fibrosis, implying that residential greenness may be an effective strategy to reduce the burden of prevalent hepatic fibrosis and its related disease in association with exposure high levels of air pollutants. The Henan Rural Cohort study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699, http://www.chictr.org.cn/showproj.aspx?proj=11375 ).

Janus kinase 2 (JAK2) methylation and obesity: A Mendelian randomization study.

BACKGROUND AND AIMS: Janus kinase 2 (JAK2) play an important role in the energy metabolism. Whether there is a causal relationship between JAK2 methylation levels and obesity remains unclear. Based on the instrumental variables of 5 SNP sites, this study was aimed to explore the causal relationship between JAK2 methylation levels and obesity by Mendelian randomization analysis. METHODS AND RESULTS: A total of 1021 participants (511 cases and 510 controls defined by body mass index (BMI) ≥ 28.0 kg/m2) was conducted from the Henan Rural Cohort study. SNPscan® was performed to test the SNP genotyping and MethylTarget™ was applied to detect the DNA methylation level. The logistic regression model was used to evaluate the associations between SNP or methylation of JAK2 and obesity (according to BMI). Mendelian randomization analysis was used to assess the potential causal association between JAK2 methylation and obesity. According to the logistic regression model, 1 CpG sit in the promotor was related to an increased risk of obesity (P < 0.05). 10 CpG sites in the exon were associated with decreased risk of obesity (P < 0.05). Mendelian randomization analysis showed a causal association between the methylated level of JAK2 and obesity, based on the instrumental variables of 5 SNPs (P < 0.05). CONCLUSIONS: This study supported that the methylation degree of JAK2 has a complex relationship with obesity, which might be related to the region of methylation. A causal relationship exists between the methylated level of JAK2 and obesity.

Associations of solid fuel use and ambient air pollution with estimated 10-year atherosclerotic cardiovascular disease risk.

BACKGROUND: Although exposure to ambient air pollution (AAP) increases the risk for arteriosclerotic cardiovascular disease (ASCVD), evidence on the association of solid fuel use with ASCVD and its association modified by ambient air pollution remains limited. METHODS: A total of 16,779 adults were derived from the Henan Rural Cohort Study. Concentrations of ambient air pollutants (PM1, PM2.5, PM10, and NO2) were estimated by a spatiotemporal model based on satellites data. Solid fuel use was assessed by a self-reported questionnaire. The associations of solid fuel use with high 10-year ASCVD risk and the modified association by exposure to air pollutants were explored using logistic regression models. RESULTS: There were positive associations of AAP exposure with high 10-year ASCVD risk among individuals with self-cooking. The joint associations between high AAP exposures and solid fuel use with high 10-year ASCVD risk were found. Compared to clean fuel user with low PM2.5 exposure, the odds ratios (ORs) and 95% confidence intervals (CIs) of high 10-year ASCVD risk was 1.25 (1.09, 1.42) for solid fuel user with low PM2.5 exposure, 1.93 (1.75, 2.12) for clean fuel user with high PM2.5 exposure, and 3.08 (2.67, 3.54) for solid fuel user with high PM2.5 exposure, respectively. Their additive effect on high 10-year ASCVD risk was observed (relative excess risk due to interaction (RERI): 0.90 (95 %CI: 0.50, 1.30), attributable proportion due to interaction (AP): 0.29 (95 %CI: 0.19, 0.40), and synergy index (SI): 1.77 (95 %CI: 1.38, 2.26)). CONCLUSION: This study showed a synergistic effect of AAP and household air pollution reflected by solid fuel use on high 10-year ASCVD risk, suggesting that reducing solid cooking fuels and controlling air pollution may have a joint effect on public health improvement.

Lifestyle Score and Genetic Factors With Hypertension and Blood Pressure Among Adults in Rural China.

Background: Although high genetic risk and unhealthful lifestyles are associated with a high risk of hypertension, but the combined relationship between lifestyle score and genetic factors on blood pressure remains limited, especially in resource-constrained areas. Aim: To explore the separate and joint effects between genetic and lifestyle factors on blood pressure and hypertension in rural areas. Methods: In 4,592 adults from rural China with a 3-year of follow-up, a genetic risk score (GRS) was established using 13 single nucleotide polymorphisms (SNPs) and the lifestyle score was calculated including factors diet, body mass index (BMI), smoking status, drinking status, and physical activity. The associations of genetic and lifestyle factors with blood pressure and hypertension were determined with generalized linear and logistic regression models, respectively. Results: The high-risk GRS was found to be associated with evaluated blood pressure and hypertension and the healthful lifestyle with diastolic blood pressure (DBP) level. Individuals with unhealthful lifestyles in the high GRS risk group had an odds ratio (OR) (95% CI) of 1.904 (1.006, 3.603) for hypertension than those with a healthful lifestyle in the low GRS risk group. Besides, the relative risk (RR), attributable risk (AR), and population attributable risk (PAR) for unhealthful lifestyle are 1.39, 5.87, 0.04%, respectively, and the prevented fraction for the population (PFP) for healthful lifestyle is 9.47%. Conclusion: These results propose a joint effect between genetic and lifestyle factors on blood pressure and hypertension. The findings provide support for adherence to a healthful lifestyle in hypertension precision prevention. Clinical Trial Registration: The Henan Rural Cohort Study has been registered at the Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). http://www.chictr.org.cn/showproj.aspx?proj=11375.

Identifying the predictive effectiveness of a genetic risk score for incident hypertension using machine learning methods among populations in rural China.

Current studies have shown the controversial effect of genetic risk scores (GRSs) in hypertension prediction. Machine learning methods are used extensively in the medical field but rarely in the mining of genetic information. This study aims to determine whether genetic information can improve the prediction of incident hypertension using machine learning approaches in a prospective study. The study recruited 4592 subjects without hypertension at baseline from a cohort study conducted in rural China. A polygenic risk score (PGGRS) was calculated using 13 SNPs. According to a ratio of 7:3, subjects were randomly allocated to the train and test datasets. Models with and without the PGGRS were established using the train dataset with Cox regression, artificial neural network (ANN), random forest (RF), and gradient boosting machine (GBM) methods. The discrimination and reclassification of models were estimated using the test dataset. The PGGRS showed a significant association with the risk of incident hypertension (HR (95% CI), 1.046 (1.004, 1.090), P = 0.031) irrespective of baseline blood pressure. Models that did not include the PGGRS achieved AUCs (95% CI) of 0.785 (0.763, 0.807), 0.790 (0.768, 0.811), 0.838 (0.817, 0.857), and 0.854 (0.835, 0.873) for the Cox, ANN, RF, and GBM methods, respectively. The addition of the PGGRS led to the improvement of the AUC by 0.001, 0.008, 0.023, and 0.017; IDI by 1.39%, 2.86%, 4.73%, and 4.68%; and NRI by 25.05%, 13.01%, 44.87%, and 22.94%, respectively. Incident hypertension risk was better predicted by the traditional+PGGRS model, especially when machine learning approaches were used, suggesting that genetic information may have the potential to identify new hypertension cases using machine learning methods in resource-limited areas. CLINICAL TRIAL REGISTRATION: The Henan Rural Cohort Study has been registered at the Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). http://www.chictr.org.cn/showproj.aspx?proj=11375 .

Residential greenness and atherosclerotic cardiovascular disease risk in a rural Chinese adult population.

Residential greenness may be beneficial for cardiovascular health, but the evidence is still scarce, especially in developing countries. This study aimed to assess the associations between exposure to residential greenness and 10-year atherosclerotic cardiovascular disease (ASCVD) risk in a large rural Chinese adult population. This was a cross-sectional study based on 31,162 participants aged 35-74 years with complete data on predictors of the 10-year ASCVD risk from the Henan Rural Cohort Study. The satellite-derived Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) were used to quantify residential greenness in a buffer radius of 500 m, 1000 m, and 3000 m. The high 10-years ASCVD risk was defined as the estimated risk ≥10% based on prediction equations from the China-PAR Project for Chinese populations. Multivariable-adjusted logistic regression models were performed to estimate the associations of greenness exposures with high 10-year ASCVD risk, and mediation analyses were employed to the potential mediators. For per interquartile range (IQR) increase in NDVI500-m, NDVI1000-m, NDVI3000-m, EVI500-m, EVI1000-m, and EVI3000-m, the adjusted OR (95% CI) of high 10-years ASCVD risk was 0.828 (0.793-0.866), 0.850 (0.817-0.885), 0.823 (0.792-0.855), 0.848 (0.809-0.889), 0.863 (0.826-0.901), 0.843 (0.805-0.883), respectively. Strong associations of NDVI500-m and EVI500-m with high 10-years ASCVD risk were found among participants with lower education level and lower averaged monthly income. The associations of greenness exposures with high 10-year ASCVD risk were partially explained by particulate matter with an aerodynamic diameter ≤1 µm, BMI, and physical activity. Enhancing residential greenness exposure may be beneficial for reducing the high 10-year ASCVD risk in rural Chinese adults.

Associations of mixture of air pollutants with estimated 10-year atherosclerotic cardiovascular disease risk modified by socio-economic status: The Henan Rural Cohort Study.

BACKGROUND: Low socio-economic status (SES) and exposure to single-air pollutant relate to increased prevalent atherosclerotic cardiovascular diseases (ASCVD), however, interactive effect between SES and exposure to single- or multiple-air pollutants on high 10-year ASCVD risk remains unclear. METHODS: A total of 31,162 individuals were derived from the Henan Rural Cohort Study. Concentrations of air pollutants (particulate matter with an aerodynamic diameter ≤ 1.0 µm (PM1), ≤2.5 µm (PM2.5) or ≤10 µm (PM10), nitrogen dioxide (NO2)) were assessed using a spatiotemporal model based on satellites data. Independent and joint associations of SES, single- and multiple- air pollutants with high 10-year ASCVD risk were evaluated using logistic regression models, quantile g-computation and structural equation models. The interactive effects of SES and exposure to single- or multiple air pollutants on high 10-year ASCVD risk were visualized by using Interaction plots. RESULTS: Exposure to single air pollutant (PM1, PM2.5, PM10 or NO2) related to increased high 10-year ASCVD risk among individuals with low education level or personal average monthly income, compared to the ones with high education level or personal average monthly income. Furthermore, similar results of exposure to mixture of air pollutants with high 10-year ASCVD risk were observed. Positive interactive effects between low SES and exposure to high single air pollutant or the mixture of air pollutants on high 10-year ASCVD risk were observed. CONCLUSION: Positive association of low SES with high 10-year ASCVD risk was amplified by exposure to high levels of single air pollutant or a mixture of air pollutants, implying that individuals with low SES may more susceptible to air pollution-related adverse health effect.

Associations of spicy food flavour and intake frequency with blood lipid levels and risk of abnormal serum lipid levels in Chinese rural population: a cross-sectional study.

OBJECTIVE: The purpose of the current study was to investigate associations between spicy food intake and serum lipids levels in Chinese rural population. DESIGN: Information on spicy food flavour and intake frequency was obtained using a two-item questionnaire survey. Dietary data were collected using a validated thirteen-item FFQ. Fasting blood samples were collected and measured for total cholesterol (TC), TAG, HDL-cholesterol and LDL-cholesterol. Multivariate linear and logistic regression models were employed to examine the relationship between spicy food and serum lipids levels according to the spicy food flavour and intake frequency, respectively. SETTING: A cross-sectional study in Henan Province. PARTICIPANTS: 38 238 participants aged 18-79 years old. RESULTS: Spicy flavour and intake frequency were consistently associated with decreased TC and non-HDL-cholesterol levels but mildly associated with elevated TAG levels. Each level increment in spicy flavour was inversely associated with high TC (OR: 0·91; 95 % CI 0·88, 0·93) and high non-HDL-cholesterol (OR: 0·88; 95 % CI 0·85, 0·91) but positively associated with high TAG (OR: 1·04; 95 % CI 1·01, 1·07). Similarly, 1-d increment in spicy food intake frequency was also inversely associated with high TC (OR: 0·92; 95 % CI 0·91, 0·94) and high non-HDL-cholesterol (OR: 0·91; 95 % CI 0·89, 0·93) but positively associated with high TAG (OR: 1·04; 95 % CI 1·02, 1·06). CONCLUSIONS: Spicy food intake was mildly associated with increased risk of abnormal TAG level, significantly associated with decreased risk of abnormal TC and non-HDL levels. Spicy food intake may be contribute to the management of lipid levels.

Independent and combined associations of solid-fuel use and smoking with obesity among rural Chinese adults.

Although solid-fuel use or smoking is associated with obesity measured by body mass index (BMI), research on their interactive effects on general and central obesity is limited. Data of 20,140 individuals in the Henan Rural Cohort Study was examined the independent and combined associations of solid-fuel use and smoking with prevalent obesity, which was measured by BMI, waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), body fat percentage (BFP), and visceral fat index (VFI). Multiple adjusted logistic regression models showed that the OR (95% CI) of prevalent obesity measured by BMI associated with exposure to solid fuels alone or with smoking was 0.78 (0.70, 0.86) or 0.46 (0.32, 0.66), compared with neither smoking nor solid-fuel exposure. Similar results had been found in other obese anthropometric indices and in the results of linear regression analysis. The results indicated that solid-fuel use and smoking have a synergistic effect on reduction in obesity indices. The effects of household air pollution from solid-fuel use and smoking on obesity should be considered when exploring the influencing factors of obesity.

Long-term exposure to air pollutants enhanced associations of obesity with blood pressure and hypertension.

Although obesity reflected by BMI can enhance the association of air pollution with increase blood pressures (BP) and prevalent hypertension in susceptible population, there remains lack evidence on interactive effects of different obesity indices and air pollutants on BP and prevalent hypertension in rural adults. 39,259 individuals were recruited from the Henan Rural Cohort. Concentrations of air pollutants (PM1, PM2.5, PM10 and NO2) were evaluated by a spatio-temporal model based on satellites data. Independent associations of air pollutants and obesity reflected by BMI, WC, WHR, WHtR, BFP and VFI on BP indicators (SBP, DBP, MAP and PP) and prevalent hypertension were analyzed by linear regression and logistic regression models, respectively. Furthermore, their additive effects were quantified by RERI, AP and S. Six obesity indices enhanced the associations of four air pollutants and BP indicators. Individuals with high PM1 concentrations plus obesity classified by BMI, WC, WHR, WHtR, BFP and VFI had a 4.18-fold (95% CI: 3.86, 4.53), 3.58-fold (95% CI: 3.34, 3.84), 3.53-fold (95% CI: 3.28, 3.81), 4.02-fold (95% CI: 3.72, 4.35), 3.89-fold (95% CI: 3.59, 4.23), 3.87-fold (95% CI: 3.62, 4.14) increase in prevalent hypertension, respectively, compared to non-obese individuals with low PM1 concentrations; similar results were observed for combined effect of PM2.5, PM10 or NO2 and obesity indices on prevalent hypertension. The significant values of RERI, AP and S indicated additive effects of air pollutants and obesity indices on hypertension. Obesity amplified the effects of exposure to high levels of air pollutants on increased BP values and prevalent hypertension, implying that obese individuals may be susceptible to elevate BP and prevalent hypertension in relation to air pollution exposure. CLINICAL TRIAL REGISTRATION: The Henan Rural Cohort study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699, http://www.chictr.org.cn/showproj.aspx?proj=11375).

Genetic Risk Score Increased Discriminant Efficiency of Predictive Models for Type 2 Diabetes Mellitus Using Machine Learning: Cohort Study.

Background: Previous studies have constructed prediction models for type 2 diabetes mellitus (T2DM), but machine learning was rarely used and few focused on genetic prediction. This study aimed to establish an effective T2DM prediction tool and to further explore the potential of genetic risk scores (GRS) via various classifiers among rural adults. Methods: In this prospective study, the GRS for a total of 5,712 participants from the Henan Rural Cohort Study was calculated. Cox proportional hazards (CPH) regression was used to analyze the associations between GRS and T2DM. CPH, artificial neural network (ANN), random forest (RF), and gradient boosting machine (GBM) were used to establish prediction models, respectively. The area under the receiver operating characteristic curve (AUC) and net reclassification index (NRI) were used to assess the discrimination ability of the models. The decision curve was plotted to determine the clinical-utility for prediction models. Results: Compared with the individuals in the lowest quintile of the GRS, the HR (95% CI) was 2.06 (1.40 to 3.03) for those with the highest quintile of GRS (Ptrend < 0.05). Based on conventional predictors, the AUCs of the prediction model were 0.815, 0.816, 0.843, and 0.851 via CPH, ANN, RF, and GBM, respectively. Changes with the integration of GRS for CPH, ANN, RF, and GBM were 0.001, 0.002, 0.018, and 0.033, respectively. The reclassifications were significantly improved for all classifiers when adding GRS (NRI: 41.2% for CPH; 41.0% for ANN; 46.4% for ANN; 45.1% for GBM). Decision curve analysis indicated the clinical benefits of model combined GRS. Conclusion: The prediction model combined with GRS may provide incremental predictions of performance beyond conventional factors for T2DM, which demonstrated the potential clinical use of genetic markers to screen vulnerable populations. Clinical Trial Registration: The Henan Rural Cohort Study is registered in the Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). http://www.chictr.org.cn/showproj.aspx?proj=11375.

Associations of residing greenness and long-term exposure to air pollution with glucose homeostasis markers.

BACKGROUND: Although long-term exposure to higher air pollutants and lower residing greenness related to disorders of glucose homeostasis have been reported, their interaction effects on glucose homeostasis in developing countries remained unclear. METHODS: A total of 35, 482 participants were obtained from the Henan Rural Cohort (n = 39, 259). Exposure to air pollutants (PM1, PM2.5, PM10 and NO2) were predicted by using a spatiotemporal model-based on satellites data. Residing greenness was reflected by Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI) which were derived from satellites data. Independent associations of single or mixture of air pollutant or residing greenness with glucose homeostasis markers were analyzed by quantile regression models and quantile g (qg)-computation method, respectively. Furthermore, interaction effects of residing greenness and air pollution on glucose homeostasis markers were analyzed by generalized additive models. RESULTS: Positive associations of single or mixture of air pollutants (PM1, PM2.5, PM10 or NO2) with fasting plasma glucose (FPG) were observed, while negative associations of single or mixture of air pollutants with insulin or HOMA-ß were observed. Residing greenness was negatively associated with FPG but positively related to insulin or HOMA-ß. Quantile regression revealed the heterogeneity were observed in the associations the residing greenness or air pollutants with glucose homeostasis markers (insulin or HOMA-ß) across deciles of the glucose homeostasis markers distributions. Furthermore, joint associations of single air pollutant and residing greenness on glucose homeostasis markers were found. CONCLUSIONS: The results indicated that exposure to air pollution had negative effect on glucose homeostasis markers and these effects may be modified by living in higher green space. These findings suggest that increased residing greenness and air pollution control may have joint effect on decreased the risk of diabetes. CLINICAL TRIAL REGISTRATION: The Henan Rural Cohort study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699, http://www.chictr.org.cn/showproj.aspx?proj=11375).

Genetic factors increase the identification efficiency of predictive models for dyslipidaemia: a prospective cohort study.

BACKGROUND: Few studies have developed risk models for dyslipidaemia, especially for rural populations. Furthermore, the performance of genetic factors in predicting dyslipidaemia has not been explored. The purpose of this study is to develop and evaluate prediction models with and without genetic factors for dyslipidaemia in rural populations. METHODS: A total of 3596 individuals from the Henan Rural Cohort Study were included in this study. According to the ratio of 7:3, all individuals were divided into a training set and a testing set. The conventional models and conventional+GRS (genetic risk score) models were developed with Cox regression, artificial neural network (ANN), random forest (RF), and gradient boosting machine (GBM) classifiers in the training set. The area under the receiver operating characteristic curve (AUC), net reclassification index (NRI), and integrated discrimination index (IDI) were used to assess the discrimination ability of the models, and the calibration curve was used to show calibration ability in the testing set. RESULTS: Compared to the lowest quartile of GRS, the hazard ratio (HR) (95% confidence interval (CI)) of individuals in the highest quartile of GRS was 1.23(1.07, 1.41) in the total population. Age, family history of diabetes, physical activity, body mass index (BMI), triglycerides (TGs), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were used to develop the conventional models, and the AUCs of the Cox, ANN, RF, and GBM classifiers were 0.702(0.673, 0.729), 0.736(0.708, 0.762), 0.787 (0.762, 0.811), and 0.816(0.792, 0.839), respectively. After adding GRS, the AUCs increased by 0.005, 0.018, 0.023, and 0.015 with the Cox, ANN, RF, and GBM classifiers, respectively. The corresponding NRI and IDI were 25.6, 7.8, 14.1, and 18.1% and 2.3, 1.0, 2.5, and 1.8%, respectively. CONCLUSION: Genetic factors could improve the predictive ability of the dyslipidaemia risk model, suggesting that genetic information could be provided as a potential predictor to screen for clinical dyslipidaemia. TRIAL REGISTRATION: The Henan Rural Cohort Study has been registered at the Chinese Clinical Trial Register. (Trial registration: ChiCTR-OOC-15006699 . Registered 6 July 2015 - Retrospectively registered).

Health-related quality of life among rural adults with type 2 diabetes mellitus: a cross-sectional study.

BACKGROUND: Previous reports about health-related quality of life (HRQoL) of type 2 diabetes mellitus (T2DM) concentrated on general patients rather than patients in rural areas with poor infrastructure and limited resources. Thus, the aims of this study were to evaluate the HRQoL of diabetics in the countryside and explore its influencing factors. METHODS: A total of 23 053 participants aged from 18 to 79 years were drawn from the Henan Rural Cohort Study for this cross-sectional study. The HRQoL of participants were assessed by utility index and VAS-score of European Quality of Life Five Dimension Five Level Scale (EQ-5D-5L) instrument. Binary logistic regression, generalized linear and tobit regression models were used to estimate the potential influencing factors on HRQoL. RESULTS: This study (23 053 participants) included 2231 T2DM patients with a crude prevalence of 9.68%. The utility index and VAS-score in health group were 0.96 ± 0.10 and 78.85 ± 14.53, while in T2DM group were 0.93 ± 0.15 and 74.09 ± 16.09, respectively. In total, most diabetics reported problem about pain/discomfort dimension. Being old, poverty, low physical activity, and with comorbidities was negatively related to HRQoL of diabetics, while high educational level was positively related to HRQoL. CONCLUSION: HRQoL of rural T2DM patients depended on several sociodemographic factors. More attention should be paid to diabetics with poor socioeconomic status in rural areas. CLINICAL TRIAL REGISTRATION: The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699) http://www.chictr.org.cn/showproj.aspx?proj=11375.

Long-term exposure to ambient PM1 strengthened the association of depression/anxiety symptoms with poor sleep quality: The Henan Rural Cohort study.

Evidence from numerous epidemiological studies for the relationship between mental disorder and sleep quality was inconclusive and few studies assessed the modification effect of exposure to ambient air PM1 (particulate matter with an aerodynamic diameter ≤ 1.0 µm) on this association. In this study, 27,572 participants aged 18-79 years from The Henan Rural Cohort study were included in the final analyses. The Patient Health Questionnaire-2 (PHQ-2) and Generalized Anxiety Disorder-2 (GAD-2) scales were used to estimate the frequency of depression and anxiety symptoms of all participants, respectively. The Pittsburgh Sleep Quality Index (PSQI) scale was used to assess night sleep quality and PSQI global score (GSC) ≥ 6 was classified as poor sleep quality. The three-year average exposure concentration of PM1 before the baseline survey was determined as long-term exposure concentration of ambient PM1. Logistic regression model was conducted to estimate the independent or joint effect of depression/anxiety symptoms and ambient PM1 exposure on poor sleep quality. In the adjusted models, the odds ratios (ORs) and 95% confidence intervals (95% CIs) of poor sleep quality associated with depression and anxiety symptoms were 3.75 (3.37, 4.17) and 3.42 (3.06, 3.81), respectively, and that associated with long-term exposure to PM1 was 1.06 (1.03, 1.09). An interaction effect was observed between anxiety symptoms score and PM1 concentration on poor sleep quality. With the increment of PM1 concentration, the association was strengthened between depression/anxiety symptoms and poor sleep quality. Besides, compared with the reference group, the ORs (95% CIs) of poor sleep quality in those with comorbidity of depression and anxiety symptoms were 4.98 (3.95, 6.29), 5.23 (3.98, 6.87), 5.76 (4.42, 7.49), and 5.58 (3.83, 8.14), respectively, from the first to the fourth quartile level of the PM1 concentration. These findings suggested that long-term exposure to PM1 strengthened the association of depression/anxiety symptoms with poor sleep quality in rural China.

Independent and interactive effect of sitting time and physical activity on prevalence of hyperuricemia: the Henan Rural Cohort Study.

BACKGROUND: There are few studies on the hyperuricemia (HUA) and moderate to vigorous intensity physical activity (PA) and also hardly regarding sitting time (ST). The purpose of this study was to examine the independent and interactive association of PA and ST with HUA. METHODS: A cross-sectional analysis was performed on 38,855 participants (aged 18-79) enrolled from the Henan Rural Cohort Study at baseline (2015 to 2017). PA and ST levels were assessed by using the International Physical Activity Questionnaire (IPAQ). HUA was defined as a serum uric acid level of > 7.0 mg/dL for males and > 6.0 mg/dL for females. Multivariable logistic regression and linear regression models were applied to examine the independent association between PA or ST and HUA and serum uric acid level. Interaction plots were used to visualize the interaction effects of PA and ST on HUA. RESULTS: PA level was inversely related with serum uric acid level (ß - 0.15, 95% confidence interval (CI) - 0.22, - 0.07), but ST was positively related with uric acid level (ß 2.12, 95% CI 1.90, 2.34). Metabolic equivalent (MET-hour/day) was associated with decreased prevalence of HUA (odds ratio (OR) 0.97, 95% CI 0.96, 0.99), while per hour increased for ST was associated with increased HUA (OR 1.05, 95% CI 1.04, 1.06). The interaction of PA and ST was significant (P < 0.001). CONCLUSION: Exposure to higher ST was independently related to increased prevalence of HUA, while vigorous PA with a decreased HUA prevalence. Meanwhile, higher daily ST might attenuate the protective effect of PA on HUA. TRIAL REGISTRATION: The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699 ).