Air pollution, genetic susceptibility, and the risk of atrial fibrillation: A large prospective cohort study.

To date, no study has explored the extent to which genetic susceptibility modifies the effects of air pollutants on the risk of atrial fibrillation (AF). This study was designed to investigate the separate and joint effects of long-term exposure to air pollutants and genetic susceptibility on the risk of AF events. This study included 401,251 participants without AF at baseline from UK Biobank. We constructed a polygenic risk score and categorized it into three categories. Cox proportional hazards models were fitted to assess the separate and joint effects of long-term exposure to air pollutants and genetics on the risk of AF. Additionally, we further evaluated the effect modification of genetic susceptibility. The hazard ratios and corresponding 95% confidence intervals of incident AF for per interquartile range increase in particulate matter with an aerodynamic diameter smaller than 2.5 µm (PM2.5) or 10 µm (PM10), nitrogen dioxide (NO2), and nitrogen oxide (NOx) were 1.044 (1.025, 1.063), 1.063 (1.044, 1.083), 1.061 (1.042, 1.081), and 1.039 (1.023, 1.055), respectively. For the combined effects, participants exposed to high air pollutants levels and high genetic risk had approximately 149.2% (PM2.5), 181.7% (PM10), 170.2% (NO2), and 157.2% (NOx) higher risk of AF compared to those with low air pollutants levels and low genetic risk, respectively. Moreover, the significant additive interactions between PM10 and NO2 and genetic risk on AF risk were observed, with around 16.4% and 35.1% of AF risk could be attributable to the interactive effects. In conclusion, long-term exposure to air pollutants increases the risk of AF, particularly among individuals with high genetic susceptibility.

Long-Term Exposure to Low Concentrations of Ambient Benzene and Mortality in a National English Cohort.

Background: Benzene affects human health through environmental exposure in addition to occupational contact. However, few studies have examined the associations between long-term exposure to low concentrations of ambient benzene and mortality risks in nonoccupational settings.Methods: This prospective cohort study consists of 393,042 participants without stroke, myocardial infarction, or cancer at baseline from the UK Biobank. Annual average concentrations of benzene for each year during follow-up were measured using air dispersion models. The main outcomes were all-cause mortality and mortality from specific causes. Cox proportional-hazards models with time-varying exposure measurements were used to estimate the hazard ratios and 95% confidence intervals (CIs) for mortality risks. Restricted cubic spline models were used to estimate exposure-response relationships.Measurements and Main Results: With each interquartile range increase in the average annual concentration of benzene, the adjusted hazard ratios of mortality risk from all causes, cardiovascular disease, cancer, and respiratory disease were 1.26 (95% CI, 1.24-1.27), 1.24 (95% CI, 1.21-1.28), 1.27 (95% CI, 1.25-1.29), and 1.25 (95% CI, 1.20-1.30), respectively. The monotonically increasing exposure-response curves showed no threshold and plateau within the observed concentration range. Furthermore, the effect of benzene exposure on mortality persisted across different subgroups and was somewhat stronger in younger and White people (P for interaction < 0.05).Conclusions: Long-term exposure to low concentrations of ambient benzene significantly increases mortality risk in the general population. Ambient benzene represents a potential threat to public health, and further investigations are needed to support timely pollution regulation and health protection.

Air pollutants, genetic susceptibility, and abdominal aortic aneurysm risk: a prospective study.

BACKGROUND AND AIMS: Air pollutants are important contributors to cardiovascular diseases, but associations between long-term exposure to air pollutants and the risk of abdominal aortic aneurysm (AAA) are still unknown. METHODS: This study was conducted using a sample of 449 463 participants from the UK Biobank. Hazard ratios and 95% confidence intervals for the risk of AAA incidence associated with long-term exposure to air pollutants were estimated using the Cox proportional hazards model with time-varying exposure measurements. Additionally, the cumulative incidence of AAA was calculated by using the Fine and Grey sub-distribution hazards regression model. Furthermore, this study investigated the combined effects and interactions between air pollutants exposure and genetic predisposition in relation to the risk of AAA onset. RESULTS: Long-term exposure to particulate matter with an aerodynamic diameter <2.5 µm [PM2.5, 1.21 (1.16, 1.27)], particulate matter with an aerodynamic diameter <10 µm [PM10, 1.21 (1.16, 1.27)], nitrogen dioxide [NO2, 1.16 (1.11, 1.22)], and nitrogen oxides [NOx, 1.10 (1.05, 1.15)] was found to be associated with an elevated risk of AAA onset. The detrimental effects of air pollutants persisted even in participants with low-level exposure. For the joint associations, participants with both high levels of air pollutants exposure and high genetic risk had a higher risk of developing AAA compared with those with low concentrations of pollutants exposure and low genetic risk. The respective risk estimates for AAA incidence were 3.18 (2.46, 4.12) for PM2.5, 3.09 (2.39, 4.00) for PM10, 2.41 (1.86, 3.13) for NO2, and 2.01 (1.55, 2.61) for NOx. CONCLUSIONS: In this study, long-term air pollutants exposure was associated with an increased risk of AAA incidence.

Genetic Susceptibility Modifies Relationships Between Air Pollutants and Stroke Risk: A Large Cohort Study.

BACKGROUND: The extent to which genetic susceptibility modifies the associations between air pollutants and the risk of incident stroke is still unclear. This study was designed to investigate the separate and joint associations of long-term exposure to air pollutants and genetic susceptibility on stroke risk. METHODS: The participants of this study were recruited by the UK Biobank between 2006 and 2010. These participants were followed up from the enrollment until the occurrence of stroke events or censoring of data. Hazard ratios (HRs) and 95% CIs for stroke events associated with long-term exposure to air pollutants were estimated by fitting both crude and adjusted Cox proportional hazards models. Additionally, the polygenic risk score was calculated to estimate whether the polygenic risk score modifies the associations between exposure to air pollutants and incident stroke. RESULTS: A total of 502 480 subjects were included in this study. After exclusion, 452 196 participants were taken into the final analysis. During a median follow-up time of 11.7 years, 11 334 stroke events were observed, with a mean age of 61.60 years, and men accounted for 56.2% of the total cases. Long-term exposures to particulate matter with an aerodynamic diameter smaller than 2.5 µm (adjusted HR, 1.70 [95% CI, 1.43-2.03]) or particulate matter with an aerodynamic diameter smaller than 10 µm (adjusted HR, 1.50 [95% CI, 1.36-1.66]), nitrogen dioxide (adjusted HR, 1.10 [95% CI, 1.07-1.12]), and nitrogen oxide (adjusted HR, 1.04 [95% CI, 1.02-1.05]) were pronouncedly associated with increased risk of stroke. Meanwhile, participants with high genetic risk and exposure to high air pollutants had ≈45% (31%, 61%; particulate matter with an aerodynamic diameter smaller than 2.5 µm), 48% (33%, 65%; particulate matter with an aerodynamic diameter smaller than 10 µm), 51% (35%, 69%; nitrogen dioxide), and 39% (25%, 55%; nitrogen oxide) higher risk of stroke compared with those with low genetic risk and exposure to low air pollutants, respectively. Of note, we observed additive and multiplicative interactions between genetic susceptibility and air pollutants on stroke events. CONCLUSIONS: Chronic exposure to air pollutants was associated with an increased risk of stroke, especially in populations at high genetic risk.

Associations of residential greenness with bone mineral density and osteoporosis: the modifying effect of genetic susceptibility.

OBJECTIVES: To investigate the associations of residential greenness with bone mineral density and incident osteoporosis, and further evaluate the potential modifying effect of genetic susceptibility. METHODS: We used the Normalised Difference Vegetation Index (NDVI) at various buffer distances, including 300 m (NDVI300m), 500 m (NDVI500m), 1000 m (NDVI1000m) and 1500 m (NDVI1500m), to serve as indicators of greenness. We fitted linear regression, logistic regression and Cox proportional hazard models to assess the associations of residential greenness with estimated bone mineral density (eBMD), prevalent osteoporosis and incident osteoporosis, respectively. With the Polygenic Risk Score (PRS) for osteoporosis, we further assessed the joint effects of genetic risk and greenness on the risk of osteoporosis. We conducted causal mediation analyses to explore potential mediators. RESULTS: Each IQR increase in NDVI300m was associated with 0.0007 (95% CI 0.0002 to 0.0013) increase in eBMD, 6% lower risk of prevalent osteoporosis (OR 0.94; 95% CI 0.92 to 0.97) and 5% lower risk of incident osteoporosis (HR 0.95; 95% CI 0.93 to 0.98). The joint effects of greenness and PRS on the risk of osteoporosis displayed a clear dose-response pattern. Compared with individuals exposed to low NDVI levels and high genetic risk, those exposed to high NDVI levels and low genetic risk had a 56% (95% CI 51% to 61%) lower risk of osteoporosis. The primary mediators in the association between greenness and incident osteoporosis were identified as PM2.5 and NO2. CONCLUSIONS: Residential greenness was associated with higher bone mineral density and decreased risk of incident osteoporosis.

HLA-C*07:01 and HLA-DQB1*02:01 protect against white matter hyperintensities and deterioration of cognitive function: A population-based cohort study.

BACKGROUND: Neuroinflammation and aberrant immune regulation are increasingly implicated in the pathophysiology of white matter hyperintensities (WMH), an imaging marker of cerebrovascular pathologies and predictor of cognitive impairment. The role of human leukocyte antigen (HLA) genes, critical in immunoregulation and associated with susceptibility to neurodegenerative diseases, in WMH pathophysiology remains unexplored. METHODS: We performed association analyses between classical HLA alleles and WMH volume, derived from MRI scans of 38 302 participants in the UK Biobank. To identify independent functional alleles driving these associations, we conducted conditional forward stepwise regression and lasso regression. We further investigated whether these functional alleles showed consistent associations with WMH across subgroups characterized by varying levels of clinical determinants. Additionally, we validated the clinical relevance of the identified alleles by examining their association with cognitive function (n = 147 549) and dementia (n = 460 029) in a larger cohort. FINDINGS: Four HLA alleles (DQB1*02:01, DRB1*03:01, C*07:01, and B*08:01) showed an association with reduced WMH volume after Bonferroni correction for multiple comparisons. Among these alleles, DQB1*02:01 exhibited the most significant association (ß = -0.041, 95 % CI: -0.060 to -0.023, p = 1.04 × 10-5). Forward selection and lasso regression analyses indicated that DQB1*02:01 and C*07:01 primarily drove this association. The protective effect against WMH conferred by DQB1*02:01 and C*07:01 persisted in clinically relevant subgroups, with a stronger effect observed in older participants. Carrying DQB1*02:01 and C*07:01 was associated with higher cognitive function, but no association with dementia was found. INTERPRETATION: Our population-based findings support the involvement of immune-associated mechanisms, particularly both HLA class I and class II genes, in the pathogenesis of WMH and subsequent consequence of cognitive functions.

Residential greenness and incident idiopathic pulmonary fibrosis: A prospective study.

BACKGROUND: The impact of residential greenness on incident idiopathic pulmonary fibrosis (IPF) is unknown. We aimed to assess the association between residential greenness and incident IPF, identify underlying pathways, and further evaluate the effect among different genetic subgroups. METHODS: 469,348 participants in the UK Biobank were included and followed until December 2020. Normalized difference vegetation index (NDVI) within 300-, 500-, 1000-, and 1500-m buffers (NDVI300m, NDVI500m, NDVI1000m, and NDVI1500m) were employed as indicators of greenness. The polygenic risk score (PRS) was constructed based on 13 independent SNPs. Cox models were fitted to assess the association of residential greenness with incident IPF. Casual mediation analyses were applied to evaluate potential mediators. FINDINGS: After a median follow-up of 11.85 years, 1574 IPF cases were identified. We found residential greenness inversely associated with incident IPF. The HRs (95%CIs) for each interquartile increase of NDVI300m, NDVI500m, NDVI1000m, NDVI1500m were 0.93 (0.87, 0.99), 0.92 (0.86, 0.98), 0.89 (0.83, 0.95), and 0.89 (0.83, 0.95), respectively. The association was stronger among individuals with intermediate or high genetic risk. In mediation analyses, the main mediators identified were PM2.5 and NO2, with proportion mediated estimated to be 31.92% and 40.61% respectively for NDVI300m. INTERPRETATION: Residential greenness was associated with reduced risk of incident IPF.

Genetic susceptibility and lifestyle modify the association of long-term air pollution exposure on major depressive disorder: a prospective study in UK Biobank.

BACKGROUND: Evidence linking air pollution to major depressive disorder (MDD) remains sparse and results are heterogeneous. In addition, the evidence about the interaction and joint associations of genetic risk and lifestyle with air pollution on incident MDD risk remains unclear. We aimed to examine the association of various air pollutants with the risk of incident MDD and assessed whether genetic susceptibility and lifestyle influence the associations. METHODS: This population-based prospective cohort study analyzed data collected between March 2006 and October 2010 from 354,897 participants aged 37 to 73 years from the UK Biobank. Annual average concentrations of PM2.5, PM10, NO2, and NOx were estimated using a Land Use Regression model. A lifestyle score was determined based on a combination of smoking, alcohol drinking, physical activity, television viewing time, sleep duration, and diet. A polygenic risk score (PRS) was defined using 17 MDD-associated genetic loci. RESULTS: During a median follow-up of 9.7 years (3,427,084 person-years), 14,710 incident MDD events were ascertained. PM2.5 (HR: 1.16, 95% CI: 1.07-1.26; per 5 µg/m3) and NOx (HR: 1.02, 95% CI: 1.01-1.05; per 20 µg/m3) were associated with increased risk of MDD. There was a significant interaction between the genetic susceptibility and air pollution for MDD (P-interaction < 0.05). Compared with participants with low genetic risk and low air pollution, those with high genetic risk and high PM2.5 exposure had the highest risk of incident MDD (PM2.5: HR: 1.34, 95% CI: 1.23-1.46). We also observed an interaction between PM2.5 exposure and unhealthy lifestyle (P-interaction < 0.05). Participants with the least healthy lifestyle and high air pollution exposures had the highest MDD risk when compared to those with the most healthy lifestyle and low air pollution (PM2.5: HR: 2.22, 95% CI: 1.92-2.58; PM10: HR: 2.09, 95% CI: 1.78-2.45; NO2: HR: 2.11, 95% CI: 1.82-2.46; NOx: HR: 2.28, 95% CI: 1.97-2.64). CONCLUSIONS: Long-term exposure to air pollution is associated with MDD risk. Identifying individuals with high genetic risk and developing healthy lifestyle for reducing the harm of air pollution to public mental health.

The association between telomere length and non-alcoholic fatty liver disease: a prospective study.

BACKGROUND: Research on the association between telomere length (TL) and incident non-alcoholic fatty liver disease (NAFLD) is limited. This study examined this association and further assessed how TL contributes to the association of NAFLD with its known risk factors. METHODS: Quantitative PCR (polymerase chain reaction) was employed to assess leucocyte telomere length. Polygenic risk score (PRS) for NAFLD, air pollution score, and lifestyle index were constructed. Cox proportional hazard models were conducted to estimate the hazard ratios (HRs) and 95% confidence intervals. RESULTS: Among 467,848 participants in UK Biobank, we identified 4809 NAFLD cases over a median follow-up of 12.83 years. We found that long TL was associated with decreased risk of incident NAFLD, as each interquartile range increase in TL resulted in an HR of 0.93 (95% CI 0.89, 0.96). TL partly mediated the association between age and NAFLD (proportion mediated: 15.52%). When assessing the joint effects of TL and other risk factors, the highest risk of NAFLD was found in participants with low TL and old age, low TL and high air pollution score, low TL and unfavorable lifestyle, and low TL and high PRS, compared to each reference group. A positive addictive interaction was observed between high PRS and low TL, accounting for 14.57% (2.51%, 27.14%) of the risk of NAFLD in participants with low telomere length and high genetic susceptibility. CONCLUSIONS: Long telomere length was associated with decreased risk of NAFLD incidence. Telomere length played an important role in NAFLD.

Air pollutants, genetic susceptibility and risk of incident idiopathic pulmonary fibrosis.

BACKGROUND: Air pollutants are considered as non-negligible risk factors of idiopathic pulmonary fibrosis (IPF). However, the relationship between long-term air pollution and the incidence of IPF is unknown. Our objective was to explore the associations of air pollutants with IPF risk and further assess the modification effect of genetic susceptibility. METHODS: We used land-use regression model estimated concentrations of nitrogen dioxide (NO2), nitrogen oxides (NO x ) and particulate matter (fine particulate matter with diameter <2.5 µm (PM2.5) and particulate matter with diameter <10 µm (PM10)). The polygenic risk score (PRS) was constructed using 13 independent single nucleotide polymorphisms. Cox proportional hazard models were used to evaluate the associations of air pollutants with IPF risk and further investigate the modification effect of genetic susceptibility. Additionally, absolute risk was calculated. RESULTS: Among 433 738 participants from the UK Biobank, the incidence of IPF was 27.45 per 100 000 person-years during a median follow-up of 11.78 years. The adjusted hazard ratios of IPF for each interquartile range increase in NO2, NO x and PM2.5 were 1.11 (95% CI 1.03-1.19), 1.07 (95% CI 1.01-1.13) and 1.09 (95% CI 1.02-1.17), respectively. PM2.5 had the highest population attribution risk, followed by NO x and NO2. There were additive interactions between NO2, NO x and PM2.5 and genetic susceptibility. Participants with a high PRS and high air pollution had the highest risk of incident IPF compared with those with a low PRS and low air pollution (adjusted hazard ratio: NO2 3.94 (95% CI 2.77-5.60), NO x 3.08 (95% CI 2.21-4.27), PM2.5 3.65 (95% CI 2.60-5.13) and PM10 3.23 (95% CI 2.32-4.50)). CONCLUSION: Long-term exposures to air pollutants may elevate the risk of incident IPF. There are additive effects of air pollutants and genetic susceptibility on IPF risk.

Effects of residential greenness and genetic predisposition on hemoglobin A1c and type 2 diabetes: Gene-environment interaction analysis from a nationwide study.

BACKGROUND: Current evidence on the relations of residential greenness with glucose homeostasis and type 2 diabetes (T2D) remained largely uncertain. Most importantly, no prior studies have investigated whether genetic predisposition modifies the above associations. METHODS: We leveraged data from the UK Biobank prospective cohort study, with participants enrolled between 2006 and 2010. Residential greenness was assessed by using the Normalized Difference Vegetation Index, and the weighting T2D-specific genetic risk score (GRS) was constructed based on previously published genome-wide association studies. Linear regression models and logistic regression models were used to investigate associations of residential greenness with glycated hemoglobin (HbA1c) and T2D prevalence, respectively. Interaction models explored whether genetic predisposition modifies greenness-HbA1c/T2D associations. RESULTS: Among 315,146 individuals (mean [SD] age, 56.59 [8.09] years), each one-unit increase in residential greenness was associated with reduction in HbA1c (ß: -0.87, 95% CI: -1.16 to -0.58) and a 12% decrease in odds of T2D (OR: 0.88, 95% CI: 0.79 to 0.98), respectively. Additionally, interaction analyses further demonstrated that residential greenness and genetic risk had cumulative effects on HbA1c and T2D. Compared with individuals who were exposed to low greenness and had high GRS, participants with low GRS and high greenness had a significant decline in HbA1c (ß: -2.96, 95% CI: -3.10 to -2.82, P for interaction = 0.04) and T2D (OR: 0.47, 95% CI: 0.45 to 0.50, P for interaction = 0.09). CONCLUSIONS: We add novel evidence that residential greenness has protective effects on glucose metabolism and T2D, and those beneficial effects can be amplified by low genetic risk. Our findings may facilitate the improvement of the living environment and the development of prevention strategies by considering genetic susceptibility to T2D.

Effect of body mass index trajectory on lifetime risk of cardiovascular disease in a Chinese population: A cohort study.

BACKGROUND AND AIMS: The longitudinal trajectories of body mass index (BMI) can reflect the pattern of BMI changes. Lifetime risk quantifies the cumulative risk of developing a disease over the remaining life of a person. We aimed to identify the trajectory of BMI and explore its association with cardiovascular disease (CVD) in the Chinese population. METHODS AND RESULTS: A total of 68,603 participants with a mean age of 55.46 years were included from the Kailuan cohort in Tangshan, China, who were free of CVD and cancer and with repeated measurements of BMI from 2006 to 2010. A latent mixture model was used to identify BMI trajectories. An improved Kaplan-Meier estimator was used to predict the lifetime risk of CVD according to BMI trajectories. During a median follow-up of 7.0 years, 3325 participants developed CVD. Five BMI trajectories were identified at three index ages (35, 45, and 55) respectively. For index age 35 years, compared with the stable low-normal weight group (22.7% [95% CI, 20.0%-25.4%]), the stable high-normal weight (27.6% [25.6%-29.5%]), stable overweight (29.4% [27.4%-31.4%]), stable-low obesity (32.8% [30.0%-35.5%]), and stable-high obesity (38.9% [33.3%-44.5%]) groups had a higher lifetime risk of CVD (P < 0.05). We observed similar patterns for stroke and myocardial infarction. Similarly, the lifetime risk of CVD was higher in the long-term overweight and obese groups at 45 and 55 index ages. CONCLUSIONS: Long-term overweight and obesity were associated with an increased lifetime risk of CVD. Our findings could assist in predicting the population burden of CVD.

Short-term exposure to reduced specific-size ambient particulate matter increase the risk of cause-specific cardiovascular disease: A national-wide evidence from hospital admissions.

Evidence for the health effects of ambient PM1 (particulate matter with an aerodynamic diameter ≤ 1 µm) pollution is limited, and it remains unclear whether a smaller particulate matter has a greater impact on human health. We conducted a time-series study in 184 major cities by extracting daily hospital data on admissions for ischemic heart disease, heart failure, heart rhythm disturbances, and stroke between 2014 and 2017 from a medical insurance claims database of 0.28 billion beneficiaries. City-specific associations were estimated with over-dispersed generalized additive models. A random-effects meta-analysis was used to estimate regional and national average associations. We conducted stratified and meta-regression analyses to explore potential effect modifiers of the association. We recorded 8.83 million cardiovascular admissions during the study period. At the national-average level, a 10-µg/m3 increase in same-day PM1, PM2.5(particulate matter with an aerodynamic diameter ≤ 2.5 µm) and PM10(particulate matter with an aerodynamic diameter ≤ 10 µm) concentrations corresponded to a 1.14% (95% confidence interval 0.88-1.41%), 0.55% (0.40-0.70%), and 0.45% (0.36-0.55%) increase in cardiovascular admissions, respectively. PM1 exposure was also positively associated with all cardiovascular disease subtypes, including ischemic heart disease (1.28% change; 0.99-1.56%), heart failure (1.30% change; 0.70-1.91%), heart rhythm disturbances (1.11% change; 0.65-1.58%), and ischemic stroke (1.29% change; 0.88-1.71%). The associations between PM1 and cardiovascular admissions were stronger in cities with lower PM1 levels, higher air temperatures and relative humidity, as well as in subgroups with elder age (all P < 0.05). This study provides robust evidence of short-term associations between PM1 concentrations and increased hospital admissions for all major cardiovascular diseases in China. Our findings suggest a greater short-term impact on cardiovascular risk from PM1 in comparison to PM2.5 and PM10.

Continuous metabolic syndrome severity score and the risk of CVD and all-cause mortality.

BACKGROUND: The dualistic diagnostic criteria for metabolic syndrome overlooked the severity of metabolic syndrome, and the relationships between the severity of metabolic syndrome and adverse health conditions are poorly characterized. We therefore aimed to investigate the associations of metabolic syndrome severity with incident cardiovascular disease (CVD)/all-cause mortality. METHODS: A total of 116,772 participants from the Kailuan study were followed up biennially between 2006 and 2018. The severity of metabolic syndrome was evaluated using a continuous metabolic syndrome severity score (MetS score). Cox proportional hazards model was used to examine the association between MetS score and the risk of CVD and all-cause mortality. Restricted cubic spline analyses were performed to explore the dose-response associations. RESULTS: We found that the risk of CVD and all-cause mortality increased consistently with the MetS score. In the multivariable-adjusted model, the hazard ratios of CVD and all-cause mortality were 2.05 (95% CI 1.86-2.25) and 1.45 (95% CI 1.35-1.56), respectively, in those subjects>75th percentile compared with those <25th percentile. Additionally, a J-shaped dose-response relationship was found between MetS score and the risk of all-cause mortality (pnonlinearity <.001), while a linear relationship between MetS score and the risk of CVD was observed in this study (pnonlinearity  = .737). CONCLUSIONS: This study suggests significant dose-response relationships between MetS score and the risk of CVD/mortality. Subjects without metabolic syndrome but with a relatively high MetS score should raise their awareness and pay more attention to the possible increased risk of CVD events.

Metabolic syndrome severity score and the progression of CKD.

BACKGROUND: Metabolic syndrome severity, expressed by the continuous metabolic syndrome risk score (MetS score), has been demonstrated to be able to predict future health conditions. However, little is known about the association between MetS score and renal function. METHODS: A total of 22,719 participants with normal renal function abstracted from the Kailuan Study were followed from 2006 to 2016. The new onset of chronic kidney disease (CKD) was defined as eGFR <60 ml/min per 1.73 m2 and/or proteinuria >300 mg/dl. Progressive decline in renal function was defined as an annual change rate of eGFR below the 10th percentile of the whole population. RESULTS: In the multivariate-adjusted model, we found that the risk of progressive decline in renal function increased consistently with the MetS score, with an odds ratio of 1.49 (95% CI, 1.28, 1.73) for those subjects>75th percentile compared with those <25th percentile. Additionally, a high MetS score was found to be associated with an increased risk of CKD, with a hazard ratio of 1.53 (95% CI, 1.33, 1.78) for subjects >75th percentile compared with those <25th percentile. CONCLUSIONS: Our findings suggested that the MetS score was associated with an increased risk of a progressive decline in renal function and was also a strong and independent risk factor for the development of CKD. These findings provide evidence of the potential clinical utility of the MetS score for assessing metabolic syndrome severity to detect the risk of decreased renal function and CKD.

Short-term exposure to gaseous air pollutants and daily hospitalizations for acute upper and lower respiratory infections among children from 25 cities in China.

To examine the short-term association between gaseous air pollutants (CO, NO2, SO2, and O3) and all-cause respiratory disease, acute upper respiratory infections (AURIs) as well as acute lower respiratory infections (ALRIs) among children, we conducted the study from 25 major cities in China. Hospitalization records of children aged 0-18 years due to all-cause respiratory diseases (889,926), AURIs (97,858), and ALRIs (642,154) from 2016 to 2019 were extracted. Concentrations of CO, NO2, SO2, and O3 were averaged across monitoring stations. Generalized additive models were used to estimate the associations between gaseous air pollutants and daily hospitalizations for all-cause respiratory disease, AURIs, and ALRIs. The meta-analysis was used to combine the city-specific estimates. A 10 mg/m3 increase in CO at lag01, and a 10 µg/m3 increase in NO2, SO2, and O3 at lag01 were associated with 1.65% (95%CI, 0.41-2.91), 0.54% (95%CI, 0.30-0.79), 0.60% (95%CI, 0.22-0.99), and 0.23% (95%CI, 0.06-0.39) increase of hospitalizations due to all-cause respiratory disease, respectively. For the disease subtype, O3 only had adverse effects on AURIs, CO and SO2 mainly on ALRIs, and NO2 on both AURIs and ALRIs. Children aged 4-6years were more vulnerable to the effects of CO and NO2, but those aged <1year were more susceptible to SO2 and O3. Besides, the O3 effect was stronger in the warm season than in the cold season. The study indicated that short-term exposure to CO, NO2, SO2, and O3 was associated with increased hospitalization for pediatric respiratory disease, and the association may vary by position of the respiratory tract, age, and season.

Lifetime risk of cardiovascular disease and life expectancy with and without cardiovascular disease according to changes in metabolic syndrome status.

BACKGROUND AND AIMS: The relationship between dynamic changes in metabolic syndrome (MetS) status and lifetime risk of cardiovascular disease (CVD) has not been reliably quantified. This study aimed to estimate lifetime risk of CVD and life expectancy with and without CVD according to dynamic MetS status. METHODS AND RESULTS: Dynamic changes in MetS status were assessed: MetS-free, MetS-chronic, MetS-developed, and MetS-recovery groups. We used Modified Kaplan-Meier method to estimate lifetime risk and used multistate life table method to calculate life expectancy. Participants free of CVD at index ages 35 (n = 40 168), 45 (n = 33 569), and 55 (n = 18 546) years. At index age 35 years, we recorded 1341 CVD events during a median follow-up of 6.1 years. Lifetime risk of 33.9% (95% CI: 26.9%-41.0%) in MetS-recovery group was lower than that of 39.4% (95% CI: 36.1%-42.8%) in MetS-chronic group. Lifetime risk of 37.8% (95% CI: 30.6%-45.1%) in MetS-developed group was higher than that of 26.4% (95% CI: 22.7%-30.0%) in MetS-free group. At index age 35 years, life expectancy free of CVD for MetS-recovery group (44.1 years) was higher than that for MetS-chronic group (38.8 years). Life expectancy free of CVD for MetS-developed group (41.9 years) was lower than that for MetS-free group (46.7 years). CONCLUSIONS: Recovery from MetS was associated with decreased lifetime risk of CVD and a longer life expectancy free of CVD, whereas development of MetS was associated with increased lifetime risk of CVD and a shorter life expectancy free of CVD.

Role of socioeconomic, lifestyle, and clinical factors in the progression of cardiometabolic multimorbidity in China: A 10-year prospective cohort study.

BACKGROUND AND AIMS: Cardiometabolic multimorbidity has become increasingly common over the past few decades. Little is known about how risk factors affect temporal progression of cardiometabolic multimorbidity. We aim to explore the role of socioeconomic, lifestyle, and clinical risk factors in the progression of cardiometabolic multimorbidity. METHODS AND RESULTS: This prospective cohort study included 56,587 participants aged ≥45 years who were free of diabetes, stroke, and heart disease. Three clusters of risk factors were assessed and each on a 5-point scale: socioeconomic, lifestyle, and clinical factors. We used multi-state models (MSMs) to examine the roles of risk factors in five transitions of multimorbidity trajectory: from healthy to first cardiometabolic disease, first cardiometabolic disease to cardiometabolic multimorbidity, health to mortality, first cardiometabolic disease to mortality, and cardiometabolic multimorbidity to mortality. In MSMs, socioeconomic (HR: 1.21; 95% CI: 1.19-1.25) and clinical (HR: 1.53; 95% CI: 1.51-1.56) scales were associated with the transition from health to first cardiometabolic. Socioeconomic (HR: 2.39; 95% CI: 2.24-2.54) and lifestyle (HR: 1.22; 95% CI: 1.18-1.26) scales were associated with the transitions from first disease to cardiometabolic multimorbidity. In addition, socioeconomic and lifestyle scales were associated with increased risk of mortality in people without cardiometabolic disease, with first cardiometabolic disease, and with cardiometabolic multimorbidity. CONCLUSIONS: Socioeconomic and lifestyle factors were not only important predictors of multimorbidity in those with existing cardiometabolic disease, but also important in shaping risk of mortality. However, clinical factors were the only key determinants of incidence of a first cardiometabolic disease.

Air pollutants, genetic factors, and risk of chronic kidney disease: Findings from the UK Biobank.

BACKGROUND: Experiment studies have suggested the emerging role of air pollutants in chronic kidney disease (CKD). However, only a few population studies conducted in Asia and North America have assessed their association, and the conclusions remained controversial. This study aims to investigate the effect of air pollutants exposure on CKD in the European population and first explores the modification effect of genetic risk on this association. METHODS: 458,968 participants from the UK Biobank were included in this study. Cox proportional hazards model was used to assess the associations of air pollutants (PM2.5, PM10, NO2, and NOx) with incident CKD. A genetic risk score of 53 single nucleotide polymorphisms was constructed to represent the genetic susceptibility to CKD. To assess the interaction effect between air pollutants and the genetic risk, we added a multiplicative interaction term and did a stratified analysis. RESULTS: During a median follow-up of 11.7 years, 16,637 incidents of CKD were identified. We observed positive associations between air pollutants exposure and CKD risk with the HRs for CKD were 1.09 (1.07, 1.11), 1.08 (1.06, 1.10), 1.05 (1.03, 1.07), 1.06 (1.04, 1.08) with per IQR (interquartile range) increment in PM2.5, PM10, NO2, and NOx, respectively. Stratified analysis showed that the associations between air pollutants and CKD were modest and marginal in the high genetic risk population (P > 0.05), while the associations were statistically significant in the low and intermediate genetic risk groups. CONCLUSIONS: Our study indicated that exposure to various air pollutants, including PM2.5, PM10, NO2, and NOx, was associated with an elevated risk of CKD. This finding provide evidence that formulating strategies to improve air quality can be helpful to reduce the burden of CKD.

Associations between short-term exposure of PM2.5 constituents and hospital admissions of cardiovascular diseases among 18 major Chinese cities.

Previous studies showed different risk effects on exposure of fine particulate matter (PM2.5) mass for cardiovascular disease (CVD) globally, which is likely due to different constituents of PM2.5. This study aimed to investigate the association between short-term exposure of PM2.5 constituents and hospital admissions of CVD. Daily counts of city-specific hospital admissions for CVD in 18 cities in China between 2014 and 2017 were extracted from the national Urban Employee Basic Medical Insurance database and the Beijing Municipal Commission of Health and Family Planning Information Center database. Directly measured PM2.5 constituents, including ions and polycyclic aromatic hydrocarbons, were collected by the Chinese Environmental Public Health Tracking system. We used the time-stratified case-crossover design to estimate the association between PM2.5 constituents and hospital admissions of CVD. Concentrations of ions accounted for the majority of the detected constituents. Excess risk (ER) of average ions concentrations for CVD was highest as 2.30% (95% CI: 1.62-2.99%) for NH4+, whose major sources are residential and agricultural emissions. This was followed by 1.85% (1.30-2.41%) for NO3- (generally from vehicles), 0.95% (0.28-1.63%) for SO42- (often from fossil fuel burning) respectively. The association for ions were generally consistent with ischemic heart disease (IHD) and ischemic stroke, e.g., NH4+ was associated with IHD (2.50%; 1.52-3.48%) and ischemic stroke (1.77%; 0.65-2.9%). For polycyclic aromatic hydrocarbons (PAHs), mainly from coal and vehicle-related oil combustion, the constituents were all associated with ischemic stroke but not for IHD. The ER for ischemic stroke was highest at 1.69% (0.99-2.39%) for indeno (123-cd) pyrene. Thus, in terms of the subtypes of CVD, the risks of hospital admissions varied with exposure to different PM2.5 constituents. Exposed to NH4+ had the highest risk to IHD and ischemic stroke, whereas PAHs were predominately associated with ischemic stroke only.