Long-term variations of urban-Rural disparities in infectious disease burden of over 8.44 million children, adolescents, and youth in China from 2013 to 2021: An observational study.

BACKGROUND: An accelerated epidemiological transition, spurred by economic development and urbanization, has led to a rapid transformation of the disease spectrum. However, this transition has resulted in a divergent change in the burden of infectious diseases between urban and rural areas. The objective of our study was to evaluate the long-term urban-rural disparities in infectious diseases among children, adolescents, and youths in China, while also examining the specific diseases driving these disparities. METHODS AND FINDINGS: This observational study examined data on 43 notifiable infectious diseases from 8,442,956 cases from individuals aged 4 to 24 years, with 4,487,043 cases in urban areas and 3,955,913 in rural areas. The data from 2013 to 2021 were obtained from China's Notifiable Infectious Disease Surveillance System. The 43 infectious diseases were categorized into 7 categories: vaccine-preventable, bacterial, gastrointestinal and enterovirus, sexually transmitted and bloodborne, vectorborne, zoonotic, and quarantinable diseases. The calculation of infectious disease incidence was stratified by urban and rural areas. We used the index of incidence rate ratio (IRR), calculated by dividing the urban incidence rate by the rural incidence rate for each disease category, to assess the urban-rural disparity. During the nine-year study period, most notifiable infectious diseases in both urban and rural areas exhibited either a decreased or stable pattern. However, a significant and progressively widening urban-rural disparity in notifiable infectious diseases was observed. Children, adolescents, and youths in urban areas experienced a higher average yearly incidence compared to their rural counterparts, with rates of 439 per 100,000 compared to 211 per 100,000, respectively (IRR: 2.078, 95% CI [2.075, 2.081]; p < 0.001). From 2013 to 2021, this disparity was primarily driven by higher incidences of pertussis (IRR: 1.782, 95% CI [1.705, 1.862]; p < 0.001) and seasonal influenza (IRR: 3.213, 95% CI [3.205, 3.220]; p < 0.001) among vaccine-preventable diseases, tuberculosis (IRR: 1.011, 95% CI [1.006, 1.015]; p < 0.001), and scarlet fever (IRR: 2.942, 95% CI [2.918, 2.966]; p < 0.001) among bacterial diseases, infectious diarrhea (IRR: 1.932, 95% CI [1.924, 1.939]; p < 0.001), and hand, foot, and mouth disease (IRR: 2.501, 95% CI [2.491, 2.510]; p < 0.001) among gastrointestinal and enterovirus diseases, dengue (IRR: 11.952, 95% CI [11.313, 12.628]; p < 0.001) among vectorborne diseases, and 4 sexually transmitted and bloodborne diseases (syphilis: IRR 1.743, 95% CI [1.731, 1.755], p < 0.001; gonorrhea: IRR 2.658, 95% CI [2.635, 2.682], p < 0.001; HIV/AIDS: IRR 2.269, 95% CI [2.239, 2.299], p < 0.001; hepatitis C: IRR 1.540, 95% CI [1.506, 1.575], p < 0.001), but was partially offset by lower incidences of most zoonotic and quarantinable diseases in urban areas (for example, brucellosis among zoonotic: IRR 0.516, 95% CI [0.498, 0.534], p < 0.001; hemorrhagic fever among quarantinable: IRR 0.930, 95% CI [0.881, 0.981], p = 0.008). Additionally, the overall urban-rural disparity was particularly pronounced in the middle (IRR: 1.704, 95% CI [1.699, 1.708]; p < 0.001) and northeastern regions (IRR: 1.713, 95% CI [1.700, 1.726]; p < 0.001) of China. A primary limitation of our study is that the incidence was calculated based on annual average population data without accounting for population mobility. CONCLUSIONS: A significant urban-rural disparity in notifiable infectious diseases among children, adolescents, and youths was evident from our study. The burden in urban areas exceeded that in rural areas by more than 2-fold, and this gap appears to be widening, particularly influenced by tuberculosis, scarlet fever, infectious diarrhea, and typhus. These findings underscore the urgent need for interventions to mitigate infectious diseases and address the growing urban-rural disparity.

Global burden of early-onset osteoarthritis, 1990-2019: results from the Global Burden of Disease Study 2019.

OBJECTIVES: Early-onset osteoarthritis (OA) is an emerging health issue amidst the escalating prevalence of overweight and obesity. However, there are scant data on its disease, economic burden and attributable burden due to high body mass index (BMI). METHODS: Using data from the Global Burden of Diseases Study 2019, we examined the numbers of incident cases, prevalent cases, years lived with disability (YLDs) and corresponding age-standardised rates for early-onset OA (diagnosis before age 55) from 1990 to 2019. The case definition was symptomatic and radiographically confirmed OA in any joint. The average annual percentage changes (AAPCs) of the age-standardised rates were calculated to quantify changes. We estimated the economic burden of early-onset OA and attributable burden to high BMI. RESULTS: From 1990 to 2019, the global incident cases, prevalent cases and YLDs of early-onset OA were doubled. 52.31% of incident OA cases in 2019 were under 55 years. The age-standardised rates of incidence, prevalence and YLDs increased globally and for countries in all Sociodemographic Index (SDI) quintiles (all AAPCs>0, p<0.05), with the fastest increases in low-middle SDI countries. 98.04% of countries exhibited increasing trends in all age-standardised rates. Early-onset OA accounts for US$46.17 billion in healthcare expenditure and US$60.70 billion in productivity loss cost in 2019. The attributable proportion of high BMI for early-onset OA increased globally from 9.41% (1990) to 15.29% (2019). CONCLUSIONS: Early-onset OA is a developing global health problem, causing substantial economic costs in most countries. Targeted implementation of cost-effective policies and preventive intervention is required to address the growing health challenge.

Long-term risk of psychiatric disorder and psychotropic prescription after SARS-CoV-2 infection among UK general population.

Despite evidence indicating increased risk of psychiatric issues among COVID-19 survivors, questions persist about long-term mental health outcomes and the protective effect of vaccination. Using UK Biobank data, three cohorts were constructed: SARS-CoV-2 infection (n = 26,101), contemporary control with no evidence of infection (n = 380,337) and historical control predating the pandemic (n = 390,621). Compared with contemporary controls, infected participants had higher subsequent risks of incident mental health at 1 year (hazard ratio (HR): 1.54, 95% CI 1.42-1.67; P = 1.70 × 10-24; difference in incidence rate: 27.36, 95% CI 21.16-34.10 per 1,000 person-years), including psychotic, mood, anxiety, alcohol use and sleep disorders, and prescriptions for antipsychotics, antidepressants, benzodiazepines, mood stabilizers and opioids. Risks were higher for hospitalized individuals (2.17, 1.70-2.78; P = 5.80 × 10-10) than those not hospitalized (1.41, 1.30-1.53; P = 1.46 × 10-16), and were reduced in fully vaccinated people (0.97, 0.80-1.19; P = 0.799) compared with non-vaccinated or partially vaccinated individuals (1.64, 1.49-1.79; P = 4.95 × 10-26). Breakthrough infections showed similar risk of psychiatric diagnosis (0.91, 0.78-1.07; P = 0.278) but increased prescription risk (1.42, 1.00-2.02; P = 0.053) compared with uninfected controls. Early identification and treatment of psychiatric disorders in COVID-19 survivors, especially those severely affected or unvaccinated, should be a priority in the management of long COVID. With the accumulation of breakthrough infections in the post-pandemic era, the findings highlight the need for continued optimization of strategies to foster resilience and prevent escalation of subclinical mental health symptoms to severe disorders.

Predicting recurrence and survival in patients with non-metastatic renal-cell carcinoma after nephrectomy: a prospective population-based study with multicenter validation.

BACKGROUND: Accurate prognostication of oncological outcomes is crucial for the optimal management of patients with renal cell carcinoma (RCC) after surgery. Previous prediction models were developed mainly based on retrospective data in the Western populations, and their predicting accuracy remains limited in contemporary, prospective validation. We aimed to develop contemporary RCC prognostic models for recurrence and overall survival (OS) using prospective population-based patient cohorts and compare their performance with existing, mostly utilized ones. METHODS: In this prospective analysis and external validation study, the development set included 11  128 consecutive patients with non-metastatic RCC treated at a tertiary urology center in China between 2006 and 2022, and the validation set included 853 patients treated at 13 medical centers in the USA between 1996 and 2013. The primary outcome was progression-free survival (PFS), and the secondary outcome was OS. Multivariable Cox regression was used for variable selection and model development. Model performance was assessed by discrimination [Harrell's C-index and time-dependent areas under the curve (AUC)] and calibration (calibration plots). Models were validated internally by bootstrapping and externally by examining their performance in the validation set. The predictive accuracy of the models was compared with validated models commonly used in clinical trial designs and with recently developed models without extensive validation. RESULTS: Of the 11  128 patients included in the development set, 633 PFS and 588 OS events occurred over a median follow-up of 4.3 years [interquartile range (IQR) 1.7-7.8]. Six common clinicopathologic variables (tumor necrosis, size, grade, thrombus, nodal involvement, and perinephric or renal sinus fat invasion) were included in each model. The models demonstrated similar C-indices in the development set (0.790 [95% CI 0.773-0.806] for PFS and 0.793 [95% CI 0.773-0.811] for OS) and in the external validation set (0.773 [0.731-0.816] and 0.723 [0.731-0.816]). A relatively stable predictive ability of the models was observed in the development set (PFS: time-dependent AUC 0.832 at 1 year to 0.760 at 9 years; OS: 0.828 at 1 year to 0.794 at 9 years). The models were well calibrated and their predictions correlated with the observed outcome at 3, 5, and 7 years in both development and validation sets. In comparison to existing prognostic models, the present models showed superior performance, as indicated by C-indices ranging from 0.722 to 0.755 (all P <0.0001) for PFS and from 0.680 to 0.744 (all P <0.0001) for OS. The predictive accuracy of the current models was robust in patients with clear-cell and non-clear-cell RCC. CONCLUSIONS: Based on a prospective population-based patient cohort, the newly developed prognostic models were externally validated and outperformed the currently available models for predicting recurrence and survival in patients with non-metastatic RCC after surgery. The current models have the potential to aid in clinical trial design and facilitate clinical decision-making for both clear-cell and non-clear-cell RCC patients at varying risk of recurrence and survival.

Use of Sex-Specific Body Mass Index to Optimize Low Correlation With Height and High Correlation With Fatness: A UK Biobank Study.

Body mass index (BMI; weight (kg)/height (m)2) is commonly used to measure general adiposity. However, evidence of its appropriateness for males and females remains inconsistent. We aimed to identify the most appropriate sex-specific power value that height should be raised to in the formula and the value that would make it achieve height independency and body fatness dependency. We randomly assigned UK Biobank participants recruited in the United Kingdom between 2006 and 2010 (n = 489,873; mean age = 56.5 years; 94.2% White) to training and testing sets (80%:20%). Using height raised to the power of -50.00 to 50.00, we identified the optimal power value that either minimized correlation with height or maximized correlation with body fat percentage, using age-adjusted correlations. The optimal power values for height were 1.77 for males and 1.39 for females. The new formulas resulted in 4.5% of females and 2.4% of males being reclassified into a different BMI category. The formulas did not show significant improvement (in terms of area under the receiver operating characteristic curve, sensitivity, and specificity) in identifying individuals with excessive body fat percentage or in predicting risk of all-cause mortality. Therefore, the conventional BMI formula is still valuable in research and disease screening for both sexes.

Observational methods for COVID-19 vaccine effectiveness research: an empirical evaluation and target trial emulation.

BACKGROUND: There are scarce data on best practices to control for confounding in observational studies assessing vaccine effectiveness to prevent COVID-19. We compared the performance of three well-established methods [overlap weighting, inverse probability treatment weighting and propensity score (PS) matching] to minimize confounding when comparing vaccinated and unvaccinated people. Subsequently, we conducted a target trial emulation to study the ability of these methods to replicate COVID-19 vaccine trials. METHODS: We included all individuals aged ≥75 from primary care records from the UK [Clinical Practice Research Datalink (CPRD) AURUM], who were not infected with or vaccinated against SARS-CoV-2 as of 4 January 2021. Vaccination status was then defined based on first COVID-19 vaccine dose exposure between 4 January 2021 and 28 January 2021. Lasso regression was used to calculate PS. Location, age, prior observation time, regional vaccination rates, testing effort and COVID-19 incidence rates at index date were forced into the PS. Following PS weighting and matching, the three methods were compared for remaining covariate imbalance and residual confounding. Last, a target trial emulation comparing COVID-19 at 3 and 12 weeks after first vaccine dose vs unvaccinated was conducted. RESULTS: Vaccinated and unvaccinated cohorts comprised 583 813 and 332 315 individuals for weighting, respectively, and 459 000 individuals in the matched cohorts. Overlap weighting performed best in terms of minimizing confounding and systematic error. Overlap weighting successfully replicated estimates from clinical trials for vaccine effectiveness for ChAdOx1 (57%) and BNT162b2 (75%) at 12 weeks. CONCLUSION: Overlap weighting performed best in our setting. Our results based on overlap weighting replicate previous pivotal trials for the two first COVID-19 vaccines approved in Europe.

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.

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.

Urban-Rural Disparity in Mortality Patterns of Respiratory Diseases Among Older Adults - China, 1987-2021.

What is already known about this topic?: Respiratory diseases (RDs) are the primary cause of death in older adults in China. However, there is limited evidence regarding the disparity in mortality rates of RDs between urban and rural areas among the elderly population. What is added by this report?: The age-standardized mortality rate (ASMR) due to RDs in the elderly population in both urban and rural areas of China has shown a consistent decrease. This trend is observed in both males and females. However, there was no significant change in the average annual percentage of ASMR for pneumonia among the urban elderly population and rural elderly men throughout the study period. What are the implications for public health practice?: Efforts should be made in China to reduce mortality from chronic lower respiratory disease and pneumonia among the elderly, particularly in urban populations.

Disparity in spectrum of infectious diseases between in-school and out-of-school children, adolescents, and youths in China: findings from a successive national surveillance from 2013 to 2021.

Background: An accelerated epidemiological transition, economic development and urbanization have brought rapid reductions but a potential disparity in infectious diseases burdens in-school and out-of-school children, adolescents, and youths in China. This paper assesses the disparity in spectrum of infectious diseases between two groups, and described disparity's variation by age, year and province, and determined the priority diseases. Methods: A total of 7,912,274 new incident cases (6,159,021 in school and 1,753,253 out of school) aged 6-21 years across 43 notifiable infectious diseases have been collected based on China's Notifiable Infectious Disease Surveillance System from 2013 to 2021. All infectious diseases are categorized into seven categories: vaccine preventable, bacteria, gastrointestinal and enterovirus, sexually transmitted and bloodborne, vectorborne, zoonotic, and quarantinable diseases. We used the index of incidence rate ratio (IRR) of by specific disease, category, year, and age to assess the disparity between those out-of-school and in-school, and determine their separate priority diseases. Findings: From 2013 to 2021, a small disparity of notifiable infectious diseases existed with higher average yearly incidence for out-of-school children, adolescents, and youth than that in-school (327.601 v.s. 319.677 per 100,000, IRR = 1.025, 95%CI: 1.023-1.027, standardized IRR = 1.169, 95%CI: 1.155-1.183), and it gradually narrowed by surveillance years with IRR from 1.351 in 2013 to 1.015 in 2021 due to large decreased disparity in compulsory education stage group. Such disparity was mainly driven by sexually transmitted and bloodborne diseases, bacteria diseases, vectorborne diseases, quarantinable diseases and zoonotic diseases. However, vaccine preventable diseases, gastrointestinal and enterovirus diseases showed higher incidence of infectious diseases for those in-school than that out-of-school, particularly for seasonal influenza, mumps and hand-foot-and-mouth disease. Meanwhile, such disparity is obvious in most of ages and in eastern and coastal regions of China, and the narrowing trend is attributed to six categories diseases, except for sexually transmitted and bloodborne diseases with gradually widened disparity between two groups with surveillance years with IRR from 22.939 in 2013 to 23.291 in 2021 due to large disparity for those who have completed compulsory education. Interpretation: A huge achievement has been achieved in reducing the burden and disparity of infectious diseases between out-of-school and in-school children, adolescents, and youths in China, particularly for the compulsory education stage population. The priorities for the coming decades will be to extend successful strategies to a broad scope and promote education, particularly for the investment of social health resources and the improvement of personal health literacy in the non-compulsory education stage. This should involve extending the years of compulsory school, improving sex health education, strengthening monitoring, expanding immunization programs coverage and prioritizing the prevention and control of sexually transmitted diseases and tuberculosis among out-of-school population. Funding: National Natural Science Foundation of China and Beijing Natural Science Foundation.

Genetic risk, adherence to healthy lifestyle and acute cardiovascular and thromboembolic complications following SARS-COV-2 infection.

Current understanding of determinants for COVID-19-related cardiovascular and thromboembolic (CVE) complications primarily covers clinical aspects with limited knowledge on genetics and lifestyles. Here, we analysed a prospective cohort of 106,005 participants from UK Biobank with confirmed SARS-CoV-2 infection. We show that higher polygenic risk scores, indicating individual's hereditary risk, were linearly associated with increased risks of post-COVID-19 atrial fibrillation (adjusted HR 1.52 [95% CI 1.44 to 1.60] per standard deviation increase), coronary artery disease (1.57 [1.46 to 1.69]), venous thromboembolism (1.33 [1.18 to 1.50]), and ischaemic stroke (1.27 [1.05 to 1.55]). These genetic associations are robust across genders, key clinical subgroups, and during Omicron waves. However, a prior composite healthier lifestyle was consistently associated with a reduction in all outcomes. Our findings highlight that host genetics and lifestyle independently affect the occurrence of CVE complications in the acute infection phrase, which can guide tailored management of COVID-19 patients and inform population lifestyle interventions to offset the elevated cardiovascular burden post-pandemic.

Air pollution, alcohol consumption, and the risk of elevated liver enzyme levels: a cross-sectional study in the UK Biobank.

Evidences on the association between exposure to air pollution and liver enzymes was scarce in low pollution area. We aimed to investigate the association between air pollution and liver enzyme levels and further explore whether alcohol intake influence this association. This cross-sectional study included 425,773 participants aged 37 to 73 years from the UK Biobank. Land Use Regression was applied to assess levels of PM2.5, PM10, NO2, and NOx. Levels of liver enzymes including AST, ALT, GGT, and ALP were determined by enzymatic rate method. Long-term low-level exposure to PM2.5 (per 5-µg/m3 increase) was significantly associated with AST (0.596% increase, 95% CI, 0.414 to 0.778%), ALT (0.311% increase, 0.031 to 0.593%), and GGT (1.552% increase, 1.172 to 1.933%); The results were similar for PM10; NOX and NO2 were only significantly correlated with AST and GGT Significant modification effects by alcohol consumption were found (P-interaction < 0.05). The effects of pollutants on AST, ALT, and GGT levels gradually increased along with the weekly alcohol drinking frequency. In conclusion, long-term low-level air pollutants exposure was associated with elevated liver enzyme levels. And alcohol intake may exacerbate the effect of air pollution on liver enzymes.

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.

Lifestyle, Genetic Susceptibility, and the Risk of Idiopathic Pulmonary Fibrosis: A Large Prospective Cohort Study.

BACKGROUND: Lifestyle is an important contributor of age-related chronic disease, but the association between lifestyle and the risk of idiopathic pulmonary fibrosis (IPF) remains unknown. The extent to which genetic susceptibility modifies the effects of lifestyle on IPF also remains unclear. RESEARCH QUESTION: Is there a joint effect or interaction of lifestyle and genetic susceptibility on the risk of developing IPF? STUDY DESIGN AND METHODS: This study included 407,615 participants from the UK Biobank study. A lifestyle score and a polygenic risk score were constructed separately for each participant. Participants were then classified into three lifestyle categories and three genetic risk categories based on the corresponding score. Cox models were fitted to assess the association of lifestyle and genetic risk with the risk of incident IPF. RESULTS: With favorable lifestyle as the reference group, intermediate lifestyle (hazard ratio, 1.384; 95% CI, 1.218-1.574) and unfavorable lifestyle (hazard ratio, 2.271; 95% CI, 1.852-2.785) were significantly associated with an increased risk of IPF. For the combined effect of lifestyle and polygenic risk score, participants with unfavorable lifestyle and high genetic risk had the highest risk of IPF (hazard ratio, 7.796; 95% CI, 5.482-11.086) compared with those with favorable lifestyle and low genetic risk. Moreover, approximately 32.7% (95% CI, 11.3-54.1) of IPF risk could be attributed to the interaction of an unfavorable lifestyle and high genetic risk. INTERPRETATION: Exposure to unfavorable lifestyle significantly increased the risk of IPF, particularly in those with high genetic risk.

Long-term Exposure to Ambient Air Pollutants and Increased Risk of Pneumonia in the UK Biobank.

BACKGROUND: Short-term exposure to air pollution has been linked to pneumonia risk. However, evidence on the long-term effects of air pollution on pneumonia morbidity is scarce and inconsistent. We investigated the associations of long-term air pollutant exposure with pneumonia and explored the potential interactions with smoking. RESEARCH QUESTION: Is long-term exposure to ambient air pollution associated with the risk of pneumonia, and does smoking modify the associations? STUDY DESIGN AND METHODS: We analyzed data in 445,473 participants without pneumonia within 1 year before baseline from the UK Biobank. Annual average concentrations of particulate matter (particulate matter with a diameter < 2.5 µm [PM2.5] and particulate matter with a diameter < 10 µm [PM10]), nitrogen dioxide (NO2), and nitrogen oxides (NOx) were estimated using land-use regression models. Cox proportional hazards models were used to assess the associations between air pollutants and pneumonia incidence. Potential interactions between air pollution and smoking were examined on both additive and multiplicative scales. RESULTS: The hazard ratios of pneumonia for each interquartile range increase in PM2.5, PM10, NO2, and NOx concentrations were 1.06 (95% CI, 1.04-1.08), 1.10 (95% CI, 1.08-1.12), 1.12 (95% CI, 1.10-1.15), and 1.06 (95% CI, 1.04-1.07), respectively. There were significant additive and multiplicative interactions between air pollution and smoking. Compared with individuals who had never smoked with low air pollution exposure, individuals who had ever smoked with high air pollution exposure had the highest pneumonia risk (PM2.5: hazard ratio [HR], 1.78; 95% CI, 1.67-1.90; PM10: HR, 1.94; 95% CI, 1.82-2.06; NO2: HR, 2.06; 95% CI, 1.93-2.21; NOx: HR, 1.88; 95% CI, 1.76-2.00). The associations between air pollutants and pneumonia risk persisted in participants exposed to air pollutants concentrations meeting the European Union limits. INTERPRETATION: Long-term exposure to air pollutants was associated with an increased risk of pneumonia, especially in individuals who smoke.

Exposure to various ambient air pollutants and 9 cardiovascular conditions among individuals with diabetes: A prospective analysis of the UK Biobank.

BACKGROUND AND AIMS: The adverse effects of air pollutants on the risk of most cardiovascular diseases (CVDs) are well-established, but the risk of CVDs such as deep vein thrombosis, pulmonary embolism, or aortic valve stenosis have been underappreciated, especially in the diabetic population. This study aimed to evaluate associations between long-term air pollutants exposure and the risk of incident CVDs among participants with diabetes. METHODS: This study included 27,827 participants with baseline diabetes from the UK Biobank. We then estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for CVDs associated with chronic air pollutant exposure in the diabetic population by fitting the Cox proportional hazards model. Moreover, we investigated the cardiovascular effects of air pollutants at concentrations below WHO guideline limits. RESULTS: After multivariable adjustment, long-term NO2 and NOx exposures were positively associated with the development of 8 and 6 types of CVDs in participants with diabetes, respectively. In term of particulate matters, the effect estimates ranged from 1.51 (1.13, 2.03) (coronary artery disease) to 4.65 (2.73, 7.92) (peripheral arterial disease) per 10 µg/m3 increase in PM2.5. Whereas, the effect estimates ranged from 1.15 (1.04, 1.27) (arterial hypertension) to 2.28 (1.40, 3.69) (pulmonary embolism) per 10 µg/m3 increase in PM10. In addition, our study discovered that for most of the cardiovascular events (8 of 9), the deleterious effects of air pollutants persisted even when participants were exposed to air pollutants concentrations below WHO guideline limits. CONCLUSIONS: Long-term exposure to ambient NO2, NOx, PM2.5, and PM10, either at normal or low level, increased risk of various cardiovascular outcomes in the diabetic population.

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.

Changing Patterns in Cancer Mortality from 1987 to 2020 in China.

BACKGROUND: China has the highest number of new cancer cases and deaths worldwide, posing huge health and economic burdens to society and affected families. This study comprehensively analyzed secular trends of national cancer mortality statistics to inform future prevention and intervention programs in China. METHODS: The annual estimate of overall cancer mortality and its major subtypes were derived from the National Health Commission (NHC). Joinpoint analysis was used to detect changes in trends, and we used age-period-cohort modeling to estimate cohort and period effects in Cancers between 1987 and 2020. Net drift (overall annual percentage change), local drift (annual percentage change in each age group), longitudinal age curves (expected longitudinal age-specific rate), and period (cohort) relative risks were calculated. RESULTS: The age-standardized cancer mortality in urban China has shown a steady downward trend but has not decreased significantly in rural areas. Almost all cancer deaths in urban areas have shown a downward trend, except for colorectal cancer in men. Decreasing mortality from cancers in rural of the stomach, esophagus, liver, leukemia, and nasopharynx was observed, while lung, colorectal cancer female breast, and cervical cancer mortality increased. Birth cohort risks peaked in the cohorts born around 1920-1930 and tended to decline in successive cohorts for most cancers except for leukemia, lung cancer in rural, and breast and cervical cancer in females, whose relative risks were rising in the very recent cohorts. In addition, mortality rates for almost all types of cancer in older Chinese show an upward trend. CONCLUSIONS: Although the age-standardized overall cancer mortality rate has declined, and the urban-rural gap narrowed, the absolute cancer cases kept increasing due to the growing elderly population in China. The rising mortality related to lung, colorectal, female breast, and cervical cancer should receive higher priority in managing cancer burden and calls for targeted public health actions to reverse the trend.

Risk of COVID-19 Diagnosis and Hospitalisation in Patients with Osteoarthritis or Back Pain Treated with Ibuprofen Compared to Other NSAIDs or Paracetamol: A Network Cohort Study.

OBJECTIVE: We aimed to investigate whether ibuprofen use, compared with other non-selective non-steroidal anti-inflammatory drugs (ns-NSAIDs), cyclooxygenase-2 inhibitors (COX-2i) or paracetamol, increases the risk of coronavirus disease 2019 (COVID-19) diagnosis or hospitalisation. DESIGN: A prevalent user and active comparator cohort study. SETTING: Two US claims databases (Open Claims and PharMetrics Plus) mapped to the Observational Medical Outcomes Partnership Common Data Model. PARTICIPANTS: Insured patients with a history of osteoarthritis or back pain and receiving ibuprofen, other ns-NSAIDs, COX-2i or paracetamol between 1 November, 2019 and 31 January, 2020 (study enrolment window 1) or between 1 February, 2020 and 31 October, 2020 (study enrolment window 2). MAIN OUTCOME MEASURES: Large-scale propensity score matching and empirical calibration were used to minimise confounding. Incidence and hazard ratios of COVID-19 diagnosis and hospitalisation according to drug/s use were estimated and pooled in the same study period across data sources using a fixed-effects meta-analysis. Index treatment episode was the primary risk evaluation window, censored at the time of discontinuation. RESULTS: A total of 633,562 and 1,063,960 participants were included in periods 1 and 2, respectively, for the ibuprofen versus ns-NSAIDs comparison, 311,669 and 524,470 for ibuprofen versus COX-2i, and 492,002 and 878,598 for ibuprofen versus paracetamol. Meta-analyses of empirically calibrated hazard ratios revealed no significantly differential risk of COVID-19 outcomes in users of ibuprofen versus any of the other studied analgesic classes: hazard ratios were 1.13 (0.96-1.33) for the ibuprofen-ns-NSAIDs comparison, 1.03 (0.83-1.28) for the ibuprofen-COX-2i comparison and 1.13 (0.74-1.73) for ibuprofen-paracetamol comparison on COVID-19 diagnosis in the February 2020-October 2020 window. Similar hazard ratios were found on COVID-19 hospitalisation and across both study periods. CONCLUSIONS: In patients with osteoarthritis or back pain, we found no differential risks of incident COVID-19 diagnosis or COVID-19 hospitalisation for ibuprofen users compared with other ns-NSAIDs, COX-2i or paracetamol. Our findings support regulatory recommendations that NSAIDs, including ibuprofen, should be prescribed as indicated in the same way as before the COVID-19 pandemic, especially for those who rely on ibuprofen or NSAIDs to manage chronic arthritis or musculoskeletal pain symptoms.